API Hub MCP — 337+ Tools
Server Quality Checklist
Latest release: v2.4.2
- Disambiguation2/5
With 338 tools, there is substantial overlap in functionality, especially in text transformation (e.g., multiple case conversion tools) and readability analysis (e.g., over a dozen readability formulas). Many tools have very similar purposes, making it difficult for agents to choose the correct one without extensive description parsing.
Naming Consistency3/5Most tools follow a verb_noun underscore_case pattern, but there are many exceptions like single-word names (health, sentiment, social), gerunds (alternating_case), adjectives (age_appropriate), and inconsistent abbreviations (calc vs calculator). This mixed convention reduces predictability.
Tool Count1/5338 tools is excessively high for any MCP server. While the server attempts to be a comprehensive utility hub, the sheer number overwhelms agents and likely degrades performance. A more focused subset would be far more usable and coherent.
Completeness3/5The server covers an extremely broad range of domains (text, math, finance, health, web, colors, etc.), but the lack of clear focus means there are always gaps. Many areas have redundant tools while other common tasks (e.g., image processing, database operations) are missing. It feels like a collection rather than a designed surface.
Average 3.5/5 across 298 of 338 tools scored. Lowest: 1/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 27 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under Apache 2.0.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
This server has been verified by its author.
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How to sync the server with GitHub?
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To manually sync the server, click the "Sync Server" button in the MCP server admin interface.
How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description is a placeholder, so there is no disclosure of behavioral traits such as side effects, permissions needed, or output behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness1/5Is the description appropriately sized, front-loaded, and free of redundancy?
While extremely concise, the description is under-specified to the point of being useless. It does not earn its place; a single character placeholder is not a valid description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of the tool (5 parameters, sibling tools of similar nature), the description is completely inadequate. It fails to leverage the output schema or provide any context for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no meaning beyond the input schema. With 0% schema description coverage and a placeholder description, the agent receives no additional context for parameters like 'to', 'tool', 'desc', or 'params_desc'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5Does the description clearly state what the tool does and how it differs from similar tools?
The description is a placeholder '{d}' that provides no information about what the tool does. It fails to state a verb, resource, or scope, making it impossible for an agent to understand the tool's purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is given. The description does not indicate when to use this tool, when not to use it, or how it differs from sibling tools like 'summarize' or 'paraphrase'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description (placeholder) gives no behavioral traits. Agent learns nothing about side effects, permissions, or return behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness1/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short but meaningless. It does not earn its place; it provides zero value to the agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters and many siblings, the description is completely inadequate. It lacks any information about usage, behavior, or parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 5 parameters with 0% description coverage, and the tool description is a placeholder. It adds no meaning beyond property names and types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5Does the description clearly state what the tool does and how it differs from similar tools?
The description is '{d}', a placeholder that provides no indication of what the tool does. It does not specify a verb or resource, nor does it distinguish from any sibling.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is provided. Agent has no information on when to use this tool versus alternatives, and given many sibling tools, this is critical.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavioral traits. The placeholder text provides no such information, leaving the agent unaware of side effects, permissions, or operational characteristics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness1/5Is the description appropriately sized, front-loaded, and free of redundancy?
While extremely short, the description is not concise in a meaningful way; it is under-specified to the point of uselessness. Every sentence (or placeholder) should add value, but '{d}' adds none.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description does not explain what the tool returns or how it behaves. Given the tool has 5 parameters and is among many similar siblings, the description is completely inadequate for a proper understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the input schema provides no descriptions for the 5 parameters (text required, to, tool, desc, params_desc). The description fails to add any meaning beyond parameter names, so it does not help the agent understand how to use these parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5Does the description clearly state what the tool does and how it differs from similar tools?
The description is literally '{d}', which is a placeholder and provides no information about what the tool does. It fails to state any verb or resource, making it impossible to discern the tool's purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is given. The description does not indicate when to use this tool versus any of the many sibling tools, nor does it mention any conditions or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are given, and the description '{d}' offers no behavioral traits. The tool's side effects, permissions, or response format are completely unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness1/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is too minimal ('{d}'), which is under-specification rather than conciseness. It fails to provide necessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description is missing, leaving the tool's behavior largely undefined. The context is incomplete for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no meaning to the parameters. Although the schema includes defaults for 'desc' and 'params_desc', the description itself does not explain any parameter beyond what is in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5Does the description clearly state what the tool does and how it differs from similar tools?
The description is a placeholder '{d}' and does not define the tool's purpose. The name 'headline' suggests headline generation, but the description provides no clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is provided. The description lacks any context on when to use this tool versus its many siblings like 'generate_slogan' or 'create_metaphor'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No behavioral traits are disclosed. The description is '{d}' and there are no annotations to provide context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness1/5Is the description appropriately sized, front-loaded, and free of redundancy?
While extremely short, this is under-specification, not conciseness. The description is '{d}', which is inadequate.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters and no output schema description, the description does not provide enough context for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description is empty and adds no meaning beyond the input schema. Schema description coverage is 0%, and the description does not compensate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5Does the description clearly state what the tool does and how it differs from similar tools?
The description is '{d}', which provides no information about what the tool does. It does not state the verb or resource. The default value of the 'desc' parameter indicates the tool extracts keywords, but that is not the tool description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool or alternatives. The description is empty.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description offers no behavioral details. The agent cannot infer side effects, required permissions, or any constraints beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness1/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single placeholder token, which is not concise but severely underspecified. It fails to provide any structure or useful content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the high number of sibling tools related to text processing, the description should clearly differentiate this tool's scope and limitations. It does not, leaving the agent without sufficient context to choose it appropriately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, and the description provides no additional meaning for parameters like 'text', 'to', 'tool', 'desc', or 'params_desc'. Default values exist but their purpose is unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5Does the description clearly state what the tool does and how it differs from similar tools?
The description is a placeholder '{d}' with no information. The name 'paraphrase' implies rewriting text, but the description fails to state a specific verb or resource, making it impossible for an agent to understand the tool's purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description is empty, so there is no context about when to use this tool versus alternatives like 'rewrite_content' or 'summarize'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided and description is empty, so no behavioral information is disclosed. The description carries full burden and fails entirely.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness1/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short but is a placeholder, not concise. It fails to earn its place by providing any useful content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters, no schema descriptions, no annotations, and an output schema, the description is entirely inadequate for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and description '{d}' adds no meaning to the five parameters. The description does not compensate for missing param info.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5Does the description clearly state what the tool does and how it differs from similar tools?
Description is '{d}', a placeholder with no verb or resource, providing no purpose information. It fails to state what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No description content, so no guidance on when to use this tool versus sibling tools like 'quiz' or others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits. The placeholder offers no information.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness1/5Is the description appropriately sized, front-loaded, and free of redundancy?
While extremely short, it is under-specified and not useful. Every sentence should earn its place, but this placeholder earns nothing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity and the presence of sibling tools, the description is completely inadequate. It fails to provide any context for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 5 parameters but 0% coverage from descriptions. The description adds no meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5Does the description clearly state what the tool does and how it differs from similar tools?
The description is simply '{d}', which is a placeholder and provides no indication of the tool's purpose. It does not state what the tool does at all.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. The description is absent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description is empty, so no behavioral traits are disclosed. The agent has no insight into side effects or requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness1/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single placeholder character, which is too minimal. It fails to provide any useful information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's likely complexity (5 parameters, many siblings), the description is completely inadequate. It does not explain the tool's purpose or how it relates to other tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no meaning to the parameters. Schema coverage is 0%, and the description does not explain what each parameter does beyond the schema's defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5Does the description clearly state what the tool does and how it differs from similar tools?
The description '{d}' is a placeholder and does not state what the tool does. No verb or resource is identified.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is provided. There is no information on when or when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations and a placeholder description, there is no disclosure of side effects, permissions, or other behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness1/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single placeholder character, which is not a valid description. It fails to provide any information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists but no description, the tool is incomplete. The agent cannot determine how 'summarize' differs from similar tools like 'tldr'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% and the description adds nothing. Parameters like 'desc' and 'params_desc' seem to contain documentation but are not explained in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5Does the description clearly state what the tool does and how it differs from similar tools?
The description is a placeholder '{d}', providing no verb or resource. It fails to state what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs. siblings like 'tldr' or 'paraphrase'. The description is absent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No behavioral traits are disclosed. There are no annotations, and the description gives no insight into side effects, permissions, or other behavioral aspects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness1/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short but not concise in a helpful way. It is a placeholder and provides no value; under-specification is not conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complete lack of useful description and no output schema visible, the description is completely inadequate for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, meaning no parameter descriptions exist in the schema. The description does not add any meaning to the parameters; it is entirely uninformative.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5Does the description clearly state what the tool does and how it differs from similar tools?
The description is just "{d}", a placeholder that does not state what the tool does. It fails to convey any purpose, and the name 'tldr' alone is ambiguous without context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not indicate when to use this tool versus alternatives like 'summarize' or 'headline' among the siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No behavioral information beyond the placeholder. No annotations are provided, and the description adds no context about side effects, permissions, or limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness1/5Is the description appropriately sized, front-loaded, and free of redundancy?
While extremely short, the content is a placeholder with zero useful information. It is under-specified rather than concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 5 parameters and no schema coverage, a placeholder description is completely inadequate. It lacks any information needed for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain any parameter's meaning. The placeholder contributes nothing to parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5Does the description clearly state what the tool does and how it differs from similar tools?
Description is merely a placeholder '{d}', providing no indication of what the tool does. It fails to specify the verb, resource, or any distinguishing characteristics from sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description lacks any context on suitable scenarios or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description is empty. Does not disclose any behavioral traits such as side effects, permissions, or output characteristics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely short but underspecified—'{d}' is not concise but incomplete. Lacks informative content, reducing its value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has 5 parameters, output schema, and many sibling tools, yet the description provides no context. Fails to give any meaningful guidance for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, requiring the description to compensate. The description is empty, so it adds no meaning beyond the schema's parameter titles and defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5Does the description clearly state what the tool does and how it differs from similar tools?
Description is '{d}', a placeholder that provides no information about what the tool does. While the name 'faq' hints at FAQ generation, the description itself is missing and misleading.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus sibling tools. Description is empty, offering no context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description gives no behavioral details. The agent has no information about side effects, permissions, or return behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness1/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single placeholder string, which is under-specification rather than concise. It does not earn its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 5 parameters and an output schema, the description is completely inadequate. An agent cannot understand the tool's purpose or usage from '{d}'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description does not add any meaning to the parameters. The schema shows parameter names and defaults but no descriptions, and the description is just '{d}'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5Does the description clearly state what the tool does and how it differs from similar tools?
The description is '{d}', which is a placeholder and provides no information about what the tool does. It fails to state the verb or resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The sibling tools list is extensive, but the description offers no context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description is a placeholder. There is no disclosure of behavioral traits such as mutation, permissions, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is under-specified, consisting only of '{d}'. It is not concise in a helpful sense; it fails to convey any useful information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the large set of sibling tools and the absence of a meaningful description, the tool definition is completely inadequate for an agent to understand when to use it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool description adds no parameter meaning. While the schema's default for 'desc' and 'params_desc' provide some clues, these are not part of the description. Schema coverage is 0% from the description's perspective.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5Does the description clearly state what the tool does and how it differs from similar tools?
The description is a placeholder '{d}', which does not state the tool's purpose. The default value for the 'desc' parameter hints at grammar fixing, but the official description is missing, making it misleading.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description is absent, offering no context on when to use this tool versus alternatives like 'proofread' or 'paraphrase'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose the calculation formula, handling of edge cases, or what the output contains. With no annotations, the description fails to provide essential behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and straightforward, but lacks necessary detail. It is not overly verbose, but the brevity sacrifices completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a calculation tool, the description is incomplete. It does not mention the formula, expected output (despite an output schema existing), or how to interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description merely lists parameter names without explaining their units or definitions (e.g., 'efficiency' could be mpg or kmpl). Schema coverage is 0%, so no additional meaning is provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates fuel cost for a journey, which is specific and distinguishes it from general calculation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool instead of other cost or calculation tools, nor any context about prerequisites or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description only says 'simplify complex text'. It does not disclose how simplification works (e.g., preserves meaning, reduces length) or any implications like language support or input limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short, but its brevity sacrifices utility. It uses minimal words but omits critical details that would help an agent understand its purpose fully.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of many similar sibling tools and an output schema, the description should provide more context about output format or behavior. It is incomplete for an AI agent to reliably select and invoke this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description merely restates the parameter 'text' as 'Text to simplify', adding no meaningful detail beyond the schema. It does not compensate for the low coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool simplifies complex text into plain language, which is clear but generic. It does not differentiate from many sibling tools like 'paraphrase', 'rewrite_content', or 'summarize', making it hard for an agent to choose among them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description lacks any context about prerequisites, exclusions, or recommended use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It mentions 'detailed breakdown' but does not elaborate on what the breakdown includes, output format, or any side effects, leaving significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short, which is concise, but it omits essential details like usage guidance and behavioral context. Every sentence is present but incomplete, so it does not earn its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of many sibling tools and the lack of usage guidance, the description is insufficient. The output schema may cover the breakdown, but the description does not reference it or provide enough context for correct selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must add meaning. It only restates the parameter name and gives a vague purpose ('Text to analyze for tone'), without specifying constraints like length, encoding, or format. Minimal added value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it analyzes tone, emotion, and sentiment with a detailed breakdown, which is specific. However, it does not differentiate from sibling tools like 'sentiment' that may perform similar analysis, so it loses some clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, exclusions, or context for use, leaving the agent without direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description fails to disclose what readability formula is used, how distribution is computed, or if it returns sentence/paragraph-level scores.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short, which could be considered concise, but it lacks structure such as sections or examples.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description does not mention the output format or how readability distribution is presented, leaving significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the parameter description only states 'Text to analyze readability distribution for,' adding minimal value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it analyzes readability distribution across sentences/paragraphs, distinguishing it from sibling readability tools that focus on single scores or other metrics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like analyze_readability or specific readability score tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does not disclose whether matching is case-sensitive, whether repeated words must be consecutive, or what the output format is. This lack of detail hinders correct usage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, consisting of one sentence and a parameter line. While brevity is positive, it sacrifices important details. The structure is straightforward but could benefit from additional information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (one string parameter) and presence of an output schema, the description could still be more informative. It lacks details on what constitutes 'repeated words' and how results are presented, making it incomplete for confident use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage. The description adds 'Text to find repeated words in.' which provides minimal context but still does not clarify constraints like case sensitivity or word boundaries. It adds little value beyond the parameter name.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Find repeated or duplicated words in text.' which is a specific verb and resource. It clearly indicates the tool's function, though it does not differentiate from siblings like 'word_frequency' or 'unique_words'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, edge cases, or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must explain behavior. It only says 'comprehensive text statistics' without listing what specific metrics are included or any limitations (e.g., length, encoding).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
Description is short and includes a parameters section, but the format is minimal. It is concise but could be better structured with details about what statistics are included.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given many sibling tools for specific counts, this tool's description should list included metrics to help selection. It fails to do so, leaving the agent unsure of what 'comprehensive' covers. Output schema exists but not referenced.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. It adds a brief line 'text — Text to analyze with full statistics,' which clarifies the parameter's role but lacks detail on format or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it provides 'comprehensive text statistics including all counts and metrics,' which identifies its purpose. However, it does not differentiate from sibling tools that offer specific statistics like char_count or word_count.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The description implies it covers multiple metrics, but does not state when a user should choose this over more specific tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only states the tool calculates the Gunning Fog index, omitting any details about input constraints, format requirements, or result interpretation. This is insufficient for a tool that calculates a specific readability metric.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief with two sentences, no wasted words, and front-loaded information. However, it may be too concise given the lack of behavioral context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having a simple single-parameter input and an output schema, the description lacks essential context about the Gunning Fog index's meaning, interpretation, or usage scenarios. With many readability siblings, more completeness is needed to help the agent select the correct tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description reiterates the parameter name 'text' but adds little beyond the schema's title. It does not explain what constitutes valid text (e.g., length, language, formatting) or provide examples, so it adds minimal value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool calculates the Gunning Fog index for text readability, specifying a verb and resource. However, it does not distinguish itself from sibling readability tools like 'fry_readability' or 'smog_index', which limits its clarity in a crowded context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites. Given the many sibling readability tools, this is a significant gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description does not disclose behavioral traits such as output format, side effects, or how paragraph structure is analyzed. The agent is left guessing what 'analyze paragraph structure' entails.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short and to the point, with no unnecessary words. It is front-loaded with the main purpose. However, the parameter list could be integrated more naturally.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool is simple, the description lacks details about what 'analyze paragraph structure' includes. With an output schema present, return values are not needed, but the behavioral ambiguity leaves it incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides a brief clarification for the 'text' parameter ('Text to count paragraphs in.'), which adds some meaning beyond the schema's type. However, given the schema has 0% description coverage, more detail would be beneficial.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it counts paragraphs and analyzes structure, but does not differentiate from siblings like line_count, word_count, or char_count. The phrase 'analyze paragraph structure' is vague and could mean different things.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as line_count or sentence_length_analyze. No explicit conditions or exclusions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose how proofreading is performed (e.g., AI-based, rule-based), what the return format is, or any limitations. The tool's behavior is opaque.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise, with a single sentence and a parameter list. However, it may be too sparse, lacking essential details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Although an output schema exists, the description does not explain what the tool returns (e.g., corrected text, error list). For a proofreading tool, this is a significant gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'text' is described only as 'Text to proofread', adding minimal value beyond the schema's type definition. No additional constraints or format details are given, and schema description coverage is 0%.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it proofreads text for grammar, spelling, punctuation, and style issues, providing a specific verb and resource. However, it does not differentiate from the sibling tool 'grammar', which may have overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'grammar' or 'paraphrase'. The description lacks context for appropriate scenarios or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries full responsibility. It only states the tool scrapes from 'any URL' and lists meta tag types, but fails to disclose behaviors like error handling, rate limits, or whether it follows redirects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise at two sentences, but the second sentence essentially restates the parameter definition already present in the schema. It could be structured more efficiently to include additional context without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema (not shown but known from context), so return values are documented elsewhere. However, for a simple tool, the description is adequate but lacks usage context like expected input formats or example calls.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With schema description coverage at 0%, the description must compensate. It merely repeats the parameter name and its purpose ('URL to scrape meta tags from') without adding format, constraints, or examples, adding minimal value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool scrapes meta tags from any URL, listing examples like title, description, OG, and Twitter cards. It effectively communicates the core function but does not differentiate from sibling tools like 'get_og_metadata' or 'analyze_url'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The sibling list includes overlapping tools such as 'get_og_metadata', but the description offers no context for selection or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must fully disclose behavior. It mentions 'randomly' but lacks details on randomness type, determinism, or any side effects. Minimal beyond the action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short but includes a redundant line repeating the parameter. It could be more concise by integrating the parameter into one sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, and an output schema exists. However, the description omits any mention of the output (shuffled string) and does not explain randomness details. It is minimally adequate but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, meaning the description must compensate. It defines 'text' as 'Text to shuffle', adding some meaning, but the schema already implies the parameter is a string. The description adds little extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies the action (shuffle) and the resource (characters in a string). It is clear but does not distinguish from similar sibling tools like reverse_text or caesar_cipher.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., randomize vs. reverse). No context or exclusions provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description only mentions calculation without disclosing side effects, constraints, or output format. Agent must infer behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two-sentence description is concise and front-loaded with purpose, but could be more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a single parameter and output schema existence, description is minimally adequate but lacks usage context and clarity on return value.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%; description adds only a brief label for 'text' parameter, providing minimal value over the schema's title.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it calculates the Automated Readability Index for text, but does not differentiate from numerous sibling readability tools (e.g., analyze_readability, dale_chall_score).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives; lacks context for appropriate application.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavioral traits. It mentions parameters but does not describe edge cases, handling of existing line breaks, or behavior when break_long is false. The description adds minimal value beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the primary action, followed by parameter listings. It is efficient with no unnecessary content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and the existence of an output schema, the description provides a minimal but functional overview. However, it lacks examples, edge case handling, or details about the return value structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. However, it merely repeats parameter names and defaults already visible in the schema, adding no new meaning or context about parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Wrap long lines of code or text to a specified width,' which is a specific verb+resource. However, it does not differentiate from the sibling tool 'wrap_text,' which likely performs a similar function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'wrap_text.' The description only explains what the tool does, not the context or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It does not mention any behavioral traits, such as handling of very long texts, error conditions, or output format, beyond the basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and includes a parameter list. While efficient, the parameter list is redundant with the schema. Overall, it is appropriately sized for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has only one parameter and an output schema exists (explaining return values), the description is minimally adequate. However, it lacks context to differentiate from similar sibling tools like word_length_distribution, limiting completeness for an agent's decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate. It merely restates the parameter name and basic purpose ('Text to analyze sentence lengths'), adding little beyond the schema. A more descriptive explanation of the parameter's role would be beneficial.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description states the tool analyzes sentence length distribution and variability, which is a specific verb+resource. However, it does not distinguish itself from sibling tools like word_length_distribution or analyze_readability that may perform similar analysis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description lacks any when-to-use or when-not-to-use information, leaving the agent without context for selection among similar siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description fails to disclose any behavioral traits such as character replacement rules, case sensitivity, or handling of special characters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise but lacks necessary details. Minimal structure works for a trivial tool but misses opportunity to clarify behavior.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool is simple with one parameter and no nested objects. Adequate for basic understanding, but lacks explanation of return value (output schema exists but not referenced).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%; the description adds 'text — Text to slugify' which barely paraphrases the schema property name. No additional semantics like format, constraints, or examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description states 'Convert text to URL-friendly slug', which is a specific verb+resource combination. It clearly distinguishes from sibling tools like 'encrypt_text' or 'hash_text'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives or any prerequisites. The description only states what it does, not context of use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It states it 'analyzes' complexity, implying a read-only operation, but does not disclose any behavioral traits such as whether it requires network access, modifies data, or has rate limits. It also does not mention the output format, although an output schema exists separately.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one sentence plus parameter list) with no unnecessary words. However, it lacks structural elements like bullet points or examples that could improve clarity. It is efficient but not optimally structured for an agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, the description is not required to detail return values. However, given the abundance of sibling readability tools, the description is too sparse to help an agent choose this tool. It does not explain what 'multiple readability dimensions' entails or how the tool differs from similar ones.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds a brief explanation for the single parameter 'text': 'Text to analyze complexity of.' Given parameter count is 1 and schema coverage is 0%, this explanation provides basic meaning but no additional details (e.g., length limits, encoding). It is minimally adequate for a simple string input.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Analyze overall text complexity using multiple readability dimensions.' This identifies the verb (analyze) and resource (text complexity) and hints at a composite nature. However, it does not differentiate from many sibling readability tools (e.g., dale_chall_score, fry_readability) by naming specific dimensions, leaving some ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like analyze_readability or specific readability index tools. There is no mention of context, prerequisites, or when not to use it. The agent must infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description carries full burden. It fails to disclose definitions (e.g., what constitutes a word, sentence, paragraph), edge cases, or output structure. Vague behavioral traits reduce transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with minimal waste. Front-loaded with key outputs. However, parameter description is redundant and could be removed. Structure is adequate but not optimized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given one parameter and no annotations, the description covers basic purpose but lacks behavioral details needed for a multi-output tool. Output schema exists but description doesn't mention it. Sibling list is large, so tool needs clearer distinction.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has one parameter 'text' with 0% description coverage. Description adds only 'Text to count words in,' which redundantly restates the schema's title. No additional semantics, constraints, or examples provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool counts words, characters, sentences, paragraphs, and average word length. It uses specific verbs and resources, but does not differentiate from siblings like char_count or word_frequency, lacking explicit distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description only lists what it counts, omitting when-not-to-use or suggested contexts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits like needing two non-zero inputs to compute the third, but it only says 'leave 0 if unknown' without clarifying the inference logic. No discussion of error handling or edge cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short but includes the formula and a parameter list. However, it lacks structure; critical information about the calculation constraint is missing, and the parameter descriptions are inline in the text rather than using a formatted table.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given three parameters and no annotations, the description is incomplete. It does not specify how the tool determines which value to calculate when multiple are non-zero, nor does it describe the output schema. Users may be confused about expected usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explains each parameter (force in N, distance in m, work in J) and instructs to leave 0 if unknown, adding meaning beyond the schema which has 0% description coverage. However, it omits the crucial detail that exactly two must be non-zero for the calculation to work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates work, force, or distance using the formula W = Fd. It specifies the three possible outputs and the resource being computed, though it doesn't differentiate it from the related sibling tool 'force_calc'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The description does not mention the requirement to provide exactly two of the three parameters, nor does it indicate what happens with invalid inputs or multiple non-zero inputs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It states it is a cipher but omits important details like whether non-alphabetic characters are preserved, case sensitivity, or that it is symmetric (encoding=decoding). The behavior is implied but not explicitly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences and one parameter line, front-loading the core purpose. There is no superfluous text. However, it could be slightly more structured with explicit output info.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, with one parameter and an output schema. The description covers the basic purpose and parameter but does not explain return values or edge cases. Since an output schema exists, the lack of return description is somewhat mitigated, but behavior on non-letters is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has no descriptions for the 'text' parameter (0% coverage). The description adds a line explaining that 'text' is the input to encode/decode. This provides basic meaning but lacks specifics about valid characters, case handling, or formatting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it applies the Atbash cipher for encoding/decoding, specifying the substitution pattern (A↔Z, B↔Y). It uses a specific verb+resource combination. However, it does not differentiate from sibling cipher tools like caesar_cipher or vigenere_cipher, which is a minor gap.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It simply says 'Use this to encode or decode...' without mentioning conditions, prerequisites, or exclusions. Given many sibling cipher tools, this is insufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It states the action but omits key behavioral traits: does it modify the original? Is it safe? What is the return format? It doesn't disclose edge cases (e.g., empty string, unicode whitespace) or whether mode validation occurs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short, front-loaded with the main action, then a concise parameter list. No redundant sentences. Slightly less than 5 because it could rephrase to avoid a block of monolithic text; but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with 2 parameters and output schema present, the description covers basic usage but omits return value description (e.g., 'Returns cleaned string'). It does not mention that whitespace is collapsed to a single space in 'all' mode. Adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. It adds brief explanations for 'text' and 'mode' including default and options. This is baseline adequate but lacks detail (e.g., 'text' could specify expected encoding, 'mode' could list exact values). Not enough to elevate above 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool removes redundant whitespace (spaces, tabs, newlines) with a specific verb 'Remove' and resource 'whitespace'. It distinguishes from siblings like 'normalize_text' or 'remove_accents' by focusing on whitespace. Slightly less than 5 because 'all' mode could be more explicit (e.g., collapsing all to single space).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like 'normalize_text' or 'whitespace_analyze'. The description does not mention prerequisites, context, or exclusions, leaving the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavior. It only states the basic function without mentioning supported encodings, accuracy, constraints, or error handling (e.g., what happens if the text is empty or binary).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and to the point, but it omits important details. It is not overly verbose, but the lack of structure (e.g., no separate sections for usage, output, or limitations) makes it less effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that the tool has an output schema but no description explains what the detection result contains (e.g., encoding name, confidence score), the description is incomplete. For a simple tool, more context about return values is expected.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description should compensate. It only repeats the parameter name and a trivial description ('Text to detect encoding of') without adding constraints, examples, or format requirements.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Detect') and the resource ('character encoding of a text string'). It is a specific verb+resource combination that distinguishes it from sibling tools like detect_language or analyze_tone.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives, such as other detection tools or encoding-specific utilities. No context about prerequisites or edge cases is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, and the description does not disclose behavioral traits such as whether it's read-only, performance considerations, or error handling. The description is too sparse to convey key behavioral aspects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise with only two sentences and no unnecessary words. It is front-loaded with the main action, though it could be slightly more informative without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one parameter, output schema exists), the description is adequate to understand the core function, but lacks usage context and behavioral details, making it minimally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning for the single parameter by naming it 'text' and describing its purpose, which goes beyond the minimal schema (type string, required). However, with 0% schema coverage, more detail would be beneficial.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates the Fry readability graph estimate for text, which is a specific verb+resource. Among siblings like ari_score, dale_chall_score, etc., this uniquely identifies the Fry method.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It lacks explicit context or exclusions that would help distinguish its usage from other readability or text analysis tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It mentions detection and suggestion but omits output format, language support, or performance traits. The existence of an output schema is not leveraged to clarify behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with no wasted words. It includes a parameter listing in a clear format. It could be slightly more structured, but it's efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with an output schema, the description is adequate but not complete. It does not differentiate from many similar siblings, nor does it explain the output schema content (e.g., whether it returns a score, list, or suggestions).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds 'Text to analyze for passive voice' to the parameter, which is slightly informative but largely redundant with the tool's purpose. Given 0% schema description coverage, more detail (e.g., accepted formats) would be beneficial.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool detects passive voice and suggests active alternatives. However, among many text analysis siblings, it does not distinguish itself explicitly, e.g., from grammar or proofread tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternative text analysis tools like grammar, proofread, or other stylistic checkers. The description only states the function.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure, but it only repeats parameter names and descriptions from the schema. It does not mention return format, error handling (e.g., invalid units), or any side effects, providing minimal insight into the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (two sentences plus parameter list) and front-loaded with the purpose. It avoids unnecessary words. A slight improvement could be using bullet points for readability, but it remains efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and the existence of an output schema, the description is adequate but not complete. It lacks error handling context, unit constraints, and does not distinguish from similar siblings. For a 3-parameter tool with no enums in schema, more could be done to ensure confident invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds brief explanations for each parameter (value as 'Pressure value to convert', from_unit and to_unit as source/target), and the first sentence lists the supported units. However, with 0% schema description coverage, it does not fully compensate (e.g., missing case sensitivity, allowed unit values explicitly enumerated). The added value is moderate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Convert' and the resource 'pressure units' with a list of supported units (psi, bar, kPa, atm, mmHg, Pa). However, it does not differentiate from sibling tools like 'pressure_calc' or other unit converters, missing an opportunity to clarify unique use cases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., 'pressure_calc' or other converters). There are no prerequisites, constraints, or scenarios mentioned, leaving the agent to infer usage without clear direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only says 'compare financial impact' without disclosing output format, assumptions (e.g., tax benefits, maintenance costs), or any limitations. Minimal behavioral insight.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: a one-line purpose followed by parameter list. No redundancy. Could be slightly more structured (e.g., bullet points), but it's efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of rent vs buy comparison (many variables, assumptions), the description lacks details on output (what values are compared?), edge cases, or required financial context. An output schema exists but is not described. Incomplete for a financial tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It provides brief definitions for each parameter (e.g., 'Monthly rent amount'). However, these add little beyond the parameter titles; they are not detailed (e.g., no units, no constraints). Baseline is 3, and this is barely adequate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool compares renting vs buying a home. While it's specific and distinct from sibling tools like amortization_calc or mortgage_calculator, it does not explicitly differentiate itself, but the purpose is clear enough.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites (e.g., having mortgage rates) or scenarios like investment comparison. The description only states what it does, not when to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description does not disclose any behavioral traits such as handling of non-letter characters or environmental impact.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded, with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool, the description is adequate but could mention edge cases or behavior with special characters. Output schema likely covers return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description minimally explains the text parameter ('Text to swap case of'), adding little beyond the schema. With 0% schema coverage, more detail is expected.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool swaps case, which is a specific verb+resource. However, it does not distinguish from sibling tools like invert_case or alternating_case.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives, nor any prerequisites or restrictions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose any behavioral traits beyond the basic calculation. No annotations are present to fill this gap. Important details like rounding behavior, handling of decimal inputs, or limits on bill amount or split count are omitted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a single sentence followed by a parameter list. It is front-loaded and contains no fluff. While it could be more structured (e.g., using headings), it effectively communicates the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple calculator with 3 parameters and an output schema (though not shown), the description adequately covers the basic operation. However, it does not explain edge cases, negative inputs, or the format of the output. Given the complexity, a bit more detail would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning to the parameters beyond the schema's raw type definitions. It explains 'bill' as total bill amount, 'percent' as tip percentage with default, and 'split' as number of people. However, it lacks details like currency unit, precision, or validation, so it only partially compensates for the 0% schema description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates tip amount and splits the bill. It uses specific verb 'Calculate' and resources 'tip amount' and 'split bill'. However, it does not differentiate from sibling tools like discount_calculator or other financial calculators, but the uniqueness is evident from the name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of context, prerequisites, or when not to use it. The description only states what the tool does.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits like handling of invalid input, return format, or external dependencies. It mentions 'check digit' but doesn't specify if the tool provides detailed error messages or simply a boolean. This is insufficient for a validation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with purpose, but the 'Parameters' section is redundant for a single parameter and could be removed. It is adequate but not optimally concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description need not detail return values. However, it lacks context on error handling and edge cases. For a validation tool, more completeness would be expected, even with an output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description lists the parameter 'iban' with a brief explanation 'IBAN number to validate.' However, with 0% schema description coverage, it adds minimal extra meaning. No format, length, or examples are provided, leaving the agent to guess the expected input type.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Validate IBAN format and check digit for international bank accounts.' This provides a specific verb ('validate') and resource ('IBAN format and check digit'), distinguishing it from sibling validation tools like validate_json or validate_vat.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, limitations, or scenarios where validation might fail. The description only explains what it does, not when to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fails to disclose important behavioral traits such as return format, error handling for invalid units, or whether the tool accepts abbreviations. The brief parameter descriptions do not cover these aspects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences and a parameter list, front-loading the core purpose. It is well-structured but could be slightly more compact.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description omits information about what the tool returns and does not explain error behavior or the full range of supported units. The minimal details are insufficient for a tool with three required parameters and no annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Given 0% schema coverage, the description adds basic meaning by naming the parameters ('Volume value', 'Source unit', 'Target unit'), but does not specify acceptable unit formats or provide a complete list of supported units beyond examples. Additional detail would be needed for full compensation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Convert between volume units' and lists specific units (liters, gallons, etc.), making the tool's purpose unambiguous. However, it does not differentiate from sibling tools like 'convert_units' that might also handle volume conversions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as the general 'convert_units' or other conversion tools. The description only states the function without context about appropriate usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description only mentions 'with histogram data' without detailing output structure or behavior. No mention of idempotency, side effects, or safety.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: one sentence for purpose and a one-line parameter list. No wasted words, but could benefit from more structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With one parameter and an existing output schema, the description is somewhat complete. However, it lacks details on how the histogram is computed or returned, which would aid agent understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'text' is described as 'Text to analyze word length distribution.' This adds minimal meaning beyond the schema (which has no parameter description). With 0% schema coverage, the description partially compensates but is still brief.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool's purpose clearly: 'Analyze word length distribution with histogram data.' This distinguishes it from siblings like word_frequency or word_count, but could be more specific about the scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives among the many sibling tools. No prerequisites or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It indicates a pure calculation with no side effects, but does not disclose any edge cases, constraints on input values (e.g., positive numbers), or behavior on invalid inputs. Score 3 as it is minimally adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, containing only a sentence and a list of parameters. No unnecessary words. However, it could be better structured by separating the purpose from parameter definitions, but overall it is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return value explanation is not needed. The tool is simple, but the description lacks context about what constitutes valid input (e.g., positive numbers for periods) and the formula used (CAGR = (final/initial)^(1/periods)-1). Score 3 as it is minimally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It only repeats parameter names with vague one-word descriptions ('Starting value', 'Ending value', 'Number of periods'), adding little beyond the schema. It fails to specify units, allowed ranges, or that periods should be complete years. Score 2.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates CAGR with three parameters (initial_value, final_value, periods). The verb 'calculate' and resource 'Compound Annual Growth Rate' are specific. However, it does not differentiate from sibling tools, but given the unique function, it is acceptably clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description merely lists parameters without context on scenarios, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It only states the basic function, lacking details on behavior such as handling multiple abbreviations, language support, or idempotency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (two sentences), but the brevity sacrifices important details. It is concise but not optimally informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given an output schema (not shown), return values need not be explained, but the description lacks details on usage scenarios, limitations, and how it integrates with sibling text tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must add value. It describes the 'text' parameter as 'containing abbreviations to expand', which slightly enriches the schema's minimal 'Text' title, but lacks format, encoding, or examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the action (expand) and resource (abbreviations, acronyms, shorthand into full forms), making it clear what the tool does and distinguishing it from siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'abbreviate' or other text manipulation tools. The description does not mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It only states 'Calculate retirement savings growth' without disclosing important behavioral traits such as compounding frequency, whether inflation is considered, or that the result is a future value projection. The tool's behavior is implied but not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with one sentence for purpose followed by a parameter list. Each parameter gets a brief explanation, but the list largely mirrors the schema property names, making it somewhat redundant. Overall efficient but could be more integrated.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema likely present, the description should explain what the tool returns beyond 'projected nest egg'. It does not mention whether output includes yearly breakdown, graph, or additional metrics. This lack of detail makes it less complete for an agent to understand the tool's full behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context beyond the schema by specifying units (e.g., 'in years') and default values (e.g., monthly_contribution defaults to 0, rate to 7.0). This helps the agent interpret parameters correctly. However, it does not clarify constraints like valid age ranges or allowed rate limits.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Calculate' and the resource 'retirement savings growth and projected nest egg', giving a precise purpose. However, it does not differentiate from similar sibling tools like 'savings_goal_calc' or 'investment_calculator', missing an opportunity to clarify its unique scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like compound_interest or savings_goal_calc. It lacks context on prerequisites, limitations, or the type of retirement calculation performed (e.g., assumes constant rate, monthly compounding).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description claims bidirectional conversion but only supports one direction. No mention of output format or side effects, which is expected for a computation tool but still lacks precision.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and includes a clear parameter list. It is front-loaded with the main action. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description does not clarify whether the result is a string or number. The 'from' direction is unsupported by parameters, leaving gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, the description adds meaning by naming parameters and explaining their roles (value and precision). However, it doesn't specify constraints or edge cases.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it converts a number to and from scientific notation, but the parameters only support converting to scientific notation, not from. This slight inconsistency reduces clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'convert_number_base' or 'significant_figures'. No context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description lacks details about the specific set of special characters that are escaped/unescaped, potential side effects, or limitations. With no annotations, the description should disclose more behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with a clear statement of purpose. The parameter list is well-structured, though it could be more integrated into the main description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is too brief for a string escape tool. It does not specify which special characters are handled (e.g., backslashes, quotes) or the output format. Although an output schema exists, the description should provide more context for safe usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explains the purpose of each parameter ('text' is the string to process, 'mode' specifies escape or unescape), adding meaning beyond the schema's types and defaults. This is important given 0% schema description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool escapes or unescapes special characters in strings. The verb 'escape' is specific and indicates the operation. However, it does not differentiate from sibling tools like 'html_escape' or 'url_encode_decode' which might have similar purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidelines are provided about when to use this tool versus alternatives. There is no mention of context, prerequisites, or scenarios where this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Mentions sorting by count, but lacks details on case sensitivity, punctuation handling, or stop words. Without annotations, the description carries the burden, but it's only partially informative.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise, front-loaded with the main action. Could add more detail without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists, so return values are covered. However, no annotation coverage and missing behavioral details leave gaps for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description adds no meaningful detail beyond the schema field title, failing to compensate for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it analyzes word frequency distribution sorted by count, which distinguishes it from sibling tools like word_count or char_count. However, it doesn't specify the output format, leaving some ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Given many text analysis siblings, explicit context would improve selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It only states the basic conversion without addressing edge cases (e.g., non-alphabetic characters, Unicode) or potential side effects. The description is too minimal to be fully transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded with the purpose. Every word earns its place; no unnecessary information. It is structured clearly with a heading and a parameter list.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple transformation with an output schema, the description is nearly sufficient, but it lacks details about return format and behavior for special inputs. Given the existence of similar sibling tools, more context (e.g., example inputs/outputs) would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description adds value by explaining the 'text' parameter. However, the explanation is minimal ('Text to convert') and does not specify expected format, length limits, or examples, which would be helpful for precise invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Convert text to alternating case' and provides an example pattern. It effectively communicates the core transformation, but does not explicitly differentiate from sibling case conversion tools like 'convert_case' or 'invert_case'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., 'convert_case' for general case conversion). There is no mention of prerequisites or context, leaving the agent to infer usage solely from the tool name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must fully disclose behavior. It only states the output is a 'full amortization schedule' but does not describe any side effects, constraints, or assumptions (e.g., rounding, error handling). The description is insufficient for a read-only calculation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and uses a clear parameter listing. However, the structure could be improved by using a more standard format (e.g., markdown) or integrating example values inline.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and presence of an output schema, the description is mostly adequate but lacks contextual hints about typical use cases or differentiation from similar tools like mortgage_calculator or auto_loan_calc.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds significant value beyond the schema, which has no param descriptions. It clarifies that 'rate' is an annual interest rate with an example, and 'term_months' is in months. This helps the agent understand expected formats, though it could be more precise about principal currency.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates full amortization schedules with monthly breakdowns, making the purpose easy to understand. However, it does not distinguish itself from similar sibling tools like loan_calculator or mortgage_calculator, missing a chance to differentiate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. With many sibling tools for loan calculations, the lack of usage context hinders agent decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It does not disclose that the tool is read-only, idempotent, or any side effects. It only lists parameters and defaults, which is minimal beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: one sentence followed by a parameter list. Each parameter gets a single line, making it easy to scan. It is appropriately front-loaded, though the parameter list could be formatted more clearly (e.g., bullet points).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema, so return value details are not required. However, the description lacks context about the calculation method (e.g., amortization formula) or any assumptions. It is minimally complete for a simple calculator.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description adds value by providing brief explanations for each parameter (car_price, down_payment, rate, term_months, trade_in) and noting defaults. This compensates for the missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states it calculates auto loan monthly payments and total cost, which is clear and specific to auto loans. However, it does not explicitly differentiate from sibling tools like 'loan_calculator' or 'mortgage_calculator', but the name itself provides sufficient distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description only states what it does, without mentioning appropriate contexts or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It mentions 'across multiple readability formulas' but does not disclose error handling, edge cases (e.g., empty text), or range of output. With no annotations, more behavioral detail is needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with no wasted words. It front-loads the purpose and immediately lists the parameter. For a simple tool, this is appropriate.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and presence of an output schema (not shown), the description could be minimally complete. However, it lacks any mention of return value or behavior. It is adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so description must add meaning. It explains 'text' as the input for calculation, which clarifies its role. However, it does not specify constraints like minimum length or encoding, so it adds limited value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates average grade level across multiple readability formulas, with a specific verb and resource. It distinguishes from sibling tools that calculate single readability scores (e.g., ari_score, fry_readability). However, it does not specify which formulas are included.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus other readability tools. The description does not mention that it is an aggregate or provide context for selection among siblings like analyze_readability, gunning_fog_score, etc.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does not disclose whether the operation is read-only, has side effects, requires permissions, or how errors are handled. The description only lists parameters and calculations, leaving behavioral traits underspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and to the point, using only a few lines. It could be better structured with bullet points or more formal formatting, but it is not verbose. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is an output schema (not shown) and the tool is a simple calculation, the description is adequate. However, it omits details like payment frequency (annual vs semi-annual) or assumptions about yield calculation, which could affect interpretation. It is functional but incomplete for more complex financial contexts.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates by adding one-line explanations for each parameter (e.g., 'face_value — Bond face/par value.'). This adds meaning beyond the schema's type and title, helping the agent understand parameter roles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates bond yield to maturity and current yield, using a specific verb ('calculate') and resource ('bond yield'). However, it does not differentiate from sibling tools like amortization_calc or compound_interest, which are also financial calculations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It lacks prerequisites, context for when it is appropriate, or exclusions. The description simply states what it does without contextual usage advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It only states the tool checks bracket matching, but does not disclose whether it is read-only, how errors are handled, or any performance implications. This is insufficient for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, using two sentences to state the purpose and parameter. It is front-loaded with the main purpose and clearly structured with a 'Parameters:' line.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (one parameter) and the presence of an output schema, the description is minimally complete. However, it lacks detail on what the output represents (e.g., boolean, list of mismatches), which could be ambiguous.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, meaning the parameter 'code' has no description in the schema. The description adds semantic meaning by stating it should be source code, which helps the agent understand the input beyond the parameter name alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks bracket/parenthesis/brace matching in source code, which distinguishes it from sibling tools like anagram_check or palindrome_check. The verb 'check' and resource are specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, no exclusions, and no prerequisites mentioned. The description lacks usage context entirely.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits beyond the basic function. It only states the conversion purpose, omitting details about how the transformation works, potential side effects, or limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, consisting of two succinct sentences. It efficiently conveys the core purpose without unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple text transformation tool, the description provides basic completeness. However, it does not mention the output format or return value, which is relevant since an output schema exists. More context about the transformation's nature (e.g., AI-based) would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning to the single parameter 'text' by explaining its role ('Text to convert to casual tone'), which goes beyond the schema's bare title. Given only one parameter, this is adequate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts formal/stiff text to casual tone, using a specific verb and resource. However, it does not explicitly distinguish from similar siblings like 'formalize' or 'simplify_text'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It simply describes the action without context or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It ambiguously states 'including/excluding spaces and non-printable chars' without specifying which behavior is default or how to control it. No disclosure of how the tool handles edge cases or what the output format is.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise (two lines) and front-loaded with the core functionality. The parameter list is structured. However, the ambiguous phrase about including/excluding could be clarified without adding much length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, the description does not need to explain return values. However, the lack of clarity on the include/exclude behavior and no mention of error handling or edge cases leaves gaps. Given the tool's simplicity, it is minimally adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description adds value by explaining the 'text' parameter as 'Text to analyze character count.' This clarifies the parameter's purpose beyond the schema's simple type declaration. For a single parameter, this is sufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool counts characters in provided text. Verb 'Count' and resource 'characters' are specific. However, it does not differentiate from sibling tools like word_count or line_count, and the mention of including/excluding spaces and non-printable chars is misleading because no such parameters exist.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Does not mention preferred contexts or exclusions. Sibling tools perform similar tasks, but no comparative information is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It only states the action but does not disclose any side effects, permissions, or limitations (e.g., whether it fetches the page, network requirements).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded, but the parameter description slightly repeats the purpose. It is efficient overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, output schema exists), the description covers the basics. It misses behavioral details but is otherwise adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning to the 'url' parameter beyond the schema's type definition, explaining it is the URL to check. However, with only one parameter and 0% schema coverage, it partially compensates.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks page size and load time, and the name itself differentiates from other URL tools. However, it does not explicitly distinguish itself from siblings like 'analyze_url'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'url_parse' or 'analyze_url'. The description only states the function without context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only says 'calculate' without disclosing safety (e.g., read-only, no side effects). No annotations exist to compensate, leaving behavioral traits unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise, front-loaded with the main purpose. Could omit the parameter list if schema is sufficient, but it's not redundant given coverage is 0%.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return values are covered. However, missing constraints (e.g., supported languages list) and no example usage, leaving some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must add meaning. It only lists parameter names and a default, missing details like code length limits, language format, or examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates cyclomatic complexity and other code metrics, with a specific verb and resource. This distinguishes it from sibling tools like code_beautify or code_stats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as code_stats or text_complexity. No when-not-to-use or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as whether it is a pure computation, requires network access, or has any side effects. It does not mention the nature of the output (e.g., a label or range). The minimal description fails to inform the agent about behavior beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (two sentences) without redundancy. It front-loads the purpose and then lists the parameter. While concise, it could benefit from a structured format (e.g., bullet list) for the parameter, but the current form is efficient for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has only one parameter, the description is adequate for a simple color analysis tool. However, it lacks additional context such as valid hex range, handling of invalid inputs, or the scale of temperature. The output schema likely covers return values, so that gap is acceptable, but the description could still be slightly more informative.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful format guidance for the single parameter 'hex_color' ('Hex color without # (e.g. '3498db')'), which is not present in the input schema (0% coverage). This helps the agent construct valid input. The example clarifies the expected format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool estimates color temperature (warm/cool) of a hex color, with a specific verb 'Estimate' and resource 'hex color'. It distinguishes from siblings like color_conversion or color_harmony tools. However, it could be more precise about the output format (e.g., categorical label vs numeric value).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., color_harmony, convert_color). The description does not provide context or exclusions, leaving the agent to infer from the tool name alone. With many color-related siblings, explicit usage tips would be helpful.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the full burden of behavioral disclosure. It only states the basic comparison function but omits critical details like case sensitivity, hash format expectations, or comparison method (e.g., string vs binary). This leaves the agent guessing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with two sentences and a parameter list. It is front-loaded with the main action. A minor point could be made for more efficiency, but overall it is appropriately sized for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity but absence of annotations, the description should provide more complete context. It lacks details about output schema, edge cases, and comparison specifics, making it insufficient for reliable agent usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds basic semantics by describing hash1 as 'First hash value' and hash2 as 'Second hash value to compare against,' which provides some context beyond the schema titles. However, it lacks specifics like accepted hash types or formats.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('compare') and the resource ('two hash values'), and specifies the result ('return whether they match'). It distinguishes itself from siblings like 'compare_items' by being hash-specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is provided. The description does not mention when to use this tool versus other comparison or hash-related tools, nor does it offer any context or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the burden. It implies a read-only calculation with 'Calculate', but does not explicitly state non-destructive behavior or disclose any side effects. Adequate but not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and lists parameters in a structured format. No superfluous information, but it could benefit from a clearer separation between description and parameter list.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of compound interest calculations, the description lacks output details (e.g., result format) and does not address edge cases. This leaves the agent with incomplete expectations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds meanings for all parameters (e.g., rate format, contributions default). However, 'compound' is vague ('Compound frequency') without listing allowed values, reducing clarity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates compound interest growth with optional contributions, using a specific verb and resource. However, it does not differentiate from sibling tools like simple_interest_calc or amortization_calc, which could lead to ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description does not mention exclusions or prerequisites, leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Lacks disclosure of assumptions (e.g., compounding frequency, monthly payment priority when both min_payment and monthly are given), no mention of read-only nature (though inferred), and no limits or side effects described.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Concise with a single sentence of purpose and a clear parameter list, though the structure is minimal and could be improved with grouping or formatting.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, the description still fails to explain the calculation logic (timeline unit, interest savings method), making it incomplete for an agent to fully understand the tool's behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Explains each parameter with example for rate, but does not clarify the interaction between optional parameters (min_payment and monthly) or their defaults, leaving ambiguity for the agent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it calculates 'credit card payoff timeline with interest savings,' which is specific and distinguishes from generic loan calculators among siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like loan_calculator or amortization_calc, nor any prerequisites or context for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description does not disclose read-only nature, error handling, or return format. Basic functionality is stated but not enough for full transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, front-loaded with action and resource. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Simple tool, output schema exists but not shown. Missing details on return value (filtered array) and error behavior. Adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has no parameter descriptions (0% coverage). Description adds meaning: 'data' is a JSON array, 'condition' is a filter expression with example. However, condition syntax is not fully specified.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it filters array items using a condition expression, with an example. Differentiates from siblings like 'sort_data' and 'deduplicate_data'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use vs alternatives, when not to use, or prerequisites. Could mention that it expects a JSON array string and condition expression.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does not mention any limitations, output characteristics, or potential side effects beyond the basic conversion, leaving the agent without important context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short and front-loaded with the core purpose. However, the 'Parameters' section is somewhat redundant given the input schema, though it does not harm conciseness significantly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists, the description does not need to explain return values. However, it lacks contextual differentiation from many sibling text manipulation tools, which would improve completeness for agent decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although schema description coverage is 0%, the description only restates the parameter's purpose ('Text to convert to formal tone') without adding new information like expected length, format, or examples. This adds minimal value beyond the parameter name itself.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Convert' and the resource 'casual or informal text to formal tone', making the tool's purpose obvious. It distinguishes from sibling tools like 'casualize', which does the opposite, and other text manipulation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'paraphrase', 'grammar', or 'simplify_text'. The context of use is entirely implied without explicit exclusions or suggestions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the full burden. It fails to disclose the formula used (e.g., Karvonen method), any limitations, or whether the calculation is safe for all users. The behavioral traits of the tool are opaque.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with a clear main sentence and a brief parameter list. It front-loads the purpose. However, there is room for a more structured format (e.g., separate sections for use cases).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists, the description need not detail return values, but it could clarify what 'heart rate zones' means (e.g., 5 intensity zones). Currently, the agent knows only that zones are calculated, not their structure or application.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage for parameters, so the tool description provides essential meaning: 'age — Age in years' and 'resting_hr — Resting heart rate in bpm (default: 60).' This adds value beyond the schema structure.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Calculate target heart rate zones for exercise,' which clearly indicates the tool's function with a specific verb and resource. However, it does not differentiate from sibling tools like bmr_calc or vo2max_calc, which have overlapping health/fitness contexts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, such as when to choose heart rate zones over other calculations. The description lacks context about prerequisites or expected input ranges.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It only states what is counted (total lines, non-empty, blank) but does not explain how lines are defined (e.g., handling of trailing newlines, whitespace-only lines). For a simple tool, some behavioral context is missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise—two sentences without extraneous information. It front-loads the purpose and includes a parameter line. However, it omits any structural elements like return value description, which might be warranted given the lack of annotations. It earns points for efficiency but loses some for missing non-redundant detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no annotations, output schema exists), the description provides a minimally adequate overview. It covers the basic function and parameter. However, it does not explain the output format or handle edge cases, leaving some gaps that an agent might encounter. An output schema is present, partially mitigating this.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, meaning the description must compensate for undocumented parameters. The description includes 'text — Text to count lines in,' which adds a minimal semantic hint but does not elaborate on expected format, constraints, or examples. The schema already defines 'text' as a required string, so the added value is marginal.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Count total lines, non-empty lines, and blank lines in text.' This specifies the verb 'count' and the resource 'lines in text,' distinguishing it from siblings like word_count or char_count. The purpose is unambiguous and immediately conveys what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus other text analysis siblings (e.g., paragraph_count, sentence_length_analyze). There is no explicit context, prerequisites, or mention of when not to use it. The usage is implied but not supported with comparative or alternative recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations present, so description carries full burden. Only states it parses and validates, but lacks details on side effects, error behavior, validation outcomes, or auth requirements. Output schema exists but not referenced.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences with front-loaded purpose. Parameter listed separately. No unnecessary words. Could be more efficient if parameter detail moved to schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having output schema, description lacks detail on validation outcomes, supported country codes, and input format variations. Incomplete for a robust parsing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 0% description coverage. Description adds example format '+441234567890', clarifying expected input. However, does not specify allowed variations (spaces, dashes) or error handling for invalid numbers.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'parse and validate' and resource 'international phone numbers'. Specifies extracted fields (country code, national number). However, phrase 'Supports major country codes' is vague and could be more precise.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides basic guidance: 'Use this to extract country code, national number, and validate formatting.' Does not mention when to avoid or compare to alternative tools. No prerequisites stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits; it only states the basic function, omitting edge cases (e.g., empty string, Unicode) and no mention of side effects or return details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief but includes a redundant parameter list; still efficient overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a simple tool with output schema present, the description is mostly adequate but lacks behavioral notes for edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, yet the description merely repeats the schema ('Text to reverse') without adding constraints like length, encoding, or format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('reverse') and resource ('characters in a string'), clearly distinguishing from sibling text tools like 'alternating_case' or 'caesar_cipher'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, nor any prerequisites or exclusion criteria provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It does not mention validation, error handling, valid input range (e.g., Roman numerals up to 3999), or output format beyond what the output schema might cover.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and direct, with a clear structure separating overview and parameter details. No unnecessary words or sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter tool with an output schema, the description is mostly adequate. However, it lacks details on valid input ranges and error behavior, which are important for an AI agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate. The 'value' parameter explanation is tautological ('Value to convert') and the 'mode' parameter adds minimal context. Expected input formats are not clarified.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts between Roman numerals and Arabic numbers, with a specific verb and resource. It distinguishes itself from sibling tools as no other tool explicitly handles Roman numerals.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives or any prerequisites. It only explains the two modes without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry full burden. It only says 'with compounding' but does not disclose compounding frequency (monthly?), rounding behavior, assumption about contributions being made at the start/end of period, or any error handling. For a financial calculator, these details are critical.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise: one sentence for purpose followed by a tidy parameter list. It is front-loaded with the main action. However, the parameter descriptions are separate from the main text, which could be more integrated.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema (not shown), the description lacks context about what the output represents (total value, profits, etc.) and how compounding is applied (monthly? annual?). For a SIP calculator, typical output includes total investment, maturity amount, and returns. This gap makes the tool harder to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. It provides clear but basic descriptions for each parameter: monthly_investment (amount), rate (annual return, example given), years (period). This adds meaning beyond schema types/titles but lacks details like permissible ranges or format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates SIP returns with compounding, which is a specific verb+resource. It distinguishes from generic financial calculators by focusing on Systematic Investment Plan, but does not explicitly differentiate from similar tools like compound_interest or investment_calculator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when calculating SIP returns, but provides no guidance on when to use this tool instead of alternatives like compound_interest or emi_calc. No when-not or context switching advice is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool calculates a grade but does not disclose any behavioral traits such as idempotency, safety, rate limits, or side effects. Given the simple calculation, it is likely safe, but the description fails to confirm this.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting of a single sentence and a parameter list. Every word is necessary, with no fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema, so the description does not need to explain return values. However, given the sibling tool set includes many readability metrics, the description lacks context about what SMOG index is or when to use it, making it minimally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema coverage is 0%, so the description must compensate. The description includes a Parameters section explaining that 'text' is the text to calculate the SMOG index for, adding meaning beyond the schema's bare type. However, it is minimal and does not provide format or examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates the SMOG readability grade, which is a specific verb and resource. It also lists the parameter. However, it does not differentiate from other readability tools like gunning_fog_score or fry_readability, so it loses a point for lack of sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus other readability metrics. There is no mention of scenarios, alternatives, or prerequisites, leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states the action (count and list frequencies) without disclosing behavioral traits like case sensitivity, punctuation handling, or output format. Behavioral details are minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief with two sentences plus a parameter line. It is front-loaded and efficient, though the parameter list is somewhat redundant with the schema. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with an output schema, the description is adequate but incomplete. It does not address edge cases (empty text), define 'unique words' (case sensitivity, punctuation), or specify the return format, relying on the output schema for details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage (no property descriptions), so the description adds meaning by explaining the 'text' parameter as 'Text to extract unique words from'. This provides context beyond the schema's type definition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool counts and lists unique words with frequencies, using a specific verb and resource. It distinguishes itself from similar tools like 'word_frequency' or 'repeated_words' by focusing on unique words, though it could be more explicit about the contrast.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus siblings. The description does not mention when not to use it or suggest alternatives, leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It states what is analyzed but does not describe the output format, whether it returns counts, positions, or a summary. The behavioral traits beyond 'analyze whitespace' are opaque.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exceptionally concise, using two short sentences. Every word serves a purpose. It is front-loaded with the core action and lists parameter descriptions effectively.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple analysis tool, the description covers the input and purpose. However, it lacks any mention of the output, which is relevant since an output schema exists. An agent would benefit from knowing what kind of analysis result to expect (e.g., counts, statistics). The description is minimally complete but leaves a gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds a brief explanation for the single 'text' parameter ('Text to analyze whitespace in'), which provides minimal context beyond the schema's name and type. With 0% schema description coverage, the description partially compensates but is not rich. For a single string parameter, this is adequate but not exemplary.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool analyzes whitespace usage, listing specific categories (spaces, tabs, newlines, trailing spaces). It is a specific verb+resource combination. However, it does not explicitly distinguish from the sibling tool 'clean_whitespace', which likely modifies whitespace instead of just analyzing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, context, or when not to use it. The description is purely functional without any usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full burden. It only states the basic conversion without disclosing behaviors like character encoding handling, error on invalid input, or output format. Minimal transparency beyond the primary action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: two sentences packed with necessary information. No wasted words or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (2 params, simple conversion), the description is minimally adequate. However, it omits output format (e.g., binary string with spaces) and error handling. An output schema exists but not described.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds meaning by explaining 'text' as input string and 'mode' with 'encode' or 'decode' options. This adds value beyond the schema titles, though does not specify default behavior or allowed mode values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts between text and binary using a specific verb ('Convert') and resource ('text to binary or binary to text'). It distinguishes from siblings like morse_code or caesar_cipher, but does not explicitly differentiate from similar encoding tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. It lacks explicit 'use when' or 'do not use' statements. The context is implied but not clarified.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full behavioral disclosure burden. It fails to mention critical behavioral traits such as case preservation, handling of non-alphabetic characters, or shift direction (positive/negative). This omission could mislead the agent about tool behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences plus a parameter list. The purpose is front-loaded, and every sentence serves a purpose. No extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a cipher with behavioral nuances) and lack of annotations, the description is incomplete. It does not explain edge cases (e.g., non-letters, negative shift) or the output format, even though an output schema exists. The agent lacks sufficient context to use the tool reliably.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal meaning beyond the schema: it restates parameter names and default values, and clarifies that mode accepts 'encrypt' or 'decrypt'. This adds value since the schema lacks an enum for mode, but overall it mostly duplicates schema information. Schema coverage is 0%, and the description compensates slightly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Encrypt or decrypt text using the Caesar cipher.' It specifies the action (encrypt/decrypt) and the resource (text), and uniquely identifies it from sibling cipher tools (e.g., atbash_cipher, vigenere_cipher) by explicitly naming the Caesar cipher.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives (e.g., other ciphers). It does not mention prerequisites, limitations, or context scenarios. The lack of explicit usage context reduces its helpfulness for an AI agent deciding between sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as side effects, rate limits, or permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences plus a parameter list; no wasted words. Front-loaded with purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and an output schema, the description covers the essentials. Could be more detailed about output format, but adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description briefly explains the 'text' parameter ('Text to analyze capitalization in'), adding meaning beyond the schema's type and title. However, the explanation is minimal.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool analyzes capitalization usage (uppercase, lowercase, mixed, title case), making the purpose evident. However, it does not differentiate from sibling text analysis tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Lacks context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits like handling of redirects, timeouts, authentication, or rate limits. It only states that HTTP status codes are reported, leaving significant behavioral assumptions unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two short sentences, no redundant words, and a clear structure. Every element adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool involves network requests and link checking, the description lacks important context such as the need for public accessibility, potential for large response, or handling of broken links. The presence of an output schema reduces the need to describe return values, but operational completeness is lacking.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It adds the meaning of the 'url' parameter as 'URL to check links on', which is helpful but minimal. A more detailed explanation of expected URL format or constraints would improve this score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('check all links') and the resource ('a page'), and specifies the output ('report their HTTP status codes'). It distinguishes itself from sibling tools like 'check_password_strength' or 'check_ssl_certificate' which address different verification tasks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool (e.g., for checking internal vs. external links, for pages with many links) or when to avoid it. No alternatives are mentioned despite a large list of sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description indicates a read-only calculation but provides no details beyond 'based on readability metrics'. Since no annotations exist, the description carries full burden but lacks specifics like output format or computational complexity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, with a single sentence for purpose and one parameter line. It is front-loaded and wastes no words, but could be structured with clearer separation of purpose and parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (inferred), the description is minimally sufficient for a simple calculation tool. However, it lacks examples, use cases, and differentiation from many sibling readability tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description includes a brief explanation of the single parameter 'text'. With 0% schema description coverage, this minimal addition compensates partially but could be more informative about expected input length or encoding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (Calculate) and resource (clarity score for text) and mentions it is based on readability metrics. However, it does not differentiate among sibling tools like analyze_readability or specific readability formulas.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as analyze_readability, dale_chall_score, or fry_readability. No context about prerequisites or when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, and the description does not disclose any behavioral details beyond the basic action. For example, it does not mention which comment styles are removed (e.g., single-line vs multi-line), or any side effects like formatting changes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences and a parameter list, making it easy to scan. It avoids redundancy but could benefit from a more structured format.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description need not explain return values. However, it lacks complete behavioral context, such as whether it handles nested comments or preserves code formatting. It is minimally adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds brief explanations for both parameters (e.g., 'Source code with comments to remove' and 'Programming language (default: python)'), which are not present in the schema. However, the explanations are minimal and could be more detailed, especially for the language parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('strip comments') and the resource ('source code'). It is specific and distinct from sibling tools like code_beautify or code_minify_js, which handle other transformations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. Given many sibling tools related to code processing, the agent lacks context to decide the correct tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does not disclose whether the tool is generative, requires authentication, or any side effects. The behavior is implied ('create') but not explicitly detailed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: two short sentences covering purpose and parameter. No wasted words; front-loaded with the action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with an output schema, the description is adequate but minimal. It doesn't explain that the output is a generated analogy, which could be inferred but not stated.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description compensates for the 0% schema description coverage by defining the parameter 'text' as 'Concept to create an analogy for', adding meaningful context that the schema lacks.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool creates an analogy comparing a concept to something familiar. However, it does not differentiate from the sibling tool 'create_metaphor', which serves a similar purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, nor any context about prerequisites or exclusions. The description is entirely missing usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose any behavioral traits (e.g., how creative, any limitations, output format). The description is too minimal to provide transparency beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise with two sentences, front-loaded with the main purpose. No wasted words, but could be slightly more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema, it does not need to explain return values. However, for a creative generation tool, more context (e.g., style, length, examples) would improve completeness. Current description is adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds a brief explanation for the only parameter ('text — Concept to create a metaphor for'), which is slightly more than the schema's title. However, schema description coverage is 0%, so the description does not fully compensate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool generates creative metaphors for any concept. Uses a specific verb ('generate') and resource ('creative metaphors'), and is distinct from siblings like 'create_analogy'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., create_analogy). No explicit when-not contexts or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description must disclose behavioral traits. It says 'safely' but does not explain what that entails (e.g., sandboxing, supported operations, limits). No mention of error handling, precision, or whether advanced functions are available.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences plus a parameter list. It is front-loaded with the main purpose. No superfluous words; every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While an output schema exists, the description still needs to cover essential context for safe use. It lacks information about error behavior (e.g., division by zero), input validation, and the scope of expressions accepted. This is inadequate for a potentially risky tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It provides a parameter 'expression' with an example, which adds meaning beyond the schema's type-only definition. However, it omits details like supported operators, constants, or functions, leaving gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'Evaluate a mathematical expression' and provides an example. It distinguishes from siblings like 'quadratic_solver' by being general-purpose. The verb+resource is specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. With many sibling tools for specific calculations (e.g., 'quadratic_solver', 'calculate_bmi'), the description does not explain the criteria for choosing this general evaluator. Implied usage is vague.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses output is a JSON array but omits important behaviors: handling of malformed HTML, multiple tables, table structure, or error cases. Minimal for a data extraction tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise with two sentences and a parameter list. Front-loaded with purpose, but lacks additional details that could be included without bloat.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With a single parameter and no annotations, but with output schema, the description adequately states 'structured JSON array' but doesn't detail the schema structure (e.g., rows/columns, handling of multiple tables). Moderately complete for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. It adds a brief hint 'HTML content containing tables' but doesn't specify format, required structure, or behavior for no tables. Baseline adjusted due to schema gap but parameter is simple.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it extracts HTML tables into a structured JSON array, using specific verb and resource. It distinguishes itself from all sibling tools, none of which perform HTML table extraction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives, no mention of prerequisites or edge cases (e.g., multiple tables, malformed HTML). The description only lists the parameter without usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of transparency. It states the basic operation but does not disclose edge cases (e.g., empty text), output format, or behavior with punctuation. It is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (two sentences plus parameter list) with no wasted words. However, it omits useful usage guidance, making it overly minimal for a tool with no annotations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is somewhat complete but lacks details about the output type or behavior. It is acceptable but could be improved.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, meaning the description adds no meaning beyond the schema. It restates parameter names and defaults without providing additional context like expected input format or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Find' and resource 'words longer than a specified length', which distinguishes it from sibling tools like find_short_words and word_count. The purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as find_short_words for shorter words. No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description does not disclose whether the tool is read-only, requires authentication, or any side effects. Output structure (has output schema) is not described.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: one-line purpose followed by bulleted parameter list. No unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Description covers basic inputs but lacks explanation of the 'fitness age' concept, input constraints (e.g., valid ranges), or what the output represents. Output schema exists but its content is not summarized.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description provides clear explanations for each parameter including units (bpm, years, sessions/week) and default value, adding significant value over the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the purpose ('Estimate fitness age') and lists key inputs. However, it does not explicitly differentiate from similar sibling tools like 'metabolic_age_calc' or 'age_appropriate'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, no prerequisites or exclusion criteria mentioned. Only parameter descriptions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fails to disclose behavioral traits such as whether the tool is read-only, error handling, or output format. The minimal description does not compensate for the lack of annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, with one sentence and a parameter list, but could benefit from better structure such as separating explanation from parameter details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and presence of an output schema, the description is mostly adequate but lacks context about the score range or interpretation, which would help agents use the result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds basic meaning to the sole parameter 'text' by stating it is the text to calculate the score for, compensating for the 0% schema coverage, but lacks details like length limits or encoding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates FORCAST readability grade level and specifies it is for non-narrative texts, distinguishing its purpose from siblings that target narrative texts, though it does not explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool by stating 'for non-narrative texts', but does not provide explicit guidance on alternatives or conditions when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility. It only lists parameters without explaining how the formulas differ, expected output, or any behavioral nuances (e.g., rounding, units). The presence of an output schema is not referenced.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, with a clear one-line summary followed by a bullet-like parameter list. It avoids unnecessary words and is easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema (which reduces the need to describe returns), the description adequately covers the input parameters and their options. It is complete for a simple calculation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates by listing all parameters with their meanings, defaults, and allowed values for 'sex' and 'method'. This provides critical context beyond the schema's basic type information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool's function ('Calculate ideal body weight using multiple formulas') with specific verb and resource. It distinguishes itself from sibling tools by focusing on ideal weight formulas, though not explicitly differentiating from similar health calculators.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this specific ideal weight formula calculator versus other related tools like bmi_calc or body_fat_calc. The description does not mention prerequisites or scenarios for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only says 'Convert'. It does not disclose behavioral traits like handling of edge cases, error handling, encoding, or whether comments and sections are supported. The minimal description leaves critical behavioral aspects unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, using a single sentence to state the purpose and one bullet for the parameter. No extraneous information is present, making it efficient for quick reading.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists, the description need not explain return values, but it lacks guidance on usage and parameter details. For a simple conversion tool among many similar siblings, it minimally conveys the core operation but misses contextual completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It describes the 'ini' parameter as 'INI content to convert', which adds some semantic context beyond the schema (e.g., it's content not a file path). However, it does not specify format expectations, validity constraints, or examples, providing minimal additional meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool converts INI config format to JSON, clearly identifying the input and output formats. This distinguishes it from sibling tools like json_to_yaml or toml_to_json that convert between other formats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, such as other format converters like json_to_yaml or toml_to_json. The description does not mention prerequisites, limitations, or contextual clues for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It only says 'Analyze keyword density' and lists parameters, omitting details like output format, case sensitivity, or whether it counts occurrences vs. frequency. This is insufficient for a tool with no annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one line for purpose followed by two bullet points for parameters. No wasted words, and the structure leads with the core function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While an output schema exists (not shown), the description still lacks completeness regarding behavioral details and return value structure. It does not explain what 'density' means (e.g., ratio, percentage) or handle edge cases. Given the tool's moderate complexity, the description is adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds meaningful explanations for both parameters: text as 'Text content to analyze' and keyword as 'Optional specific keyword to check density for.' This compensates for the schema's lack of descriptions, though additional detail on format or constraints would improve it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Analyze keyword density in text,' which is a clear purpose with a specific verb and resource. However, it does not differentiate from similar sibling tools like 'word_frequency' or 'keywords', which reduces clarity in context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It only states what it does, without mentioning when it is appropriate or when to avoid it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description lacks behavioral details such as the algorithm used (e.g., Mifflin-St Jeor), assumptions (e.g., activity level definitions), or output format. For a mathematical calculator, this transparency is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with a clear verb and resource, followed by a bulleted parameter list. No unnecessary words or repetition. Efficiently structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 6 parameters (3 required) and an output schema (not shown in description), the description should indicate what the output contains. It fails to describe return values or validation rules, making it incomplete for a non-trivial calculator.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds basic meaning to parameters (e.g., 'weight — Weight in kg') but with 0% schema coverage, it should explain valid values for 'activity' and 'goal'. The defaults are noted, but no enumeration or context is given, leaving ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Calculate daily macronutrient targets (protein, carbs, fat).' It uses a specific verb ('Calculate') and resource ('macronutrient targets'), and it distinguishes itself from sibling health calculators like BMR or TDEE.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives (e.g., bmr_calc, tdee_calc). It does not mention prerequisites, exclusions, or context. Users must infer usage from the parameter list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full behavioral disclosure burden. It fails to mention edge cases like division by zero if old_value is zero, or handling of negative values, which are critical for correct interpretation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Description is short and front-loaded with the main action. The parameter list is readable but not structured (e.g., not using a table or bullet points). Still, it is concise and every sentence serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple math tool with two numeric parameters and an output schema (present but not detailed in input), the description is adequate. However, it could include notes on edge cases to be fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so description must compensate. It provides basic definitions ('Original value.' and 'New value.') but lacks details like units, allowed ranges, or constraints. This is minimal but sufficient for a simple numeric tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool calculates percentage change between two values. The verb and resource are specific, and it is distinct from sibling tools like 'percentage_calculator' which likely handles different percentage operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, such as other calculator tools or different percentage functions. There are no exclusions or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden for behavioral disclosure. It does not mention that the tool fetches the URL content, nor does it discuss edge cases (inaccessible URL, non-text content, rate limits). The description is too minimal for a tool that performs network requests.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences, front-loading the purpose and then listing the parameter. No redundant information. However, it sacrifices completeness for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema (not shown), so return values are already documented. However, the description does not explain that the tool fetches the URL, nor does it cover potential failure modes or prerequisites. Given the sibling set includes many readability and URL tools, more context would help disambiguate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, but the description adds a brief explanation for the 'url' parameter ('The URL to analyze for readability.'). This adds some meaning beyond the schema's empty title, but lacks format requirements, examples, or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool analyzes URL readability using specific metrics (Flesch-Kincaid, Gunning Fog). It distinguishes from siblings like 'analyze_readability' (likely for text) and 'read_url' (which likely just fetches content). The verb 'Analyze' and resource 'URL readability scores' are specific and concrete.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'analyze_readability' or 'gunning_fog_score'. There is no mention of prerequisites (e.g., URL must be accessible) or exclusions. The agent must infer usage from context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility for behavioral disclosure. It only states the basic function without addressing edge cases, performance, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, front-loading the purpose. The parameter list is separate and clear. It could be slightly more detailed without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and an existing output schema, the description is minimally complete. However, it lacks behavioral context and usage guidelines, which would enhance completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal meaning to the parameter beyond the schema, clarifying that 'text' is 'with accents to remove'. However, it does not cover format or examples. Schema description coverage is 0%, so the description partially compensates.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action: removing diacritical marks/accents from characters. It identifies the verb and resource, distinguishing it from sibling text manipulation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It lacks context for usage, such as prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It states the calculation but does not mention the return format (e.g., calories per day), potential approximations, or any assumptions. For a read-only calculator, this is minimal but incomplete.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one main sentence and a clear parameter list. No filler or redundant information. The structure front-loads the purpose and then lists parameters efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the description covers parameters well, it does not describe the output (though an output schema exists). It could mention that the result is in kcal/day. For a 5-parameter tool, the description is adequate but not fully self-contained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds units for weight (kg), height (cm), age (years), and enumerates allowed values for sex and activity, which are absent from the schema (0% coverage). This significantly helps the agent understand parameter constraints beyond types and defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates Total Daily Energy Expenditure (TDEE) based on activity level. The verb 'Calculate' and specific resource 'TDEE' provide clear purpose. However, it does not explicitly distinguish from sibling tools like bmr_calc, though the focus on activity level implies the difference.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives like bmr_calc or macro_calc. The description does not specify that TDEE is for maintenance calories or that BMR is for resting state. No alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fails to disclose behavioral traits such as case sensitivity, return format, or whether it scans the entire input. The minimal description leaves significant uncertainty about how the tool operates.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with two sentences covering purpose and parameter. However, mixing parameter documentation into the main description instead of using the schema's description field makes it slightly less structured. Overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one input string) and presence of an output schema, the description is minimally adequate. However, it does not explain behavior like scanning logic or edge cases, missing opportunities to fully inform the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage for the 'code' parameter, but the description adds a brief explanation ('Source code to scan for TODO/fixme comments'). This provides basic context beyond the schema's type-only definition, though it lacks details like character limits or encoding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool finds TODO, FIXME, HACK, NOTE, XXX comments in source code, providing a specific verb and resource. It distinguishes from sibling code analysis tools like code_stats or code_complexity by focusing on comment markers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The description implies usage for scanning code comments but does not mention when to avoid it or compare with similar tools like search or analysis functions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explains the core behavior: truncation with optional ellipsis and default length. However, it does not disclose edge cases (e.g., text shorter than length) or any side effects. Without annotations, this is adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: one sentence stating the purpose followed by a parameter list. It is front-loaded and avoids redundancy, earning its place efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the main functionality but does not mention return value. Since an output schema exists (as per context), the description does not need to explain return values, but it could still hint at what to expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds meaning by listing parameters with brief explanations ('text — Text to truncate.'). This compensates for the schema gap but is minimal and does not elaborate on parameter constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Truncate' and the resource 'text', specifying the behavior with length and ellipsis options. It distinguishes itself from sibling text manipulation tools like 'capitalize_text' or 'reverse_text' by its specific truncation function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus other text tools. There is no mention of when not to use it or context like typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states basic functionality but does not disclose important behavioral traits such as handling of non-alphabetic characters, case sensitivity, or whether the cipher preserves case. This leaves significant gaps in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the purpose, using three sentences plus a bulleted parameter list. It is efficient, though the parameter list could be integrated into the prose to reduce redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description does not mention the return value (e.g., the transformed string). It omits details on edge cases and parameter constraints. For a tool with moderate complexity and zero schema description coverage, the description is incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It enumerates parameters with brief explanations (e.g., 'text — The plaintext or ciphertext string'), but these add minimal meaning beyond the parameter names and schema types. No details on constraints like key alphabetic characters or mode valid values are provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it encrypts/decrypts text using the Vigenère cipher with a keyword, which is a specific verb+resource combination. It effectively distinguishes itself from sibling tools like caesar_cipher or atbash_cipher by naming the specific cipher method.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says 'Use this for classical encryption using the Vigenère method,' which implies a context but does not explicitly state when not to use it or provide alternatives among siblings. There is no guidance on choosing this over other cipher tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavioral traits. It lacks details on wrapping algorithm (word vs character wrap), handling of long words, or newline behavior. For a text wrapping tool, these are important.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise with a clear front-loaded purpose and a brief parameter list. Every sentence is necessary and no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given an output schema, return values are covered. However, the description lacks details on wrapping behavior (e.g., algorithm, edge cases), which are important for a text wrapping tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description explains each parameter's purpose and default for width, adding value beyond the schema types and names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Wrap text to specified line width,' which is a specific verb+resource. However, it does not distinguish from the sibling tool 'line_wrap', which may serve a similar purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'line_wrap' or 'indent_text'. It only states what it does without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses parameter ranges but fails to mention output format (e.g., hex string like #RRGGBB), error conditions, or side effects. This is incomplete for a conversion tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise with a single sentence and parameter list. However, it omits output details, which would be valuable. Still, it avoids unnecessary verbiage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists but is not shown; the description does not explain return values. For a simple conversion tool, this is adequate but incomplete. Could mention the output type (e.g., hex color string).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no descriptions (0% coverage), so the description compensates by providing clear parameter descriptions and value ranges for all four parameters. This adds meaningful semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts CMYK to hex color, which is a specific verb+resource. It distinguishes from siblings like hex_to_cmyk, hex_to_hsl, etc., but does not explicitly differentiate from the reverse conversion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Parameter ranges are given (0-100), implying correct input values. No explicit guidance on when to use this tool vs alternatives, nor exclusions. Usage context is implied but not elaborated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only says 'beautify/format', but does not specify if the tool mutates input, returns a new string, or requires authentication. It lacks detail on side effects, rate limits, or error conditions. The output schema is not referenced, leaving return value ambiguous.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise: two sentences with bulleted parameters. No extra words or fluff. Information is front-loaded with the purpose, then parameter details in a structured list. Every sentence earns its keep.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (so return format need not be detailed), the description is adequate for a simple formatting task. However, it lacks mention of output behavior (e.g., returns formatted string), error handling, or size limits. The implicit assumption that it works for multiple languages is not confirmed. Completeness is moderate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning beyond the schema by explaining each parameter: 'code — Source code to beautify' and 'language — Programming language (default: javascript)'. However, it does not enumerate supported languages or provide constraints, leaving ambiguity about valid inputs. Since schema coverage is 0%, the description partially compensates but could be more precise.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Beautify/format source code with proper indentation.' It uses specific verbs (beautify/format) and resource (source code). It distinguishes from siblings like code_minify_js (minification vs beautification) and code_indent_check (checking vs fixing).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool vs alternatives (e.g., code_minify_js, sql_format). It does not mention prerequisites, limitations, or scenarios where other tools are more appropriate. Usage context is entirely implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It only states 'calculate' but does not disclose any behavioral traits such as whether it mutates data, requires authentication, or what errors might occur. For a read-only calculation tool, it is minimally transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a bullet list for parameters. It is front-loaded with purpose. A minor improvement could be reordering for better readability, but overall it earns its space.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the existence of an output schema, the description adequately covers parameters but lacks context on return values, error handling, or examples. For a financial calculator, this is adequate but not rich.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description fully compensates by explaining each parameter: shares (number owned), dividend_per_share (amount per share per payment), and frequency (options and default). This adds essential meaning beyond the basic schema types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates dividend income with specific payout frequencies (annual, quarterly, monthly). It is a specific verb+resource but does not differentiate from sibling tools like investment_calculator or compound_interest.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It does not mention context, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It uses the word 'estimate', implying approximation, but does not explain data sources, accuracy, or possible side effects. It lacks details on network requirements or what happens with unregistered domains.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one sentence for purpose followed by a parameter list with example. Every word serves a purpose, no fluff. Front-loaded with the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one parameter, no annotations, output schema present), the description is mostly complete. It states the purpose and parameter usage. However, it could mention error handling or limitations (e.g., 'requires valid registered domain') to fully prepare the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides no parameter descriptions (coverage 0%). The description compensates by specifying the parameter 'domain' with an example ('e.g. example.com'), adding clear meaning beyond the raw schema. This effectively guides the user on input format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool estimates 'domain registration age and expiry information', providing a specific verb and resource. It distinguishes from siblings like dns_lookup or dns_whois_lookup by focusing on age/expiry rather than general DNS data. However, it could be slightly more precise (e.g., 'expiry information' is vague).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives. For instance, it doesn't mention that one should use domain_age for age/expiry vs dns_whois_lookup for full whois data. Users receive no context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavior like how it handles invalid inputs (e.g., all three parameters zero) and whether it returns an error or the computed value. It only lists parameters without clarifying the required input combination or output format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the purpose. The parameter list is clear, but it could be more structured (e.g., bullet points or a table). Still, it's efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema (as per context), but the description doesn't reference it or explain what the tool returns. It also lacks handling of edge cases. For a simple calculator, more completeness is expected.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Since schema description coverage is 0%, the description adds critical meaning: units (kg, m/s², N) and the instruction to leave unknown as 0. This helps the agent understand how to provide inputs, though it could explain the relationship more explicitly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Calculate force, mass, or acceleration using F = ma' which is specific and verb+resource. It distinguishes from sibling tools like gravitational_force_calc or kinetic_energy_calc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs other physics calculators, nor any instructions on prerequisites like requiring exactly two known values. The description does not say when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Lacks detail on the algorithm, output format (though output schema exists), and any side effects or prerequisites; no annotations provided.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise with no wasted words; parameter descriptions are directly listed in a clear structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Sufficient for a simple generation tool; output schema compensates for lack of return value description, but could mention number of generated colors.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Adds meaning beyond the schema by specifying the hex format (without #) and providing an example for 'base', and states the default for 'count'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it generates a harmonious color palette from a base color, but does not explicitly differentiate from similar sibling tools like color_harmony.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as complementary_color or color_mix.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description should disclose behavioral traits. It only states the core function, lacking details on side effects, performance, or state changes. For a read-like tool, it doesn't even hint at being safe or idempotent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: two sentences plus a single parameter bullet. No wasted words, front-loaded with the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists, the description doesn't need to detail return values. However, it lacks context about edge cases (e.g., empty strings), and doesn't explain whether the output is boolean, score, or classification. Still adequate for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description adds a brief line for the 'text' parameter: 'Text to check for gibberish content.' This adds minimal meaning beyond the schema's empty description, but doesn't provide specifics like encoding or length limits.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Detect if text appears to be gibberish or random strings', which is a specific verb and resource. It clearly distinguishes this from sibling tools like 'detect_language' or 'sentiment' by focusing on gibberish detection.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., 'lang_detect' for language, 'analyze_readability' for text complexity). Missing context on when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description only states the conversion purpose and parameter. It does not disclose edge cases, invalid input handling, or color space assumptions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—two sentences covering purpose and parameter. No fluff, front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple conversion tool, the description covers the essential input format. The output schema (present) likely handles the return structure. Minor omission: no explicit output description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, but the description adds crucial format guidance: 'Hex color without # (e.g. '3498db')'. This compensates well for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Convert hex color to HSL values', specifying the verb and resource. It is distinct from sibling tools like hex_to_cmyk or hex_to_hsv, but lacks explicit output format details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus other color conversion tools (e.g., hex_to_hsv, hsl_to_rgb). No context on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It lists parameter ranges but does not disclose output format (e.g., with or without '#'), clamping behavior, or error handling. Minimal beyond purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: one sentence for purpose, then a clean list of parameters. No unnecessary words, front-loaded purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers input parameters adequately but omits output format details (e.g., 'returns hex string like #FF0000'). Given output schema exists, description could still clarify return structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds basic meaning to parameters (e.g., 'Hue angle (0-360)') which the schema lacks (0% coverage). However, it does not provide detailed constraints or examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Convert') and the specific conversion (HSV to hex), distinguishing it from sibling color conversion tools like cmyk_to_hex, hex_to_hsl, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description only explains functionality without context or exclusion criteria, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only states the basic function without mentioning supported languages, accuracy, network requirements, or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (two sentences, no fluff) and front-loaded with the core purpose. It could be slightly improved by listing key supported languages.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with an output schema, the description is adequately complete. It doesn't need to detail return values due to the output schema, though it could mention typical outputs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although schema description coverage is 0%, the description adds a brief explanation for the 'code' parameter ('Source code to detect language of'), providing modest value beyond the schema's title 'Code'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Detect' and the resource 'programming language of source code', distinguishing it from the sibling 'detect_language' which likely detects natural languages.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'detect_language'. The description lacks any context about prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It only states the input parameter but does not describe any behavioral traits (e.g., read-only, algorithmic details) or output beyond what schema implies.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise with a clear structure: one-sentence purpose followed by a parameter listing. Every element is necessary and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and presence of an output schema, the description sufficiently covers purpose and input. No omission is critical for a readability score calculator.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates by clearly explaining the 'text' parameter's role. This adds meaning beyond the schema's bare 'string' definition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it calculates Linsear Write readability score. Verb+resource is specific. However, it doesn't distinguish from sibling tools like 'analyze_readability' which might offer similar functionality, so not a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like other readability formulas. No context about prerequisites or use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of disclosing behavioral traits. It only states the basic computation but fails to mention critical details such as assumptions (e.g., fixed vs. adjustable rate, compounding frequency), whether taxes/insurance are included, or the nature of the amortization output. This leaves significant ambiguity for an agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise: a single sentence followed by a parameter list. Every element is functional and there is no extraneous text. The structure is clear and easy to scan, making it efficient for an agent to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema, the description need not detail return values, but it should provide enough context for parameter usage and behavioral expectations. The description covers the purpose but lacks guidance on input validation, edge cases, or assumptions. For a simple calculator with three parameters, this is adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It adds a useful example for the rate parameter (e.g., 5.5 for 5.5%) but offers no further clarification for principal or years. While the example helps, the description does not fully explain the expected units or constraints for all parameters, achieving only marginal added value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates monthly mortgage payments, total interest, and amortization. It uses a specific verb ('calculate') and resource ('mortgage payments'), and distinguishes it from siblings like loan_calculator or auto_loan_calc by explicitly mentioning amortization, which is characteristic of mortgage calculators.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. Given the many sibling financial calculators (e.g., loan_calculator, rent_vs_buy_calc), explicit when-to-use or when-not-to-use information is missing, making it likely for an agent to misuse or overlook this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It only explains input mapping but says nothing about output, edge cases (e.g., negative discriminant, a=0), or error handling. The output schema exists but the description adds no behavioral context beyond inputs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two short sentences. It presents the equation first, then lists parameters, which is a clear structure. Some redundancy (the equation line and parameter list) is acceptable; no unnecessary text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has three required parameters and an output schema, but the description omits critical aspects: what the function returns (roots, discriminant, etc.), handling of non-real solutions, and constraints (a ≠ 0). The existing output schema reduces the burden, but the description still lacks sufficient context for an agent to use it confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, meaning no parameter descriptions in the schema. The description compensates by defining each parameter (a, b, c) in the context of the quadratic equation, adding meaning beyond type 'number'. It clearly maps coefficients to their roles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Solve quadratic equation ax² + bx + c = 0', clearly identifying the verb (solve) and resource (quadratic equation). It is distinct from sibling tools, many of which are unrelated calculation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. It does not mention when not to use (e.g., for linear equations) or refer to related tools like 'evaluate_math' or 'slope_calc'. The context implies a specific quadratic solver but lacks explicit usage boundaries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It does not disclose which stop words list is used, how unsupported languages are handled, or any side effects. The output schema exists but its content is not hinted at.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one line of purpose followed by two lines of parameter definitions. No wasted words, and the core action is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple nature (2 params, no annotations, output schema exists), the description covers the basics. However, it omits potential issues like unknown language fallback or stop word list customization, leaving gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description adds basic meaning by explaining 'text' as the input text and 'language' as language with default 'english'. This adds value beyond schema types, but lacks detail like allowed language values or format restrictions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Remove', the resource 'common stop words from text', and the purpose 'for cleaner analysis'. It is specific and distinct from sibling tools like remove_accents or clean_whitespace.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, when not to use it, or comparison with similar tools like normalize_text.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description adds parameter ranges (0-255) but does not disclose behavioral traits like pure function behavior, output range specifics, or error handling. With output schema present, description partially compensates but remains minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Concise one-sentence description followed by clear bullet-point parameters. No extraneous text, but could include a note about output format.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple conversion tool with output schema, the description is adequate. However, it omits detail about output ranges (e.g., hue 0-360, saturation/lightness percentages) which could be helpful for interpretation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage; description adds valid integer ranges (0-255) for each parameter, which is essential for correct usage. Adds meaningful detail beyond schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states conversion from RGB to HSL with specific color model terms. Does not explicitly differentiate from sibling tools like hex_to_hsl or color_convert, but the name and description are unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives (e.g., hex_to_hsl, cmyk_to_hex). Lacks context for selection among color conversion tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does not disclose behavioral traits such as input validation, case sensitivity, or error handling. For example, it does not state whether empty strings or invalid units are accepted, or if the conversion is case-sensitive. This lack of transparency leaves the agent uncertain about edge cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two lines stating the purpose and a parameter list. It is front-loaded with the main action and units. Every word serves a purpose with no fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and low schema coverage, the description is minimal. It covers the basic conversion but omits details like output format, error handling, or unit variants. However, since an output schema exists, the description need not explain return values, but it still misses behavioral context for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It lists 'value — Speed value to convert.', 'from_unit — Source unit.', 'to_unit — Target unit.', which adds minimal clarity beyond the schema's property titles. However, it does not specify allowed values for from_unit/to_unit (e.g., exact strings, case sensitivity). This partial addition justifies a baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Convert between speed units: km/h, mph, m/s, knots, ft/s.' It specifies the exact resource (speed units) and the action (convert), effectively distinguishing it from sibling tools like angle_convert or area_convert.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It lacks instructions on prerequisites, limitations, or scenarios where this tool is preferred. The only context is the list of units, but no when-to-use or when-not-to-use details.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should carry full burden. It only states the tool formats SQL but doesn't disclose that it does not execute queries, side effects, or output behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: one-line purpose followed by parameter list. No redundant information, front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple formatting tool. Output schema exists but description doesn't mention return format. Could be more complete with example or note that result is formatted SQL string.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but description lists parameters with brief explanations and allowed dialect values, adding meaningful context beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states it formats/beautifies SQL queries with configurable dialect, clearly distinguishing it from sibling code formatting tools like 'code_beautify'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like 'code_beautify', nor when not to use it. Implies usage but lacks explicit context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosing behavioral traits. It fails to explain what 'major words' means (e.g., handling of articles, prepositions, conjunctions), how punctuation is treated, or whether the tool preserves existing capitalization. This lack of specificity reduces transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one clear sentence followed by a parameter list. Every word serves a purpose, and there is no redundant or extraneous information. It is well-structured and easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema (which clarifies return values), the description is reasonably complete but could benefit from clarifying the capitalization rule (e.g., 'using standard English title case, where articles and prepositions are lowercased unless they are the first or last word'). This would enhance completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no descriptions (0% coverage), so the description must compensate. It repeats the parameter name ('text') and adds a basic explanation ('Text to convert to title case'), but does not specify valid formats, length limits, or encoding. This adds minimal but non-zero value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: converting text to title case, with a specific verb ('Convert') and resource ('text to title case'). It distinguishes itself from sibling tools like 'convert_case' and 'capitalize_text' by specifying the transformation type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as when text requires more nuanced casing rules or when to use 'capitalize_text' instead. No prerequisites, exclusions, or context are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses parameters but lacks behavioral details such as how the age range is determined, limitations, or output format. The existence of an output schema does not compensate for missing behavioral context in the description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with no wasted words, front-loading the purpose. However, it could be slightly more structured, e.g., adding a brief example.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter tool with an output schema, the description covers the purpose and parameters adequately. However, it lacks information about the return value format and potential edge cases, which would make it more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds meaning to both parameters: text is described as 'Text to check age appropriateness for', and min_age as 'Minimum age filter (default: 0 = no filter)'. This clarifies the parameters beyond their types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool determines the age range for which text content is appropriate, using a specific verb and resource. This distinguishes it from sibling tools like analyze_readability or analyze_tone.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives, nor any exclusions. The description only states the purpose without context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It only states the basic operation without disclosing how sentence boundaries are detected (e.g., handling of abbreviations, newlines) or any edge-case behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: one sentence plus a parameter list. It front-loads the purpose efficiently. However, the parameter list could be integrated more elegantly, and the structure is minimal.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one string parameter, output schema exists but no nested objects), the description is adequate but lacks details on sentence boundary behavior and potential edge cases. It meets the minimum viable standard.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides no description for the 'text' parameter (0% coverage). The description compensates by adding 'Text to capitalize', which clarifies the parameter's role and adds meaning beyond the schema's type constraint.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: 'Capitalize the first letter of each sentence in text.' It uses a specific verb and resource, and explicitly mentions sentence-level capitalization, which distinguishes it from sibling tools like 'title_case' (word-level) or 'uppercase'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'title_case' or 'convert_case'. There is no mention of prerequisites, context, or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It states it mixes colors with a ratio, but does not specify the mixing method (e.g., RGB linear interpolation), output format, or behavior with invalid input (e.g., non-hex strings). This is minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the purpose. The parameter list is clear but slightly verbose; it could be condensed. Overall, no extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema, the description does not need to detail return values. However, it lacks edge-case handling, input validation notes, or mixing domain context (e.g., color space). Adequate for a simple tool but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning to all three parameters beyond the input schema: it explains that color_a and color_b are hex colors without '#', provides examples, and defines the ratio range and default. Despite 0% schema coverage, the description covers all parameters well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Mix two hex colors together with a given ratio,' which is a specific verb-resource combination. It distinguishes itself from sibling color tools like complementary_color or color_tint_shade by focusing on mixing two colors with a ratio.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives like complementary_color or color_blindness_sim. It does not mention scenarios, prerequisites, or exclusions, relying only on the implied use case of mixing two colors.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description only mentions 'CSV text with header row and data rows'. Does not disclose error handling, edge cases (e.g., quoted fields, missing values), or behavior for malformed input.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences plus a parameter line, front-loaded with purpose. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists (not shown) so return description is not needed. Lacks mention of delimiter assumptions, encoding, or size limits, but adequate for a simple 1-param tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has only a 'csv' string with 0% coverage; description adds essential meaning: 'CSV text with header row and data rows', clarifying format and structure.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Parse CSV text into structured JSON array' with a clear verb and resource. It distinguishes from siblings like convert_json_to_csv but doesn't explicitly differentiate from similar tools like tsv_to_json.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides context ('from spreadsheets or exports into JSON format for programmatic use') but lacks explicit when-not-to-use or alternatives like TSV conversion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as read-only status, destructive actions, authentication needs, error handling, or validation of timezone codes. The user is left unaware of potential failures or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, using a short introductory sentence followed by a clear parameter list. Every sentence is valuable, no fluff, and the main purpose is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the primary purpose and parameters but omits edge cases, error behavior, and supported timezone formats beyond a short list. Given the output schema exists, return values are likely documented, but completeness for a simple conversion tool is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema description coverage, the description adds meaningful parameter semantics: it explains the timestamp parameter defaults to current time, and both from_tz and to_tz default to 'UTC'. This compensates well for the schema's lack of detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts timestamps between timezones, with a specific verb and resource. However, it does not explicitly distinguish from sibling tools like time_convert or convert_timestamp, which may have overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says 'Use this when you need to express times in a different timezone,' providing clear usage context. However, it does not mention when NOT to use it or list alternative tools, limiting guidance for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It does not mention rate limiting, permissions, robots.txt compliance, or the format of returned 'structured page content'. This leaves significant gaps for an agent deciding whether to invoke the tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences plus a parameter list are efficient and front-loaded with purpose. The formatting is slightly informal (using 'Parameters:' block), but no unnecessary text. Could be more structured but remains concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, return values are not required. However, the description lacks context on how crawling works (e.g., does it follow sitemap links only? How are max_pages applied?). Additional details on expected behavior and limitations would improve completeness for a complex operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It briefly explains url as 'Website URL to crawl' and max_pages with its default, adding minimal context beyond the schema. This meets a baseline but offers no deeper semantics (e.g., accepted URL formats, page count limits).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool crawls a website's sitemap and returns structured page content. The verb 'crawl' and resource 'sitemap' are specific and distinct from siblings like 'web_scrape' and 'read_url'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for crawling multiple pages via sitemap, but provides no explicit guidance on when to use this tool versus alternatives (e.g., web_scrape for single pages). No when-not-to-use or exclusion criteria are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must cover behavioral traits. It only states the basic function without disclosing output format (score vs grade level), input requirements (plain text, length limits), or edge cases. The output schema may help, but the description itself adds little transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences for the purpose and one parameter listed. It is front-loaded and contains no superfluous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one param, output schema exists), the description is fairly complete. It states the purpose and input. Missing usage guidelines and behavioral depth are minor for this simple tool, but they prevent a perfect score.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must explain parameters. It adds 'text — Text to calculate Dale-Chall score for,' which clarifies the single parameter's purpose. However, it lacks details like maximum length, encoding, or content restrictions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Calculate Dale-Chall readability score for text.' The verb 'Calculate' and resource 'Dale-Chall readability score' are specific, and it distinguishes from sibling tools like 'fry_readability' or 'gunning_fog_score' by naming a unique metric.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. The description does not mention scenarios, prerequisites, or when Dale-Chall is preferred over other readability scores.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description partially carries the burden. It mentions a confidence score but does not detail behavior for empty text, multiple languages, or unknown languages. Adequate for a simple tool but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Description is extremely concise with two clear sentences. No superfluous content, and the parameter section is neatly formatted.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (not shown), the description appropriately mentions the confidence score. For a simple language detection tool, this covers the key aspects, though edge cases are not addressed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. The parameter description ('Text to detect language of') adds minimal clarifying value beyond the parameter name. However, given a single straightforward parameter, it is minimally adequate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool detects language and returns a confidence score. However, it does not distinguish itself from the sibling tool 'lang_detect', which likely performs a similar function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., lang_detect). The description simply states what it does without context on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool checks DNSSEC and validates the chain, but doesn't explain what happens if DNSSEC is missing, whether it makes external queries, or any rate-limiting or permission considerations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short (two lines plus parameter list) and front-loaded with the purpose. It could be more structured, but it is efficient with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 1 parameter and an output schema (not shown), the description adequately states the core function. However, it lacks behavioral details about error handling or performance, leaving the agent with minimal context for complex scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description must compensate. It adds 'Domain — Domain name to check (e.g. 'example.com').' This provides an example but little additional meaning beyond the schema's type and title.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks DNSSEC enablement and validates the chain. This is a specific verb ('Check') and resource ('domain DNSSEC') that distinguishes it from siblings like dns_lookup or dns_whois_lookup.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives like dns_lookup or reverse_dns_lookup. Usage is implied by the name and description but not clarified.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description clarifies the input parameters (e.g., annual interest rate example) but does not mention output format, rounding, or precision. Since annotations are absent, the description bears full responsibility, but it provides only basic parameter details without deeper behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a clear opening sentence and a parameter list. It is front-loaded with the purpose and avoids unnecessary words. The parameter list is slightly redundant with the schema but adds brief clarification.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of a full input schema and output schema (though not shown), the description sufficiently explains the calculation purpose. However, it omits details about the output and fails to differentiate usage from similar siblings, leaving some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds value for the 'rate' parameter by providing an example format ('e.g. 8.5 for 8.5%'), but for 'principal' and 'tenure_months', it merely restates schema titles. This marginal addition keeps it at a baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates Equated Monthly Installments for loans, which is a specific verb+resource. Among siblings like 'loan_calculator' and 'mortgage_calculator', it uniquely focuses on EMI, so it is well-distinguished.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternative finance calculators like 'loan_calculator' or 'compound_interest'. The description lacks context for selection and does not mention exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It only states the basic operation and mentions the separator default, but it does not disclose how arrays are handled (e.g., array indices), what happens with invalid JSON, circular references, or non-object types. This is insufficient for predictable invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short and front-loaded with the core action. It uses a bullet list for parameters. While efficient, it could be more structured (e.g., separate the description from parameter details). Nearly conciseness-perfect with minimal waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with only two parameters and no output schema provided in the description (though context says one exists). The description covers essential purpose and parameters but lacks details on return format, error behavior, and edge cases. Adequate but not complete given the lack of annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It briefly explains both parameters: json_str is the JSON string, separator is the delimiter (with default). This adds some value but does not explain constraints like valid JSON format or acceptable separator characters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool flattens nested JSON to dot-notation key-value pairs. This is a specific verb+resource combo that distinguishes it from siblings like unflatten_json (which does the inverse) and process_json (general JSON processing).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you need to flatten JSON, but it does not explicitly state when to use over alternatives, nor does it mention when not to use it. No exclusions or context for selecting this tool over related tools like unflatten_json.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description carries full responsibility. It states the tool calculates GCD and LCM but omits key details: the format of the output (e.g., JSON object with 'gcd' and 'lcm' fields), handling of edge cases (negative numbers, zero), and any side effects. For a simple computation, this is minimally adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences plus a bullet list. No extraneous words. Every line conveys essential information efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with two parameters and an output schema (unseen). The description covers the basic purpose but lacks details on output structure, error handling, or valid input ranges. It is adequate but not thorough for a tool with no annotations and 0% schema coverage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, requiring the description to compensate. However, it merely paraphrases the schema ('a — First number', 'b — Second number') without adding constraints, ranges, or examples. The description adds little value beyond the parameter titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Calculate GCD and LCM' with specific resource 'two numbers'. The verb and resource are precise, and it naturally distinguishes from sibling math tools that perform other calculations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., fraction_calc, prime_operations). There is no mention of specific use cases or conditions for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description lacks details on the tool's behavior beyond the output, such as the number of taglines generated, randomness factors, or any safety considerations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences plus parameter list, but could be better structured by integrating the parameter description more smoothly or adding a one-line summary of the output.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema, the description does not need to detail return values, but it fails to specify the number of taglines or provide comparative context against sibling tools, leaving some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The parameter description 'Brand or content description' adds meaningful context beyond the schema, clarifying the expected input. Though only one parameter exists, the description effectively communicates its purpose.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates 'short, memorable taglines' from 'brand description', effectively distinguishing it from similar tools like generate_slogan or generate_hashtags.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of scenarios where generate_tagline is preferable over generate_slogan or other content generation tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It mentions Newton's law but does not disclose behavior on invalid inputs (e.g., negative or zero masses/distance), precision, or how results are returned. The output schema exists but is not described here.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the purpose. Parameter explanations are provided but could be more structured (e.g., bullet points). Overall, no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 3-parameter tool with an output schema, the description covers the basic purpose and parameter meanings. However, it lacks usage guidelines and behavioral details, making it minimally adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds units (kg, m) and clarifies that mass1 and mass2 are masses of objects and distance is between centers. Since the input schema has 0% description coverage (only titles), this adds meaningful context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Calculate gravitational force between two masses using Newton's law,' which is a specific verb+resource. It uniquely identifies the tool among many siblings, as no other tool calculates gravitational force.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention limitations, prerequisites, or situations where other tools (like force_calc) might be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the full responsibility. It does not mention edge cases (e.g., invalid hex, case sensitivity), output format, or any limitations. This leaves the agent uncertain about behavior beyond the basic conversion.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences: purpose followed by parameter explanation. It is well-front-loaded but could be more structured with bullet points for readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a simple tool with one parameter and an output schema (presumably documenting return values), the description is minimally adequate. However, it lacks details about validation, error handling, or the exact output structure, leaving some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds critical meaning: it clarifies that hex_color should be without # and provides an example. This compensates for the missing schema description, although more detail (e.g., case tolerance) would improve it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Convert hex color to CMYK' with a clear verb and resource. It specifies the input format without #, distinguishing it from sibling color conversion tools like cmyk_to_hex or convert_color.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as convert_color or hex_to_hsl. The description simply states what it does without context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It does not mention error handling (e.g., invalid JSON), performance considerations, or any side effects. The minimal description leaves significant uncertainty for an AI agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one sentence plus a parameter list) and front-loaded with the main action. It is appropriately sized for a simple tool, though it could include more detail without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (one parameter, output schema present), the description is reasonably complete. It covers the core function, and the output schema documents return values. However, missing details like error handling slightly reduce completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The sole parameter json_str is described as 'JSON string to convert', which adds no meaningful information beyond its name and type from the schema. Schema coverage is 0%, but the parameter is simple; however, the description should explain expected format or constraints (e.g., valid JSON required).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Convert' and the resources 'JSON string to YAML format', making the tool's purpose unambiguous. It distinguishes itself from sibling tools like json_to_xml or xml_to_json.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs. alternatives (e.g., for converting JSON to XML). The description implies usage but does not explicitly state prerequisites or scenarios where it is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses the Boer formula and parameter units, which adds value beyond the schema. However, does not describe the output format (presumably LBM in kg) or address edge cases. No annotations are provided to supplement.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: a single sentence for purpose and a bullet-point list for parameters. No wasted words; front-loaded with the main action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequately covers the calculation details for a simple tool. Missing explicit output description and differentiation from sibling health calculators. Could better address what the result represents.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description effectively explains each parameter's unit (kg, cm, years) and the default 'male' for sex. Adds meaning beyond the raw schema types but lacks constraints like valid ranges.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Calculate lean body mass (LBM) using Boer formula' – specific verb and resource. Distinguishes from siblings by specifying a unique formula, but does not explicitly differentiate from similar body calculators.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like BMR or body fat calculators. The mention of 'Boer formula' implies usage for LBM estimation, but no context about appropriate users or situations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility for behavioral disclosure. It only lists parameters without explaining behavior for invalid inputs, error handling, or how base_size affects conversion. This is insufficient for safe tool invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and uses a structured list for parameters. It is front-loaded with the purpose statement. Every sentence adds value, though the parameter explanations are terse yet sufficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists, return values need not be explained. However, for a tool with many sibling converters, more context on limitations (e.g., percent conversion requires base_size) would improve completeness. The description is adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description compensates by adding meaning to each parameter: 'value', 'from_unit', 'to_unit', and 'base_size' with a default. It clarifies accepted units and default behavior, which the schema lacks.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts between specific CSS units (px, pt, rem, em, percent) with a verb and resource. It distinguishes itself from sibling conversion tools by targeting CSS units, leaving no ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'convert_units' or other unit converters it only states what it does, not when to prefer it or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden but only states the basic action. It does not disclose behavioral traits like timeout behavior, connection details, or what constitutes 'open' or 'closed'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a short sentence and parameter list. It is front-loaded and wastes no words, though it could benefit from a structured format.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers the essential purpose and parameters, but lacks usage guidelines and behavioral transparency. An output schema exists, so return value details are not required, but the description could still be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description adds meaning: specifies host as 'Hostname or IP address', port range (1-65535), and protocol default ('tcp'). This compensates for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Check if a network port is open on a host.' It uses a specific verb ('Check') and resource ('network port'), and distinguishes it from siblings which cover other utilities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description provides no context about prerequisites, limitations, or situations where another tool might be more suitable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions counting by type but lacks details on what qualifies as punctuation, handling of edge cases, or performance traits. For a simple tool this is minimal but acceptable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences, no wasted words. Structure is clear: purpose first, then parameter list. Could be slightly improved by adding a note about the output.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the existence of an output schema, the description covers basic usage. It doesn't specify what punctuation types are counted, which may leave some ambiguity, but is adequate for a straightforward tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description adds value by explaining the 'text' parameter. However, it only restates the parameter name and type without deeper semantics, achieving a baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool counts punctuation marks by type, using a specific verb and resource. It effectively distinguishes from siblings like char_count, word_count, or other text analysis tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. No context about prerequisites or scenarios where it is appropriate or not.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It mentions 'purchasing power comparison,' which adds value beyond simple conversion. However, it lacks details on rate limits, authentication, or side effects. The behavioral disclosure is adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with a clear purpose sentence, followed by a parameter list. While the parameter list is verbose, it is structured and useful. No wasted sentences, but could be more compact.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 5 parameters and an output schema. The description explains the conversion and purchasing power comparison, but does not clarify how the comparison works (e.g., based on PPP indices) or describe the output format. Adequate but leaves some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It lists parameters with brief defaults but essentially restates schema titles (e.g., 'Salary amount', 'Source currency code'). It adds minimal extra meaning beyond the schema, but the defaults are helpful. Score 3 reflects baseline compensation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Convert salary between currencies with purchasing power comparison.' This distinguishes it from sibling tools like convert_currency (simple currency conversion) and salary_breakdown (breaking down salary components).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., convert_currency, salary_breakdown). There is no mention of context or exclusions, leaving the agent to infer usage from the description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavioral traits. It mentions default cycles and range but does not explain how the tool calculates the schedule, what happens if both bedtime and wake_time are provided, or how invalid times are handled. The behavioral transparency is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with the main purpose. The parameter list is integrated but not verbose. Every sentence provides information, though the structure could be slightly more organized (e.g., separating the purpose from parameter details).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity, the description is adequate but incomplete. It does not mention edge cases (e.g., both parameters provided) or the output format (though output schema exists). The lack of explanation about the time format and validation limits completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must add meaning. It explains each parameter: bedtime defaults to calculating from wake time, wake_time defaults from bedtime, and cycles has a default and range. This adds significant context beyond the schema types and titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Calculate optimal sleep schedule based on sleep cycles (90 min each)'. It uses a specific verb ('Calculate') and resource ('sleep schedule'), and distinguishes itself from sibling tools (no other sleep-related tools in the list).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, exclusions, or suitable contexts. The usage is only implied by the function name and brief parameter descriptions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Minimal disclosure: describes validation of format but does not specify behavior on invalid input (e.g., error message vs boolean return), nor explicitly state it is a read-only operation. No annotations exist to compensate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Short and to the point, but slightly under-specified for a validation tool. Could include example or accepted format without adding verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and presence of an output schema, the description adequately covers the core functionality. However, missing details about validation extent (format only vs. checksum) slightly reduce completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description merely restates the parameter name 'vat' without adding meaning beyond the input schema. It does not specify expected format (e.g., country code prefix, length) or provide examples, despite 0% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool validates VAT number format for EU countries, using a specific verb and resource. It distinguishes from sibling validation tools like validate_iban.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives (e.g., validate_iban, validate_json). Lacks context on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does not disclose behavior like case sensitivity, handling of empty strings, or output format. The return value semantics are omitted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with a clear structure: purpose, usage note, then parameter list. It is front-loaded with the main purpose and avoids unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, output schema existence, and no annotations, the description adequately covers the purpose, usage, and parameter semantics. It omits edge cases but is sufficient for a straightforward similarity tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful explanations for each parameter beyond the schema, such as 'first string to compare' and lists method options with defaults. Despite the context indicating 0% schema coverage, the description actually provides parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates string similarity between two words or phrases and lists the algorithms. It distinguishes from siblings like levenshtein_distance by specifying different methods, but does not explicitly differentiate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says 'Use this to compare strings using various algorithms,' which implies when to use it, but it does not specify when not to use it or mention alternative tools. The context from sibling tools is not leveraged.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It mentions parameter units and default but does not outline formula, edge cases (e.g., zero/negative values), error handling, or return value structure. The output schema exists but is not referenced.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief, with a clear introductory sentence followed by a list of parameters. No redundant information. It is front-loaded and every sentence serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool is simple and the output schema presumably documents return values, the description omits any mention of required parameters (schema indicates weight and height are required) and does not discuss potential errors or usage scope. It is adequate but leaves gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description must compensate. It adds meaning by specifying units for weight and height (e.g., 'kg for metric, lbs for imperial') and defines the unit parameter's values. This is helpful but could be more precise (e.g., requiring positive numbers).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Calculate BMI (Body Mass Index) from weight and height.' This provides a specific verb, resource, and scope. It uniquely identifies the tool among siblings, as BMI calculation is distinctly described.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives like bmr_calc or body_fat_calc. The description does not specify prerequisites, contexts, or exclusions, leaving the agent without comparative advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits like error handling, data limits, or side effects. It only states the calculation type and parameter format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with only 4 lines, front-loading the core action. No extraneous text. The parameter list is clear and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the description covers the basic functionality and parameters, it does not address limitations (e.g., requirement of equal-length data), edge cases, or differentiate from the many sibling tools. However, the presence of an output schema somewhat mitigates the need for return value explanation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 0% description coverage, so the description compensates by explaining 'method' as 'pearson' or 'spearman' with default, and 'x', 'y' as comma-separated values. This adds meaningful context beyond the schema's type string.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the action ('Calculate'), the resource ('correlation'), and the two supported methods ('Pearson or Spearman'). This is specific and distinguishes it from other statistical tools among siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives such as 'descriptive_statistics' or 'calculate_distance'. No when-not or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description lacks behavioral details such as error handling, rate limits, or permission requirements. With no annotations provided, the minimal description fails to disclose important aspects like what happens if the URL is invalid or if detection fails.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences: one for purpose and one for the parameter. It front-loads the core functionality, making it easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description does not need to explain return values. However, it omits context about error states, network requirements, or what constitutes a valid URL. Combined with no annotations, the description feels incomplete for a tool that makes external requests.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning to the single parameter 'url' with an example URL, which is more informative than the schema's minimal 'Url' title. Since schema coverage is 0%, the description partially compensates, though it could detail acceptable formats or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Detect which CDN or reverse proxy is serving a website.' It specifies a specific verb ('Detect') and resource ('CDN or reverse proxy'), and is distinct from sibling tools that detect languages or text encoding.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not indicate when to use this tool versus alternatives like http_client or dns_lookup, nor does it mention prerequisites or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description should disclose behavior beyond the basic purpose. It only says 'check and validate' without explaining what the validation entails, what the output looks like, or how it handles edge cases. The output schema exists but is not referenced in the description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one introductory sentence and a brief parameter list. Every sentence earns its place; no redundancy or unnecessary detail. The structure is front-loaded with the purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema (not shown), the description does not need to detail return values. However, it lacks behavioral context (e.g., what kind of validation, supported languages for the default) and does not mention any prerequisites or limitations. It is adequate but incomplete for a tool with many siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description's parameter list adds meaning: it explains that 'code' is source code to check and 'language' is the programming language with default 'python'. This clarifies the role of each parameter beyond the schema's type-only definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Check and validate code indentation consistency' with a specific verb and resource. It distinguishes itself from sibling tools like 'indent_text' (which indents) and 'code_beautify' (which formats broadly).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'code_beautify' or 'code_stats'. It does not mention when not to use it or any prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It explains the basic behavior (generates schemes) and notes the color format (without #). However, it does not mention what the output looks like, any limitations, or whether it validates input. For a simple tool, this is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at three lines, front-loading the purpose. The 'Parameters' section is clear but somewhat redundant with the schema. It could be more streamlined, but there is no unnecessary text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists and the tool is simple, the description covers the essential information. It lacks detail on scheme options, but overall it is sufficient for the agent to understand the tool's purpose and parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must add meaning. It explains 'color' as base hex color without # and 'scheme' as harmony type, but does not list possible values for scheme (e.g., complementary, triadic). This leaves ambiguity about acceptable inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates color harmony schemes, listing specific types (complementary, triadic, analogous) which distinguishes it from siblings like complementary_color that likely outputs only one scheme.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives, no prerequisites, and no exclusions. The description does not help the agent decide between this and related sibling tools like color_mix or generate_color_palette.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It only states the tool fetches exchange rates, without mentioning rate limits, authentication requirements, side effects, or response behavior. This is minimal transparency for a data retrieval tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short with a one-sentence summary followed by a parameter bullet list. It is front-loaded and efficient, though the bullet list repeats some schema defaults. Overall, every sentence contributes to understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has four optional parameters and an output schema. The description covers parameter meaning adequately, and the purpose sentence implies the output (exchange rates). With no annotations, it could mention output structure or limitations, but the presence of an output schema reduces the need. Complete for basic usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It provides brief explanations for each parameter (source/target currency, amount, date with default values). While helpful, it lacks detail like valid currency codes, date format specifics, or amount constraints. This adds meaning beyond the schema but could be richer.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Get cross-currency exchange rates with optional historical date,' specifying a distinct verb, resource, and optional scope. This distinguishes it from siblings like 'convert_currency' and 'list_currencies' by focusing on rate retrieval with a historical feature.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as 'convert_currency' or 'list_currencies.' The description lacks context for choosing between tools, leaving the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description should fully disclose behavior. However, it does not mention handling of invalid inputs, edge cases (e.g., empty arrays, non-numeric values), or the return format (though an output schema exists). It lacks transparency about potential errors or limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a clear purpose statement, a bullet-like list of statistics, and a parameter explanation. It is front-loaded but could be more structured with clear labeling of sections.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one parameter and an existing output schema, the description adequately covers what the tool does and how to provide input. It lists the computed statistics, though it omits details like output format for quartiles. Overall sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema description coverage, the tool description adds meaning to the 'numbers' parameter by specifying it accepts comma-separated numbers or a JSON array. This clarifies the input format beyond the schema's bare type 'string'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Calculate' and lists the resource 'descriptive statistics' including a clear enumeration of outputs (mean, median, mode, etc.). It distinguishes itself from siblings by being a general stats tool, not a specialized one like calculate_correlation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool over alternatives, no exclusions or prerequisites. It simply states what it does without context for selection among many similar statistical tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It fails to disclose important behavioral traits such as error handling when insufficient parameters are provided, or whether it performs multi-equation solving. The output schema exists but behavior beyond that is opaque.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one sentence defining purpose and a parameter list with units. Every element adds value, and the main action is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description adequately defines inputs. However, it lacks preconditions (e.g., at least two parameters required) and does not mention the equation solving logic, leaving some gaps for a calculation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description compensates by adding units (V, A, Ω, W) and usage hints ('leave 0 if unknown'), providing meaning beyond the raw parameter names and types in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates electrical values using Ohm's Law and power equations, specifying the verb 'calculate', the resource 'electrical values', and the governing laws. It distinguishes itself from sibling calculation tools by focusing on electrical domain.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives, nor does it provide conditions for use (e.g., need at least two inputs). It only implies usage by listing parameters and suggesting to leave unknown as 0.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only states 'Convert between energy units' without disclosing any behavioral traits such as error handling, precision, or supported unit validation. This is minimal and leaves the agent guessing about edge cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two effective sentences: one for the purpose and one for the parameters. Every sentence adds value, and the structure is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple unit converter, the description covers the essential functionality and parameter meanings. However, it lacks details about valid unit inputs, error behavior, or output format (despite an output schema, its content is unknown). It is adequate but not fully comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds meaning by listing parameters and their purposes ('value — Energy value', etc.). However, it does not specify valid unit strings or constraints, so the added value is moderate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Convert between energy units' and lists a specific set of units (J, cal, Wh, kWh, BTU, ft-lb, eV), making its purpose clear and distinguishing it from sibling conversion tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for energy unit conversion but provides no explicit guidance on when not to use or alternatives. It is straightforward for such a simple converter, but lacks exclusions or comparisons to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description should disclose behavioral traits. It states the action (generate) but does not mention edge cases, default starting values (e.g., 0 and 1), or what happens with invalid input like negative count. The behavioral transparency is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise with two sentences: one for purpose and one for parameter documentation. Every sentence serves a clear function with no unnecessary words or redundancies.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema (which likely documents the return format), the description is moderately complete. However, it omits key behavioral details like starting values (e.g., 0, 1) and error handling, which would help the agent anticipate output for edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explicitly explains the 'count' parameter: 'Number of Fibonacci numbers (default: 10).' Since the schema provides no description (0% coverage), this adds essential meaning beyond the default value and type, helping the agent understand the parameter's role.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate the Fibonacci sequence up to the specified count.' It uses a specific verb (Generate) and resource (Fibonacci sequence) with a clear qualifier, distinguishing it from sibling tools like factorial_calculator or prime_operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, nor does it mention limitations or prerequisites. It only describes the parameter count, leaving the agent to infer usage context from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the burden of disclosure. It indicates a read-only generation operation, which is accurate. No mention of AI usage or potential inconsistencies, but for a simple generation tool, this is minimally adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with no wasted words. The purpose is stated first, followed by the parameter in a clear format. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (single parameter, clear purpose) and the existence of an output schema, the description is sufficiently complete. It could mention that the result is a list of hashtags, but this is likely covered by the output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It explicitly defines the 'text' parameter as 'Content to generate hashtags from', adding clear semantics beyond the schema's type-only definition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool generates hashtags from content for social media. The verb 'generate' and resource 'hashtags' are specific, distinguishing it from sibling tools like 'keywords' or 'generate_slogan'. However, it does not explicitly mention the output format (e.g., list of strings).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like 'keywords' or 'generate_seo_metadata'. The description only states the action, lacking context on appropriate use cases or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states only what the tool does (generate slogans) without disclosing behavioral traits such as AI model usage, number of outputs, or limitations. This is insufficient for a generative tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: two sentences that state purpose and parameter definition. No wasted words, front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and the tool's simplicity (one parameter), the description is sufficiently complete. It covers the input clearly and, with the output schema, the agent can infer return structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description clarifies the single parameter 'text' as 'Brand or product description', adding meaningful context beyond the schema's generic string type. Schema coverage is 0%, so the description compensates well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'generate' and the resource 'catchy marketing slogans' from brand/product description. It is specific but does not differentiate from similar sibling tools like 'generate_tagline' or 'generate_pitch', which may cause ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when a slogan is needed from a description, but lacks explicit guidance on when not to use it or alternatives. No mention of when to prefer this over sibling tools like 'generate_tagline'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It implies a read-only operation via 'display', but does not explicitly state behavior like side effects, error handling, or limitations. It adds basic transparency but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one sentence for purpose followed by a parameter line. Every part is essential, no wasted words, and it is front-loaded with the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter), the description is mostly complete but lacks details about the output format (beyond listing components) and any usage constraints. The presence of an output schema (not shown) may mitigate this, but relying on that, the description is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides a brief parameter description ('Text to create hex dump of') which adds minimal meaning beyond the schema. This is adequate but not thorough.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool displays a hex dump of text with offset, hex bytes, and ASCII representation. It uses a specific verb and resource, and there is no sibling tool with similar functionality, so it distinguishes well.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, intended use cases, or when not to use it. Given the tool is a utility for text representation, the absence of usage guidance lowers the score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description carries full burden. It states input must be hex without '#', but does not disclose output ranges (e.g., 0-360 for hue) or error handling for invalid input. Adequate for a simple conversion but lacks detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, parameter in second. No wasted words. Efficient and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter color conversion, the description covers the input format. Output schema exists, so return values need not be described. Lacks error scenarios but sufficient for typical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has no parameter description (0% coverage). Description adds 'without #' and an example, clarifying the expected format. This compensates well for the schema gap, though could specify valid characters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Convert hex color to HSV values', specifying the action and output. It distinguishes from sibling tools like hex_to_hsl by explicitly mentioning HSV, though it could be more precise about the HSV value format.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool over alternatives like hex_to_hsl or hsv_to_hex. No prerequisites beyond the parameter description. Minimal context for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral details like redirect handling, error responses, or rate limits. 'Analyze' is vague.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no wasted words, front-loading the purpose and parameter details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one parameter and an output schema, the description adequately explains basic usage but omits details on response format, error cases, and the nature of 'analysis'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning to the single parameter 'url' by explaining its purpose and providing an example, compensating for the 0% schema description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the tool fetches and analyzes HTTP response headers from any URL, distinguishing it from similar tools like http_client by focusing on headers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool vs alternatives such as http_client, check_ssl_certificate, or analyze_url.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description lacks behavioral details beyond stating it calculates subnet info. With no annotations provided, the description does not disclose error handling, input validation, or any side effects, which is inadequate for a calculation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at two sentences plus parameter details. It front-loads the purpose, then lists parameters. Every part earns its place, though the parameter list could be more integrated into the prose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description appropriately focuses on what the tool calculates. It covers the key outputs (network, broadcast, hosts) and the parameter details, making it complete for a straightforward subnet calculator.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema description coverage, the description adds meaning by explicitly defining each parameter with examples: 'ip — IP address (e.g. '192.168.1.0'). cidr — CIDR prefix length (default: 24).' This compensates for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Calculate IPv4 subnet information: network, broadcast, hosts.' It uses a specific verb and resource, distinguishing it from siblings like 'ipv6_expand' by focusing exclusively on IPv4 subnet calculations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, when not to use it, or comparison to sibling tools such as 'ipv6_expand', leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description does not disclose error handling (e.g., invalid JSON, missing path), side effects, or read-only nature. Minimal behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: one sentence for purpose, then bullet-style parameter descriptions. No wasted words. Front-loaded with the main action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Has an output schema (not shown) which reduces need for return value explanation. However, lacks coverage of edge cases, performance, or usage boundaries. Adequate for a simple query but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but description provides clear parameter explanations ('JSON string to query', 'Dot-notation path (e.g. users.0.name)') with an example, adding meaning beyond the schema types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Query a JSON object using dot-notation path traversal', specifying the action (query) and resource (JSON object). The sibling tools include many text/JSON converters but no direct path query tool, so it stands out.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'process_json' or JSON conversion tools. Does not mention contexts or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry the burden. It mentions the formula but does not disclose behavior for edge cases (e.g., all zeros, negative values, underdetermined system). Missing return format or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Concise with one-line purpose and parameter list. No wasted words, though the bullet list could be integrated into a single paragraph for better flow.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple calculation tool, but lacks explanation of edge cases or response structure. Output schema exists, so return values are covered, but completeness is moderate given missing operational details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and description fully compensates by providing units (kg, m/s, J) and usage instructions (leave 0 if unknown) for each parameter, adding significant meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool calculates kinetic energy, mass, or velocity using the formula KE = ½mv², but does not differentiate from sibling physics calculators like force_calc or momentum_calc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage by instructing to leave unknown parameters as 0, but lacks explicit when-to-use or comparison with alternatives. No guidance on prerequisites or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It does not mention any assumptions, limitations, or output details (e.g., what constitutes 'metabolic age'). The output schema exists but the description doesn't reference it.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one line stating the purpose, followed by a clear parameter list. Every sentence earns its place, and there is no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema (context indicates it exists), the description provides enough to understand inputs and purpose. However, it lacks details about the output format, formula, or any edge cases, which would be helpful for complex usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context to all three parameters: it specifies units for bmr ('calories/day'), clarifies age as chronological, and defines sex options with a default. This adds value beyond the schema, which only has titles and types. Schema coverage is 0%, so the description compensates well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Compare BMR-based metabolic age to chronological age.' It uses a specific verb ('Compare') and identifies the resource ('BMR-based metabolic age' vs. 'chronological age'), which distinguishes it from sibling tools like bmr_calc or fitness_age_calc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention any prerequisites, restrictions, or scenarios where the tool is or isn't appropriate. For a calculation tool, this is a gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It explains the normalization forms and parameters but does not mention error handling (e.g., invalid form input), performance, or side effects. The behavior is straightforward, so it is minimally adequate. The description adds some value by listing allowed forms but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exceptionally concise: one sentence for purpose, followed by a list of parameters with clear labeling. No extraneous information. Every word serves a purpose, and the structure makes it easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema (not shown), the description covers the core operation and parameters adequately. It does not include examples or edge cases, but for a straightforward normalization tool, it is nearly complete. The low parameter count and high description coverage compensate for the missing schema descriptions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% parameter description coverage, so the description carries full burden. It clearly explains both parameters: 'text' as 'Text to normalize' and 'form' with default and allowed values. This adds significant meaning beyond the schema's property names and types, compensating well for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Normalize Unicode text to NFC, NFD, NFKC, or NFKD form.' The verb 'normalize' and specific resource 'Unicode text' are precise. However, it does not explicitly distinguish from sibling tools that also transform text (e.g., 'remove_accents', 'convert_case'), which prevents a score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. Given the extensive list of sibling text manipulation tools, explicit context such as 'Use when you need canonical Unicode normalization for comparison or storage' would be helpful. The description only states what it does, not when to apply it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states the basic check without disclosing whether it is case-sensitive, handles whitespace, or ignores punctuation, which are typical considerations for palindrome checking.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with one sentence and a parameter list. Every sentence is necessary and no redundant information is present.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the output schema exists and can describe the return type, the description lacks important behavioral details such as case sensitivity, whitespace handling, and exact output format. For a simple tool, this is borderline adequate but leaves ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explicitly defines the single parameter 'text' as 'Text to check for palindrome property.' This adds meaning beyond the schema, which only provides a title and type. However, it does not specify any constraints or formatting hints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks if text is a palindrome, with a specific verb and resource. It distinguishes from sibling tools like anagram_check and reverse_text by focusing on the palindrome property.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidelines on when to use this tool versus alternatives like checking for anagrams or reversing text. The description does not provide context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits like output structure, potential limitations, or required permissions. It only states what it does, not how it behaves or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two short sentences, front-loading the purpose and parameter explanation without extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the existence of an output schema, the description is adequate but lacks details about the output format (e.g., list of pros vs cons) or any limitations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The parameter 'text' is explained as 'Topic, product, or decision to analyze,' which adds semantic meaning beyond the schema's type definition. However, it does not specify any constraints like length or formatting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates structured pros and cons analysis from text or a topic. The verb 'generate' and resource 'pros and cons analysis' are specific and distinguish it from sibling tools like 'sentiment' or 'analyze_tone'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It does not mention context, prerequisites, or scenarios where another tool would be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It only explains parameter roles but fails to disclose key behaviors such as validation (exactly two non-zero inputs required), error handling for invalid inputs, or output format. This lack of behavioral context hinders correct invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loaded with the purpose, and presents parameters in a clear list format. Every sentence adds value without redundancy or unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple mathematical tool, the description provides basic input semantics but omits important details such as the requirement that exactly one side must be unknown and validation rules. With an output schema existing, the output format is not critical but missing constraints reduce completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description explicitly defines each parameter: 'a — Side a (leave 0 if unknown)', etc. This adds meaning beyond schema titles and defaults, effectively compensating for the lack of structured descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool solves the Pythagorean theorem to find a missing side of a right triangle, which is a specific and distinct purpose. It names the verb 'solve' and the resource 'Pythagorean theorem', and the parameter explanation differentiates it from other calculation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like geometry_calc or quadratic_solver. There is no mention of prerequisites, exclusions, or context for using the tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Explains the core logic (finding missing value) and parameter roles. Lacks disclosure on error handling or invalid inputs, but acceptable for a simple math tool given no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: one sentence for purpose followed by a clear parameter list. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Sufficient for a straightforward calculator with output schema. Missing details like rounding or result format, but covers the essential behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Adds meaningful descriptions for all four parameters beyond the schema (which has only titles). Clarifies that 'a' and 'b' are first ratio values, 'value' is the known value, and 'side' indicates which side it represents.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool solves ratio proportions (a:b = c:d). However, it does not differentiate from sibling 'proportion_calc' which likely has similar functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., proportion_calc). Does not mention prerequisites or edge cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It merely restates the calculation purpose without revealing assumptions (e.g., compounding frequency, rounding), edge cases, or limitations. This is insufficient for a financial calculation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence followed by a concise parameter list. Every element is necessary, and no information is wasted. It is structured effectively for quick scanning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists (though not shown in detail), the description does not need to explain return values. However, it omits mentioning the formula or assumptions (e.g., compound interest formula) and does not specify that the result is a monthly payment amount. It is minimally complete but could clarify the output semantics.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning beyond the schema by providing examples (e.g., 'Annual interest rate (e.g. 3.0 for 3%)') and clarifying default behavior ('initial savings amount (default: 0)'). Since schema description coverage is 0%, this addition is valuable.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description begins with 'Calculate monthly savings needed to reach a financial goal,' using a specific verb and resource. It clearly distinguishes this tool from many sibling financial calculators (e.g., loan_calculator, mortgage_calculator) by focusing on savings goals.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like compound_interest, loan_calculator, or investment_calculator. It does not mention scenarios where this tool is appropriate or should be avoided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It states 'Search the web' but fails to mention that this involves external HTTP requests, potential rate limits, latency, or error handling if an engine fails. There is no indication of the tool's impact on resources or any side effects beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise, consisting of a single sentence for the purpose followed by a bullet list of parameters. Each parameter is described in a single line. There is no redundant information, and the structure is clear and scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema (not described) and three parameters. The description covers the core functionality and parameter semantics but omits details about the return structure, pagination, error codes, or any usage constraints. Given that an output schema exists, the description could have been more complete by summarizing the response format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0% (no descriptions in the schema properties). The description compensates by listing each parameter with a brief explanation, including possible engine values and defaults. However, it does not add details beyond the schema's property names and defaults, such as constraints on 'count' (e.g., maximum) or format of 'query'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search the web using multiple engines', specifying the verb (search) and resource (web with multiple engines). It distinguishes from siblings by explicitly listing the engines and the 'auto' selection, implying a mult-engine capability not present in siblings like 'readability_url' or 'research_topic'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description lists parameter details (engines, default count) but offers no guidance on when to use this tool versus alternatives. It does not mention scenarios where a specific engine is preferred nor when not to use the tool. The sibling list contains many tools that might be used for related tasks, but no explicit comparison is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool sorts arrays but does not describe crucial aspects such as whether the input is mutated, error handling for invalid JSON, or the exact format of the sorted output. The lack of behavioral details limits the agent's understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting of a single sentence for the purpose and a bulleted list for parameters. Every part serves a clear function with no redundancy. It is efficiently structured for quick parsing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the description covers the basic purpose and parameters, it omits details about the return value format (though an output schema exists), potential errors (e.g., invalid JSON, non-sortable types), and whether the sort is stable. Given the tool's simplicity and the presence of an output schema, the description is minimally adequate but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides only types and defaults, with no property descriptions. The description adds meaningful context: 'data — JSON array to sort' clarifies the expected format, 'key — Sort key for objects. Empty for value arrays' explains conditional usage, and 'order — 'asc' (default) or 'desc'' enumerates valid values. This significantly aids agent comprehension beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Sort an array of values or objects.' It uses a specific verb (Sort) and specifies the resource (array of values or objects), which distinguishes it from sibling tools that might perform other operations on arrays.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention any exclusions, prerequisites, or scenarios where another tool would be more appropriate. The agent is left to infer usage from the function's name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral transparency. It describes the core function (generating a Soundex code) but omits details about input constraints (e.g., should 'text' be a single word?), output characteristics (string format, length), and any side effects or performance considerations. The description lacks sufficient behavioral context beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at 4 sentences, front-loading the main purpose, then usage context, then parameter details. Every sentence adds information without redundancy. It is well-organized and easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and an output schema, the description covers the essential aspects: what it does, when to use it, and what input to provide. However, it lacks detail on the output format (though the output schema exists, the description doesn't describe the return value). Given the low complexity, this is mostly complete but could include output format hints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter 'text' with no description. The tool description adds meaning by specifying 'the word to encode with Soundex', clarifying that the input should be a single word and indicating its purpose. This exceeds the bare schema information. Without schema descriptions, this added context is valuable.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates a Soundex phonetic code for a word and explicitly mentions its use in name matching and phonetic indexing. It distinguishes itself from siblings like nato_phonetic by focusing on encoding entire words for similarity rather than representing letters. However, it doesn't specify the output format (e.g., length 4), which slightly reduces clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear intended use case ('name matching and phonetic indexing') and explains that it's useful for finding similar-sounding names. However, it does not mention when not to use this tool nor discuss alternatives (e.g., levenshtein_distance for edit distance, nato_phonetic for letter-by-letter encoding). The guidance is present but basic.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden but only lists units and parameter names, omitting details like rounding, precision, handling of invalid units, or output format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a clear two-sentence overview and a parameter list, though it could be more structured (e.g., bolding or listing units inline).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and the existence of an output schema, the description covers essential aspects (purpose, units, parameters), though it lacks edge case handling or unit format clarification.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description adds meaning with brief parameter explanations ('Time value to convert', 'Source unit', 'Target unit'), but does not specify allowed unit values beyond the first line.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Convert between time units' and lists supported units, making the purpose specific and distinct from sibling conversion tools like 'angle_convert' or 'convert_units'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for time unit conversion but provides no explicit guidance on when to use this tool vs alternatives (e.g., 'convert_units' for general conversions) or any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the calculation and risk assessment but provides no details about behavior (e.g., is it read-only? what happens with invalid input?). It is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the main purpose. The parameter list is clear and every sentence is useful. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and 3 simple parameters, the description covers the essential points. It doesn't explain the risk assessment details but is sufficient for a basic calculator.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description adds meaning: waist/hip circumferences in cm, sex with default male. This clarifies parameter semantics beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates waist-to-hip ratio and health risk assessment, which is a specific verb+resource. It distinguishes from sibling tools like bmr_calc or body_fat_calc by focusing on this unique metric.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., other health calculators). The description lacks context about prerequisites or typical scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full burden. It does not disclose error handling, behavior with invalid XML, or limitations like namespace support. Only basic conversion is implied.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise with no extraneous words. The structure is efficient: a clear one-line purpose followed by a parameter list. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists, the description does not need return value details. However, the tool's simplicity means completeness is adequate but lacks edge case handling or notes on XML parsing rules.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides a brief explanation for the `xml` parameter ('XML content to convert'), which adds value over the schema's minimal title. However, it lacks details on expected format or encoding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the core function: converting XML text to structured JSON. It is specific and distinguishes from sibling tools like `json_to_xml` which does the reverse.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool over alternatives. The description only states the function without mentioning when it is appropriate or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It explains the calculations but lacks details on edge cases, limitations (e.g., text length, language), or output structure. Since it is a simple calculation, transparency is adequate but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: a single sentence for the action followed by a one-line parameter definition. No extraneous information, perfectly front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter and an output schema present. The description covers the core functionality. Minor missing context (e.g., language support, no side effects) but overall sufficient for a straightforward calculation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description adds 'Text to analyze for readability' for the 'text' parameter, which is a basic semantic improvement over the schema title alone. However, it provides no additional constraints or formatting details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Calculate Flesch-Kincaid readability score, grade level, and reading ease', providing a specific verb and resource. It clearly distinguishes itself from sibling readability tools like 'fry_readability' or 'gunning_fog_score' by naming the exact formula.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Given the large number of sibling readability tools, explicit context for selection is missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full behavioral burden. It only states basic conversion and lists parameters, but does not disclose input validation, error handling, or behavior for invalid units. For a simple tool, this is minimal but still lacks important operational details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: a single sentence for purpose followed by a bullet list of parameters. Every sentence adds value, and the structure is front-loaded with the main action. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity of a simple conversion tool with 3 required parameters and an existing output schema, the description covers the primary action and parameter roles. It is mostly complete, though it could be enhanced by listing allowed unit values or mentioning edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must explain parameters. It provides brief explanations (e.g., 'Angle value', 'Source unit', 'Target unit'), which add some meaning beyond the schema's property names. However, it does not specify acceptable values for from_unit and to_unit (e.g., the actual strings allowed), which is critical for a unit conversion tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Convert' and the resource 'angle units', and lists the specific units supported (degrees, radians, gradians, arcminutes, arcseconds). This distinguishes it from sibling converter tools like area_convert or temperature_all.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for angle unit conversion but does not provide explicit guidance on when to use this tool versus a general converter like convert_units, nor does it mention any exclusions or alternatives. The context is clear but lacks comparative direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It does not disclose behavior for invalid units, edge cases, or side effects. For a simple conversion, this is minimal but acceptable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short, clear sentences in the first paragraph and a bulleted list of parameters. No unnecessary information, front-loaded with purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers the basic operation and lists supported units. Could be improved by mentioning the output format, but output schema exists. Good for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning beyond the schema by labeling each parameter's role: 'value — Area value to convert', 'from_unit — Source unit', 'to_unit — Target unit'. This is helpful given 0% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Convert between area units' and lists specific units (sq m, sq ft, etc.), which differentiates it from other conversion tools among siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'convert_units' or 'volume_convert'. There is no mention of when not to use it or which scenarios it is best suited for.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility for disclosing behavior. It mentions conversion to human-readable format with listed units, but omits important details such as whether binary (1024-based) or decimal (1000-based) units are used, how negative numbers or zero are handled, and the impact of the precision parameter on rounding. These gaps reduce transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, with a one-sentence summary followed by parameter definitions. However, the parameter explanations could be integrated into the main description for better flow, and the bullet list formatting is acceptable but not optimal.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (two parameters, no nested objects, output schema exists), the description covers the core functionality adequately. It lacks edge-case details but is sufficient for a straightforward conversion tool. The presence of an output schema means return values are already documented elsewhere.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description compensates for zero schema coverage by clearly explaining both parameters: 'bytes' (Number of bytes) and 'precision' (Decimal places, default: 2). This adds meaningful context beyond the schema's type-only information, making the parameters self-explanatory.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: converting bytes to human-readable format, specifying exact units (B, KB, MB, GB, TB, PB). This is a specific verb ('Convert') with a well-defined resource ('bytes'), and it distinguishes itself from sibling conversion tools by focusing solely on byte formatting.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For example, there are sibling tools like 'convert_units' or 'data_rate_convert' that might handle similar conversions. The description does not mention any prerequisites, limitations, or when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It does not explain how 'closest' is determined (e.g., Euclidean distance in some color space), what happens if no close match exists, or any limitations. The behavior is opaque.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief (two sentences) and front-loaded with the purpose. Every sentence is necessary and no redundant information is present.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is mostly complete. However, it could have briefly mentioned the output type (e.g., 'Returns the color name and possibly hex') to improve clarity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides only the parameter name and type, with no description. The description adds crucial semantic information: 'Hex color without # (e.g. '3498db')', clarifying format and providing an example. This compensates for the 0% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Find the closest named CSS color for a given hex value', which specifies the verb (find), resource (closest named CSS color), and input (hex value). This distinguishes it from sibling color tools like color_mix or color_harmony.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many color-related sibling tools, users need context on when to search for a named color vs. mixing or generating palettes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only lists conversion and parameters, omitting details like rounding, error handling, or case sensitivity for unit strings. For a simple conversion, the behavior is somewhat predictable, but the description lacks transparency about return format or validation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at three lines, front-loading the purpose and listing units and parameters. Every sentence earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple conversion tool with an output schema (present but not detailed), the description covers the essential purpose and parameters. It lacks details on return values or error cases, but the tool's low complexity reduces the need. Completeness is adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides brief meanings for each parameter (e.g., 'value — Data rate value'), adding basic semantics beyond the schema titles. However, it does not specify valid unit strings or value constraints, limiting its helpfulness.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Convert between data transfer rate units' with specific verb and resource. It lists the supported units (bps, Kbps, Mbps, Gbps, Tbps), making the purpose unambiguous. This distinguishes it from sibling conversion tools like 'convert_units' or 'speed_convert'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when or when not to use this tool. The description implies usage for data rate conversions but doesn't differentiate from the general 'convert_units' tool or set expectations for input formats. Context is implied by the tool name, not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must cover behavioral traits. It mentions the basic behavior of removing duplicates and the role of the key, but omits details such as whether the operation is destructive, handling of non-array inputs, or the deduplication algorithm. This is minimally informative.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, using two sentences and a parameter list. The parameter explanations are integrated rather than a separate section, which is efficient. However, the phrasing 'Parameters: data — ...' is slightly informal and could be more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, the description provides the core functionality but is incomplete. It does not address error handling, performance, or edge cases like non-object elements when a key is provided. The existence of an output schema compensates partially, but the description alone is minimally sufficient for a simple deduplication tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning beyond the schema by explaining that 'data' is a JSON array and 'key' is used for object deduplication, with an empty key defaulting to value comparisons. While helpful, it could clarify data format expectations (e.g., JSON string vs array) and key behavior for edge cases.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Remove duplicate entries from an array', using a clear verb+resource structure. Among many sibling tools like 'sort_data' or 'filter_data', it is distinctly about deduplication, making its purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage scenarios by distinguishing between value deduplication (no key) and object deduplication (with key). However, it does not explicitly state when to use this tool over alternatives or mention when not to use it, leaving the guidance somewhat implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description implies a simple deterministic computation with no side effects, which is sufficient for such a tool. However, since no annotations exist, a brief note on the return type or behavior could improve transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting of a single clear sentence followed by a bullet-point style parameter list. Every word adds value, and the structure is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with four numeric parameters and an output schema, the description is complete. It covers the function and parameter semantics adequately, leaving no critical gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning beyond the schema by labeling parameters as X/Y coordinates of the first and second points. This compensates for the 0% schema description coverage and clarifies the role of each parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates Euclidean distance between two points in 2D space, using a specific verb and resource. However, it does not distinguish itself from sibling tools like 'calculate_distance' or 'pythagorean_calc', which could cause confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of use cases or when not to use it, leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must cover behavioral traits. It mentions that records are returned 'when available', which adds some context. However, it does not disclose error handling (e.g., non-existent domain) or any side effects. Given the read-only nature, the transparency is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, with three sentences covering purpose, usage, and return types, followed by parameter details. No wasted words, and the essential information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, output schema exists), the description is mostly complete. It explains what it does, when to use it, what records are returned, and the parameter. However, it could mention error handling or differentiation from 'dns_lookup' for full completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one parameter 'domain' with 0% description coverage. The description adds a usage example and clarifies it is a domain name. This adds value beyond the schema but does not provide constraints or validation details. Baseline is 3 due to low schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool looks up DNS records for a domain and lists specific record types (A, AAAA, MX, NS, TXT, CNAME). It is distinct from many siblings but does not explicitly differentiate from 'dns_lookup', which may be similar.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description advises when to use the tool ('Use this to find what DNS records a domain has'), but does not mention when not to use it or provide alternatives among sibling tools like 'dns_lookup'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the full burden of behavioral disclosure. It fails to describe key behaviors such as how multiple parameters interact (e.g., if both last_period and conception are provided), what happens with missing inputs, or what specific milestones are returned. The description is minimal and lacks transparency beyond parameter descriptions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: a single sentence summarizing the purpose followed by a bullet list of parameters. Every sentence is necessary, and the structure is clear and easy to scan. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 parameters, no required fields, output schema exists), the description is mostly sufficient. It defines inputs clearly. However, it could be improved by noting that the due date calculation follows a standard rule (e.g., Naegele's rule) or by mentioning the return structure. Despite this, the presence of an output schema partially reduces the need for return value documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides brief explanations for each parameter (e.g., 'First day of last menstrual period (ISO date)'), adding meaning beyond the schema's titles and types. However, the explanations are minimal and lack detail on formatting constraints or edge cases.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates 'estimated due date and pregnancy milestones,' which is a specific verb+resource. It is distinct from sibling tools like ovulation_calc or calculate_age, as it focuses on pregnancy due dates and milestones.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives. However, the parameter list and title imply its use for pregnancy due dates, providing implied context but no exclusion criteria or alternative suggestions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It states what the tool checks (validity, reachability, disposability) but does not disclose whether it makes network calls, has rate limits, or other behavioral traits. The description lacks detail on operational behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: one sentence for purpose and a bullet-like parameter description. No wasted words; every part earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and an output schema (not shown), the description is nearly complete. It covers purpose and parameter usage. However, it misses guidance on when to use versus similar tools like verify_email, leaving a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only one parameter (email) with schema description coverage 0%. Description adds valuable context by providing the parameter purpose and an example format ('user@example.com'), going beyond the schema's type definition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description uses specific verb 'check' and clearly defines the resource 'email domain' with three distinct aspects: validity, reachability, and disposability. This goes beyond the tool's name, avoiding tautology and distinguishing it from sibling tools like verify_email.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. Despite many sibling tools (e.g., verify_email), the description does not mention when to prefer this over others or any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not mention any behavioral traits such as limitations, error handling, or performance characteristics. It only describes core function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, then parameter. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a single parameter and existence of an output schema, the description is largely complete. It could mention entity formats but is adequate for agent invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. It provides a brief but clear meaning for the 'text' parameter: 'Text to extract entities from.' Sufficient for a single simple parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool extracts named entities (people, places, orgs, dates) from text, using a specific verb and resource. It distinguishes from siblings like extract_contacts by specifying entity types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use or when not to use this tool versus alternatives. Sibling tools like extract_contacts or sentiment exist but no comparison is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It mentions parameters and defaults but does not specify what defines a 'word,' how punctuation is handled, or the output format. This leaves gaps for the agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences plus a parameter list. Every word serves a purpose, and the structure is front-loaded with the primary action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 parameters, no nested objects) and the existence of an output schema, the description adequately covers the core functionality and parameter meanings. It could mention word definition rules, but overall it is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds clear, human-readable explanations for both parameters (e.g., 'Text to search for short words' and 'Maximum word length (default: 3)'). This surpasses the minimal schema labels.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Find words shorter than a specified length.' It uses a specific verb-resource pair and distinguishes from the sibling tool find_long_words.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when or when not to use this tool vs alternatives like find_long_words. The description is minimal and does not help the agent decide context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It describes input and output but does not disclose behavioral traits such as whether the checklist is deterministic, its format, or any side effects. Lacks transparency about how the checklist is generated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief with two sentences: one for purpose and one for parameters. The parameter list is short and clear. It is front-loaded with the purpose, but the parameter section could be more integrated.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the single parameter and the existence of an output schema (not shown), the description is adequate but minimal. It does not explain what constitutes a 'step-by-step checklist' or the output format, leaving some ambiguity for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds meaning by stating the parameter 'text' is a 'Process or task description to create a checklist from', clarifying its purpose. However, no additional constraints or examples are provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates a step-by-step checklist from a process or task description, using a specific verb and resource. This distinguishes it from sibling tools that generate other outputs like hashtags or passwords.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for process/task descriptions but does not provide explicit guidance on when to use this tool versus alternatives (e.g., explain, summarize). No exclusion criteria or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the full burden of behavioral disclosure. It only states 'Create a compelling elevator pitch', without revealing generative AI involvement, potential length limits, or any constraints. This lack of detail forces the agent to infer behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—two sentences with no wasted words. The purpose is front-loaded, and the parameter definition is immediately clear. Every part earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (single input, existing output schema), the description is largely complete. It defines the input purpose and matches the expected output of an elevator pitch. Minor gaps like clarifying 'elevator pitch' length are acceptable given the schema covers output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although schema coverage is 0%, the description adds significant value by defining the 'text' parameter as 'Product, service, or business description.' This goes beyond the schema's bare 'string' type and clarifies the expected input content.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool creates an 'elevator pitch' from a product or business description. This verb-noun combination is specific and distinguishes it from sibling tools like generate_slogan or generate_tagline, which produce different types of content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description does not mention contexts where this tool is preferred, exclusions, or related tools such as generate_slogan or generate_tagline that might serve similar purposes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It implies making requests but does not disclose potential side effects, authentication needs, rate limits, or error responses. Only mentions method support and header syntax.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise: single paragraph with clear purpose sentence followed by parameter list. No unnecessary words, front-loaded with key action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given output schema exists, return values are covered. However, lacks details on error handling, timeouts, or idempotency. Adequate for a simple HTTP client but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must explain parameters. It does so thoroughly: url as required full URL, method with defaults and allowed values, headers with optional JSON string and example. Adds significant meaning beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: making arbitrary HTTP requests from the API hub, listing supported methods. It implicitly distinguishes from sibling tools like http_headers or read_url by being a general-purpose client, but does not explicitly differentiate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides a use case ('when you need to call a URL but don't have direct HTTP access'), but no exclusions or comparisons to alternatives. Lacks guidance on when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description is straightforward and accurately describes the transformation. However, with no annotations, it relies entirely on the description for behavioral traits. It does not mention how non-alphabetic characters are handled, but the core behavior is clear. A score of 3 reflects that it is adequate but could be more explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences that front-load the key information. Every word adds value; there is no fluff. The structure is efficient for an AI agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple text transformation tool with an output schema, the description covers the essential transformation logic. It does not elaborate on edge cases (e.g., empty string, numbers) but given the tool's simplicity and the presence of an output schema, it is largely complete. A score of 4 acknowledges minor gaps like lacking a note on non-alphabetic characters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage for the parameter, so the description must compensate. It adds a brief description ('Text to invert case of') which clarifies the parameter's purpose. This is minimal but sufficient for a simple string parameter; a more detailed example or constraint could improve it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (invert case) and the resource (each character), with a specific definition (upper->lower, lower->upper). It is precise and leaves no ambiguity about what the tool does, distinguishing it from siblings like 'alternating_case' or 'capitalize_text' despite not explicitly naming alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus similar case transformation tools (e.g., 'swap_case', 'convert_case', 'alternating_case'). The agent has no context to differentiate its use case, which is important given the many siblings in this domain.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states the output includes hex and RGB but does not disclose sorting, limits, or any edge cases. For a list tool, more behavioral context would be helpful.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one sentence plus a note about no parameters. Every word earns its place, and there is no fluff. Front-loads the main purpose immediately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool is simple (0 params, output schema exists), the description is mostly complete. It mentions the output includes hex and RGB, but could optionally list sample output or number of colors. Nonetheless, it conveys the essential information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so the description correctly notes that no parameters are needed. Schema coverage is 100%, and the description adds no extra parameter info, which is appropriate. Baseline for 0 params is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a list of named CSS colors with hex values and RGB components. It distinguishes itself from sibling tools like 'color_named' (likely just names) and 'hex_to_rgb' (conversion) by specifying both name and values.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It does not mention any siblings or when not to use it, leaving the agent to infer from context alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must cover behavioral traits. It only states what the tool returns but does not disclose anything about caching, rate limits, authentication, or output format details. The presence of an output schema partially compensates, but the description lacks behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences covering purpose and parameter note. No filler or redundant information. It is well-structured and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters, output schema exists), the description is largely sufficient. However, it could be improved by providing context about when to use this listing tool versus other language-related tools, or by noting the source of the language list.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, and schema coverage is 100%. The description explicitly notes 'no parameters needed,' which is clear. For zero-parameter tools, a baseline of 4 is appropriate, and the description adds no unnecessary detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get a list of all languages with ISO codes and native names.' It uses a specific verb and resource, and is distinct from sibling tools like 'detect_language' or 'list_countries'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not mention when to use this tool over alternatives, nor does it specify prerequisites or limitations. Given the context of many sibling tools, this is a significant gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It correctly implies a safe read-only calculation, but does not disclose edge cases, precision, or the fact that it returns both margin and markup. The behavior is adequately implied for a simple calculator.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the purpose, followed by parameter descriptions. It wastes no words, but the parameter list format is minimal and lacks explanations for potential questions (e.g., currency, units).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool is simple, the description does not specify the return format (e.g., returns object with margin and markup percentages). An output schema exists but is not shown, and the description does not compensate. Given the simplicity, the gap is moderate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, but the description adds meaning: 'cost — Cost of goods sold' and 'revenue — Total revenue'. This goes beyond the schema titles, clarifying the domain context. However, the schema titles are already fairly clear, so the added value is moderate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates 'profit margin percentage and markup' from 'cost and revenue', using specific verbs and resources. This distinguishes it from sibling tools like 'markup_calc' and 'percentage_calculator'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. For example, it doesn't indicate whether it handles negative costs or revenues.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description carries full burden. Only states basic calculation, no details on edge cases, rounding, negative values, or error handling. Output schema may help but description adds minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Concise two-sentence purpose followed by parameter bullets. No wasted words, front-loaded with main function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple math tool with 2 parameters and output schema, the description is nearly complete. Could include formula or constraints, but adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description adds essential meaning: 'Cost of goods sold' and 'Markup percentage (e.g. 50 for 50%)' clarifies that markup_percent is a percentage, not decimal.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates selling price from cost and markup percentage with specific verb and resource. It distinguishes from other pricing tools like margin_calc by specifying markup percentage.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. No mention of scenarios, prerequisites, or when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions merging with two strategies but does not disclose critical behaviors like conflict resolution (overwrite vs combine), error handling for invalid JSON, or the structure of the output. With no annotation support, the description is insufficiently transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences plus a list for parameters. The purpose is front-loaded, and the parameter list is clear. However, the parameter list could be integrated into a more flowing narrative without losing clarity. Overall, it is efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 3 parameters and an output schema (not shown). The description covers the parameters adequately but omits any description of the return value. For a simple tool, this might be acceptable, but the lack of information about the output format or potential errors leaves the agent uncertain about what to expect. It is minimally complete for the given complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides meaningful definitions for all three parameters: json_a and json_b are described as 'First JSON string' and 'Second JSON string', and strategy is explained as 'deep (default) or shallow'. This adds value beyond the bare schema, though it could include format expectations (e.g., valid JSON must be keys in double quotes).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool merges two JSON objects with a choice of deep or shallow strategy. The verb 'merge' and resource 'JSON objects' are specific, and the distinction between deep and shallow differentiates it from similar siblings like 'flatten_json' or 'unflatten_json'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly provide guidance on when to use this tool versus alternatives or when to choose deep vs shallow strategy. The purpose is implied through the parameter descriptions, but there is no contextual 'when-to-use' or 'when-not-to-use' information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It describes the operation as a simple calculation with no side effects, but does not disclose any behavioral traits like error handling, permissions, or rate limits. For a straightforward math tool, this is adequate but lacks additional depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, with a one-line summary followed by a list of parameters. However, repeating parameter documentation in the description slightly reduces conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The output schema exists, so the description does not need to explain return values. However, the description could mention the output format briefly for clarity. It is complete enough for a simple tool but lacks mention of edge cases or result structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds parameter descriptions (e.g., 'x1 — X coordinate of first point.') that are not present in the schema (0% schema description coverage). This provides clear meaning beyond the parameter names and types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Calculate the midpoint between two points in 2D space.' This is a specific verb-resource combination, accurately describing the tool's function and distinguishing it from sibling tools like 'calculate_distance' or 'slope_calc'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives. It does not mention when not to use it or provide context for selection among similar calculation tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states the calculation purpose but does not disclose behavioral details such as the return format, assumptions (e.g., typical ovulation day 14), or any limitations. The output schema exists but the description should add context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and to the point, but it includes a parameter list that could be integrated more naturally. Still, every sentence adds value, and it is front-loaded with the purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema and only 2 simple parameters, the description provides adequate context for an AI agent to use the tool. However, it could mention that the calculation uses the typical 14-day luteal phase assumption to fully set expectations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It explains both parameters: last_period as 'First day of last menstrual period (ISO date)' and cycle_days as 'Average cycle length in days (default: 28).' This adds meaningful semantics beyond the schema's type and default.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Calculate ovulation window and fertile days.' The verb 'calculate' and resource 'ovulation window and fertile days' are specific and distinct from sibling tools like calculate_bmi or due_date_calc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description lists parameters and their meanings, implying the tool is used when one has last period date and cycle length. However, it does not explicitly state when to use versus alternatives (e.g., due_date_calc) or provide exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It only states the purpose; it does not mention the return type (likely boolean), edge cases (e.g., empty text), or performance considerations. The output schema exists but is not referenced.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences plus a parameter listing. No unnecessary words. The purpose is front-loaded, and the parameter is clearly separated.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (boolean check on text) and the presence of an output schema, the description is nearly complete. It could mention that the tool returns a boolean, but this is minor. The description works for an agent to understand the core functionality.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It lists the parameter 'text' with a brief description ('Text to check for pangram property'). This adds basic meaning but lacks details like expected encoding, case sensitivity, or maximum length.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: checking if text is a pangram (contains every letter of the alphabet). The verb 'check' and the specific resource 'pangram' make it distinct from sibling tools like palindrome_check or anagram_check.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for pangram checking but provides no explicit guidance on when to use this tool versus alternatives (e.g., other text analysis tools). No 'when not to use' or alternative tools are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden. It states the tool estimates reading time but does not disclose the output format, units (e.g., minutes, seconds), or whether it handles edge cases like empty text. This is minimal transparency for a simple computation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one sentence stating the purpose followed by a clean parameter list. It is front-loaded with the core action, and every part is informative without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 parameters, no nested objects), the description covers the essential functionality and parameters. An output schema exists, so explaining return values is not required. The description could mention the unit of the result (likely minutes) for completeness, but it is sufficient for an AI agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description is the sole source for parameter meaning. It clearly explains 'text' as the content to estimate and 'wpm' as the reading speed with a default. This adds necessary context beyond the schema property names alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('estimate') and the resource ('reading time for text') with the specific parameter 'at a given words-per-minute rate'. It effectively distinguishes from sibling tools like 'speaking_time' which deals with speech, and other text analysis tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. Given the presence of 'speaking_time' and other text analysis tools, the description does not mention when to prefer reading_time or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only states 'Calculate', implying a read-only operation. There is no disclosure of rate limits, authentication needs, or error behavior. For a calculation tool, it could be more transparent about assumptions or limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the purpose, followed by a parameter list. Every sentence adds value with no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema and the tool's relatively low complexity, the description sufficiently covers the calculation and parameters. It does not explain return values, but the output schema likely handles that.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds comments to each parameter (e.g., 'income — Annual taxable income'), which enriches understanding beyond the schema's titles. However, it lacks constraints like income positivity or country enum values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Calculate' and the specific resources: tax bracket, effective rate, and take-home pay. It distinguishes itself from siblings like 'salary_breakdown' by focusing on tax brackets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives (e.g., salary_breakdown), nor does it mention when not to use it or any prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries full burden. It does not disclose any behavioral traits beyond what it does, such as whether it makes network requests or has side effects. For a read-only parsing operation, it is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with one sentence for purpose and one sentence for parameter. No unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter and an output schema. The description covers the essential purpose and parameter. It could mention the output schema's role, but that is not required.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, but the description compensates by explaining the 'url' parameter with a concrete example. This adds meaning beyond the schema's type and required status.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Parse' and the resource 'URL into its components', listing specific components (protocol, host, path, query, fragment). This distinguishes it from sibling tools like analyze_url or url_encode_decode.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool vs alternatives. It does not mention when not to use it or suggest other tools for different URL operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose key behavioral details such as case sensitivity, whitespace handling, or punctuation treatment. This leaves the agent unaware of important nuances beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: a single sentence outlining the purpose followed by a lean parameter list. No extraneous information is present, and the critical purpose is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool, the description covers the basic purpose and parameters, but it omits important context like whether the comparison is case-insensitive or how whitespace is handled. An output schema exists but is not referenced in the description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema lacks descriptions for parameters, but the tool's description explicitly lists and describes each parameter ('text_a — First text to compare', 'text_b — Second text to compare'), effectively compensating for the missing schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: checking if two texts are anagrams. The verb 'check' and the specific concept 'anagrams' make the function unambiguous and distinguish it from other text comparison tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool (when anagram verification is needed) but does not explicitly guide when to use it over alternatives like 'palindrome_check' or 'levenshtein_distance'. No exclusions or context are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It mentions checking contrast ratio but does not specify whether it returns a ratio or pass/fail, or if it adheres to specific WCAG levels like AA/AAA. Important behavioral details are missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise with two short sentences and a clear parameter list. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description does not need to detail return values. However, it lacks context about WCAG level compliance or additional accessibility details, which would be helpful for an agent to fully understand the tool's scope.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, leaving the description to explain parameters. It adds meaning by specifying that colors are hex without the '#' symbol, which the schema only indicates as strings. This compensates well for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks WCAG contrast ratio between two colors for accessibility, using specific verbs and resource. It distinguishes itself from sibling tools like color_mix or color_harmony.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a clear purpose but does not explicitly state when to use this tool versus alternatives like other color tools or when not to use it. No guidance on context or exclusions is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It only states the basic conversion action without disclosing edge cases (e.g., handling of digits, special characters, or non-ASCII text). For a simple tool, this is a moderate gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and to the point, with a clear introductory sentence followed by parameter documentation. It is efficient, though slightly redundant by repeating parameter names in the list.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists (though not shown), the description does not need to explain return values. It covers the essential input details and behavior. However, it could mention output format or error handling for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description compensates by listing both parameters ('text' and 'style') with brief explanations and enumerates the valid values for 'style'. This adds significant meaning beyond the schema fields.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'convert' and the resource 'text', and specifies the target case styles (camelCase, PascalCase, snake_case, etc.). This differentiates it from siblings like 'swap_case' or 'invert_case' by naming specific case conventions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for general case conversion but does not explicitly state when to use this tool versus siblings like 'swap_case', 'title_case', or 'alternating_case'. No exclusions or alternative recommendations are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It only states the action and parameters, lacking any disclosure of side effects, error handling (e.g., division by zero), or performance characteristics. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: one sentence plus a bullet-like parameter list. Every piece is meaningful, no fluff. Front-loaded with purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, return values are covered. The description covers operation and parameters well. However, it misses critical constraints like denominator != 0, which is essential for correct use. Slightly incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema coverage (no descriptions in JSON schema properties), the tool description provides clear explanations for all 5 parameters, including allowed values for 'operation' and defaults for optional ones. This fully compensates for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs arithmetic operations on fractions (add, subtract, multiply, divide). The verb 'Perform' and resource 'arithmetic operations on fractions' are specific, and the listed operations distinguish it from siblings like geometry_calc or general math tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. It does not mention any context, prerequisites, or when not to use it. With many math-related siblings (e.g., evaluate_math, quadratic_solver), this is a gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It merely states the calculation purpose without explaining data sources, accuracy, or any side effects. For a simple calculator, this might suffice, but it lacks necessary transparency for agents to understand reliability or dependencies.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one sentence for purpose plus a structured parameter list. Every line contributes value without redundancy, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the parameters well but does not explain the return format or any limitations (e.g., year ranges, inflation data sources). However, since an output schema exists, the agent can infer return structure. For a simple calculator, this is moderately complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds significant meaning by listing each parameter with a brief explanation and example values for years and country codes. This helps agents understand the expected input beyond the schema's bare types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a clear verb-resource pair: 'Calculate the inflation-adjusted value of money over time.' This immediately conveys the tool's primary function and distinguishes it from sibling tools like amortization_calc or compound_interest, which serve different financial calculations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides parameters and defaults, which implicitly guides usage, but it does not explicitly state when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions. For a straightforward calculator, this is adequate but not exemplary.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations; description lacks details on compound frequency, whether result is future value, or assumptions. Minimal beyond parameter names and basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Concise with bulleted parameter list, front-loaded main purpose. No fluff, but could be slightly more structured with outcome description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers inputs and basic function; output schema exists so return shape is documented. Lacks assumptions (e.g., compounding frequency), but sufficient for use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but description adds clear, helpful definitions for each parameter (e.g., 'rate — Expected annual return rate (e.g. 7.0 for 7%)'), which compensates well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it calculates investment growth using compound interest with optional monthly contributions. Distinguishes from compound_interest and loan/mortgage calculators.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage for investment growth calculations but provides no explicit when-to-use or when-not-to-use guidance compared to sibling tools like compound_interest or simple_interest_calc.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries full burden. It discloses the purpose and parameter values but does not mention any behavioral traits such as idempotency, caching, error handling, or required network access. The description is lacking in this dimension.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a single clear sentence followed by a parameter list. It is well-structured and front-loaded, though the parameter list could be integrated more seamlessly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and an output schema, the description provides the necessary information: purpose and allowed parameter values. It could elaborate on what the output contains, but it is largely complete given the tool's scope.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema only shows the 'layout' parameter with a default but no enum values. The description adds meaningful detail by listing allowed layout values: 'us', 'uk', 'de', 'fr', 'es', 'it'. This compensates for the 0% schema description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Get keyboard layout reference showing key positions and characters.' The verb 'Get' and resource 'keyboard layout reference' are specific, and no sibling tool appears to have similar functionality, distinguishing it well.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance is provided. The description implies usage for retrieving keyboard layouts, but it does not address alternatives or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the transformation (removing whitespace and comments) but does not mention edge cases, error handling, or limitations (e.g., malformed CSS handling). The basic behavior is clear but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two front-loaded sentences: the first states the purpose, and the second describes the parameter. No superfluous words or repetition. It earns its place efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, output schema exists), the description covers the core action and parameter. However, it lacks usage context, such as prerequisites or when to choose this over other minification tools. The presence of an output schema reduces the need to describe return values, but the overall completeness is adequate but not excellent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds meaningful context by listing the parameter as 'css — CSS content to minify,' clarifying what the single required parameter expects. This provides sufficient semantics for the agent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Minify CSS by removing whitespace and comments,' specifying the exact verb and resource. It distinguishes itself from sibling tools like 'code_minify_js' and 'minify_html' by explicitly targeting CSS.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, such as when minifying other code types like JavaScript or HTML. The description lacks explicit contexts, exclusions, or alternative tool mentions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description carries burden. It instructs to leave unknown as 0, implying two knowns needed. However, doesn't specify behavior for invalid inputs (e.g., all zero, all non-zero) or return format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences, front-loaded with formula, no wasted words. Each sentence adds essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple tool with output schema, but lacks details on error handling and exact computation behavior. Could specify how exactly it selects which variable to compute.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage; description adds units (N, m², Pa) and usage hint (leave 0 if unknown), which is valuable beyond type information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states it calculates pressure, force, or area using P = F/A, with clear verb and resource. It distinguishes from sibling tools like force_calc and pressure_convert by covering all three variables.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this vs alternatives. No when-not or context provided. Implicitly it's for physics calculations, but no explicit direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adequately explains that the tool processes JSON strings and the modes affect output. However, it does not disclose error handling (e.g., what happens with invalid JSON in minify mode) or return format. With no annotations, more detail on behavior would be beneficial.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a single introductory line followed by a clear, parameter list. It is front-loaded with purpose and uses minimal words effectively.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description covers purpose, parameters, and use cases adequately. Minor omissions like input size limits or return value details are not critical but could be added.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema itself has no parameter descriptions (0% coverage), so the description compensates well by explaining that 'json_string' requires raw JSON text and listing the three mode options with defaults. This adds significant meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states three specific operations (prettify, validate, minify) and lists concrete use cases like debugging and formatting. However, it does not explicitly differentiate from sibling tools such as 'validate_json' or 'code_beautify', which may overlap.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context by listing appropriate use cases, but it does not offer when-not-to-use guidance or mention alternatives. No explicit exclusions are given, which would help the agent avoid misuse.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description bears full burden. It discloses that the tool transforms text via letter rotation and allows custom shift. However, it does not mention case handling, non-alphabetic character behavior, or edge cases, leaving some ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exceptionally concise—two sentences plus a bulleted parameter list—with no unnecessary words. The purpose is front-loaded, making it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of a likely output schema, the description is adequate. However, it omits mention of case preservation and non-letter handling, which would be helpful for a complete understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description lists parameters with brief explanations: 'Text to transform' and 'Rotation amount (default: 13)'. This adds meaning beyond parameter names, though more detail (e.g., alphabetic-only operation) would improve clarity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Apply ROT13 or custom ROT-N cipher (letter rotation)', specifying the verb (apply), resource (cipher), and variant (ROT13 vs custom). This effectively distinguishes it from sibling tools like caesar_cipher and atbash_cipher.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for letter rotation ciphers but lacks explicit guidance on when to use this tool versus alternatives like caesar_cipher. No when-not-to-use or exclusion criteria are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only gives the formula without disclosing any behavioral traits such as rounding, precision, or error handling. It does not add value beyond the basic calculation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a clear formula and parameter list. It is front-loaded with the purpose. However, it could be better structured, e.g., separating the formula from parameter descriptions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema (not shown but indicated), the description adequately covers the input parameters. It does not need to explain return values. Some additional behavioral context would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context to each parameter: 'Annual interest rate (e.g. 5.0 for 5%)' and 'Time period in years'. With 0% schema description coverage, this compensation is good, though more detail on units or constraints could be added.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the purpose: 'Calculate simple interest' with the formula provided. It distinguishes itself from sibling tools like compound_interest and amortization_calc implicitly by specifying the simple interest calculation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like compound interest or loan calculators. The description implies its use for basic interest calculation but does not mention exclusions or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states 'Powered by AI — no scraping needed,' implying external service usage but not detailing implications like rate limits, data handling, or URL accessibility. It does not disclose any destructive or side effects. The description covers basic behavioral traits but lacks depth for a tool that processes external URLs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two paragraphs and a parameter line, front-loading the purpose and output. It is concise with no wasted words. Every sentence adds value. Slightly longer than strictly necessary due to the parameter documentation inline, but still efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has only one parameter and an output schema exists, the description covers the core functionality and return values adequately. It lists specific output fields. However, it lacks mention of edge cases like invalid URLs, non-HTML pages, or performance considerations, but these are somewhat mitigated by the output schema's existence.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'url' is described with a format hint ('e.g. "https://example.com/page"') and the requirement that it is a full URL. Though schema coverage is 0%, the description compensates by explaining the parameter beyond the schema's type string. The example adds practical guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool analyzes a URL and returns a structured summary with specific output fields (title, summary, key points, topics, sentiment, reading time). It uses the specific verb 'analyze' and resource 'URL'. While it mentions 'no scraping needed' to differentiate, it does not explicitly compare to closely related siblings like 'read_url' or 'scrape_meta_tags', so a 4 is appropriate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use: 'Use this to understand what a web page is about without reading it.' This provides clear context. However, it does not mention when not to use or suggest alternatives, which would strengthen the guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so description carries full burden. It uses 'Estimate' to indicate approximation, which is good, but lacks disclosure of limitations (e.g., not for legal accuracy) or error handling. Parameter listing adds some transparency but not beyond schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Description is short and front-loaded with purpose. The parameter list is efficient, but the structure could be slightly improved (e.g., separating parameter descriptions more clearly). No redundant content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (context signal), description does not need to detail return values, but it fails to specify BAC units (e.g., g/dL) or mention edge cases (e.g., zero weight). Adequate for a simple calculator but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so description compensates by providing units ('kg', 'hours') and clarifying 'standard drinks' and drink type options. This adds meaning beyond schema titles and defaults, though no formula assumptions are given.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Estimate blood alcohol content (BAC) level' using a specific verb and resource. It distinguishes itself from sibling calculator tools (e.g., bmi_calc, body_fat_calc) by focusing on BAC estimation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage (when BAC estimation is needed) but does not provide explicit when-to-use or when-not-to-use guidance. No alternatives are mentioned, which is acceptable given no direct sibling competitors.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral transparency. It does not disclose whether the tool is read-only, what it modifies, or any side effects. The calculation nature is obvious, but the description lacks explicit behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: a single sentence stating purpose and method, followed by a parameter list. Every sentence is necessary and front-loaded with the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description appropriately omits return value details. It covers the purpose and parameter semantics sufficiently for a simple math tool, but could mention that BMR is in calories per day.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds valuable meaning beyond the schema by specifying units (kg, cm, years) and the default for 'sex'. This is especially important given the 0% schema description coverage. However, it does not specify constraints like positivity or allowed values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Calculate Basal Metabolic Rate (BMR)' and specifies the Mifflin-St Jeor equation. This distinguishes it from sibling tools like calculate_bmi or body_fat_calc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when BMR calculation is needed, but it does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; the description carries full burden. It explains the estimation methods and parameter roles but lacks details on accuracy, limitations (e.g., Navy method for adults only), or that results are estimates. Some transparency, but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: a lead sentence followed by a parameter list with brief explanations. No wasted words, but the list could be formatted more cleanly (e.g., bullet points or table). Still efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 7 parameters (3 required, 4 optional) and an output schema present, the description covers the tool's purpose and input semantics. However, it omits context about formula sources or output interpretation (e.g., body fat category). Adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description compensates well. All parameters are listed with units (e.g., weight in kg) and optionality clarified (e.g., 'optional, for Navy method'). This adds meaning beyond the schema's titles, though default values could be explicitly noted.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool estimates body fat percentage using either measurements or a BMI-based formula. It distinguishes between two methods and names specific parameters for the Navy method. This contrasts with sibling tools like bmi_calc (which calculates BMI, not body fat).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use cases through parameter lists (optional measurements for Navy method) but does not explicitly state when to use this tool versus alternatives like bmi_calc or tdee_calc. No exclusion criteria or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as precision, validation, or formula-specific behavior beyond listing the formulas. With zero annotations, more detail would be expected.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loaded with the primary purpose, and then clearly lists parameters in a structured way. Every sentence is necessary and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema, the description does not need to detail return values. It adequately covers input parameters and purpose. Minor missing details like unit clarity or formula validation but sufficient for a simple calc tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description provides meaningful details for each parameter: weight in kg, height in cm, and formula options with defaults. This adds value beyond the schema titles, though constraints or formatting guidance are missing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action ('Calculate BSA') and resource ('Body Surface Area'), with specific mention of multiple formulas, distinguishing it from sibling tools like BMI or BMR calculators.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives, but the purpose is clear from the name and description. Usage is implied, but no exclusions or context are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description indicates a read-only analysis of code, which is accurate. However, without annotations, it could benefit from stating that the code is not stored or modified. The current description is adequate but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences plus parameter explanations. Information is front-loaded, and every sentence serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the input parameters and lists the output statistics. With an output schema present, the agent can infer the return structure. It is complete enough for a straightforward analysis tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning beyond the schema by explaining the code parameter as source code and the language parameter as optional with auto-detection. With 0% schema coverage, this adds significant value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool retrieves code statistics including LOC, comments, blank lines, functions, and classes. This distinguishes it from sibling tools like text_stats or code_complexity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like code_complexity. It mentions language auto-detection but does not specify prerequisites or scenarios where this tool is preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It lists parameters and options but does not describe the output format or any side effects. Since it is a simulation tool, it is read-only, but this is not explicitly stated. The description is adequate but lacks detail on what is returned.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with two sentences plus a parameter list. It is front-loaded with the purpose. However, it could be more structured (e.g., separate sections for description and parameters). No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists, the description does not need to explain return values. However, the explanation of what the tool returns (e.g., a modified hex color, an RGB value, or a visualization) is absent. For a simulation tool, this is a notable gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides meaningful details: hex_color should be without '#', deficiency lists options with a default. This adds significant value beyond the schema which only specifies types and default.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool simulates color appearance for different types of color blindness, specifying verb 'simulate' and resource 'how a color appears'. It distinguishes from sibling color conversion tools by focusing on color vision deficiency simulation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide explicit guidance on when to use this tool versus alternatives. While the purpose is clear, there are no when-to-use, when-not-to-use, or alternative mentions. The context implies accessibility testing, but this is not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden for behavioral disclosure. It states the input format but omits details about output (though an output schema exists), error handling, or validation. It is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief with two sentences: purpose first, then parameter details. Every sentence adds value, and there is no superfluous text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (one input, simple computation) and the existence of an output schema, the description is mostly complete. It lacks information on error behavior for invalid color formats, but this is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description compensates by explaining the hex_color parameter format ('Hex color without #') and providing an example ('3498db'). This adds significant meaning beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: 'Find the complementary (opposite) color on the color wheel.' It uses a specific verb 'Find' and specific resource 'complementary color', distinguishing it from sibling tools like color_harmony (full palette) or convert_color (format conversion).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as color_harmony or color_mix. It does not mention exclusions, prerequisites, or context for appropriate use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden for behavioral disclosure. It correctly constrains input to non-negative integers, but does not explain behavior for invalid inputs, overflow handling, or the nature of the return value (beyond what output schema might convey).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficient with one clear sentence plus a parameter line. It is appropriately sized for a simple tool, though a more structured format (e.g., separating usage constraints) could improve it slightly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description covers the essential purpose and parameter semantics. Minor gaps include lack of mention of large number support or error handling, but overall adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds significant meaning beyond the schema: it specifies the role ('to calculate factorial of') and the constraint ('non-negative'), compensating for the 0% schema description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Calculate') and the resource ('factorial of a non-negative integer'), which is specific and distinguishes this from sibling calculator tools that handle different mathematical operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool vs. alternatives among the many sibling tools. The description does not mention context, prerequisites, or related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must convey behavioral traits. It describes the core transformation but does not specify error handling for invalid inputs or edge cases (e.g., malformed addresses). For a simple read-only tool, this is minimally adequate but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences with no redundancy. The first sentence states the purpose, and the second lists the parameter. Every word serves a purpose, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists (though not shown), the description does not need to explain return values. For a tool with one simple parameter and no annotations, the description covers the essential use case adequately. It could optionally mention that the result is the expanded address, but the output schema likely handles that.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, so the parameter 'ipv6' is just a string type. The description adds meaning by labeling it as an IPv6 address to expand and providing examples ('::1', '2001:db8::1'), which helps the agent understand the expected format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: expanding abbreviated IPv6 addresses to full notation. The verb 'Expand' and the resource 'abbreviated IPv6 addresses' are specific and unambiguous. None of the sibling tools target IPv6 expansion, so it is well-distinguished.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus others. It does not mention prerequisites, acceptable input formats, or when not to use it (e.g., already expanded addresses). Given the many sibling tools, explicit context would help.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It does not disclose constraints like maximum number size, handling of negative numbers, decimals, or rounding behavior. The example is simple and may mislead about edge cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short, front-loaded with the main purpose, and uses bullet-style parameter explanations. Every sentence adds value, with no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description covers the core functionality well. However, it omits details like supported number ranges or error handling, which would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Since schema description coverage is 0%, the description adds essential meaning: it explains that 'number' is the number to convert and 'currency' is an optional code for money format. This is more than the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific verb ('Convert') and resource ('numbers to English words'), with a concrete example. It easily distinguishes from sibling tools like 'roman_numerals' or 'binary_convert'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when English word representation is needed, and the 'currency' parameter hints at monetary formatting. However, it lacks explicit guidance on when to use this tool versus alternatives, or when not to use it (e.g., for very large numbers that might not be supported).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It describes a simple calculation with no side effects, but it does not explicitly state it's a read-only operation or that it requires no external dependencies.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, with a one-line purpose followed by a clear parameter list. Every sentence is necessary and well-organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists, the description adequately covers inputs. It lacks discussion of edge cases or error conditions, but for a simple calculator it is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description adds value by explaining each parameter (distance, time components, unit) and their defaults. However, it could provide more details on constraints (e.g., non-negative values).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates pace, speed, and finish time for running/walking, with a specific verb and resource. It stands out among many calculator tools by focusing on pace.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternative calculators like convert_units or other calculators. There is no mention of prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior, but it omits edge cases like what happens if the source text is longer than the target length or if the character input is invalid. The return type is not mentioned, though an output schema exists.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences and a parameter list, front-loaded with the action. No extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple padding tool with an output schema, the description covers the core functionality and all parameters. Minor gaps exist regarding edge cases, but overall it is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description explains each parameter, including defaults and allowed values for 'side'. This adds significant meaning beyond the schema, though it could be more precise (e.g., enumerating allowed values).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool pads text to a specified length on left, right, or both sides, using a specific verb and resource. It distinguishes from many text-related siblings like truncate_text or wrap_text.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. Usage is implied but not explicitly contrasted with siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and description lacks details on side effects, data sources, or reliability. Only mentions token savings and return structure, which is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Description is short, front-loads purpose and usage. The token-saving claim is slightly extraneous but not harmful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, the description adequately covers usage and parameter. However, it lacks details on how research is performed (e.g., web search, LLM inference), which could help agent calibration.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but description provides a useful example and clarifies the parameter's purpose, adding meaning beyond the schema's type and title.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool researches any topic and returns a structured report, with a specific verb and resource. Distinguishes from siblings like search_web or summarize.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says to use when needing a quick research briefing. Does not mention when not to use or provide alternatives, but context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description only states basic calculation; lacks disclosure on edge cases (e.g., zero cost) or output format. However, as a straightforward math tool, risky behavior is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: two sentences and a simple parameter list. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and only two simple parameters, the description provides sufficient context for a basic ROI calculation. Could mention return format differences but overall adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Description adds meaning beyond schema by explaining what 'gain' and 'cost' represent. Although schema coverage is 0%, the parameter descriptions are clear and directly tied to the formula.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates ROI percentage, using a specific verb and resource. It is distinct from sibling tools like 'investment_calculator' and 'stock_return' by focusing on a standard financial metric.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description does not mention prerequisites, limitations, or comparison to other calculation tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses the basic calculation function but does not address edge cases (e.g., negative salary, invalid frequency) or any behavioral traits like rounding or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first states purpose, second lists parameters. It is concise and front-loaded with purpose. However, the parameter list could be more integrated or structured as a bullet list for readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists (not shown), so return values need not be described. The description covers the core functionality but lacks details on error handling, input validation, or examples, which for a simple tool is acceptable but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description adds significant meaning by explaining each parameter: salary amount, frequency with allowed values ('annual', 'monthly', 'weekly', 'daily', 'hourly'), and currency code with default. This goes beyond the schema's type-only definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'calculate' and resource 'salary breakdown' with explicit time periods (hourly, daily, weekly, monthly, annual). It distinguishes from sibling tool 'salary_convert' which likely does single conversion, while this computes all equivalents.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by listing parameters but does not explicitly state when to use this tool versus alternatives like 'salary_convert'. It provides no exclusions or contextual guidance beyond the parameter list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description states that the tool estimates speaking time, implying a read-only calculation. However, it does not disclose any potential side effects, required permissions, or behavior beyond the basic estimation. The output schema exists but is not referenced in the description, so the agent must infer return structure from the schema alone.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one sentence and a two-line parameter list. Every part is valuable and there is no redundancy. It is well-structured and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple calculation tool, the description covers the core functionality and parameter semantics. The presence of an output schema compensates for the lack of return value description. Minor gaps include no mention of edge cases or limitations, but these are not critical for this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides brief explanations for both parameters ('text' and 'wpm'), including the default value for wpm. Since the schema has 0% description coverage, this adds essential meaning beyond just type and title, though more detail (e.g., text format expectations) could be beneficial.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: estimate speaking time for text given a words-per-minute rate. The verb 'estimate' and resource 'speaking time' are specific, and the tool distinguishes itself from the sibling tool 'reading_time' by focusing on speaking rather than reading.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, such as 'reading_time'. The description does not mention any prerequisites or contexts where this tool is preferred, leaving the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that the tool converts to 'all other units' (not just selected ones) and lists the units. However, it does not specify what is returned (e.g., an object with all four values), precision handling, or whether negative temperatures are supported.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences plus a parameter list. It front-loads the purpose and then details parameters. Every sentence is necessary, with no filler or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity and the presence of an output schema, the description is mostly sufficient. It covers the conversion behavior and parameters, but could be enhanced by noting the output format (e.g., 'returns an object with converted temperatures') to improve contextual completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It explains both parameters: 'value' as temperature value and 'from_unit' as source unit with allowed values ('c', 'f', 'k', 'r'). This adds meaning beyond the schema, but could be more explicit about the unit codes.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action with a specific verb ('Convert') and resource ('temperature from any unit to all other units'). It explicitly lists the units (C, F, K, R) and distinguishes from sibling conversion tools (e.g., convert_units) by focusing on temperature and the 'all' conversion behavior.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives (e.g., convert_units for single conversions or specific calculators). It does not mention exclusions or preferred contexts, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as error handling, return type, or side effects. It only describes the transformation without context on permissions or potential issues.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one sentence summarizing purpose followed by a clean parameter list. Every sentence adds value with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (input transformation) and the presence of an output schema (though not visible), the description covers the essential input format and separator. It does not address edge cases, but for a straightforward tool it is nearly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description effectively adds meaning by naming both parameters and explaining them: 'json_str' as 'Flattened JSON string' and 'separator' with default. This compensates for the lack of schema-level descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb ('reconstruct') and resource ('nested JSON from dot-notation flattened format'). It effectively distinguishes itself from the sibling 'flatten_json' by describing the inverse operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when dealing with dot-notation flattened JSON, but lacks explicit guidance on when to use this tool versus alternatives like 'flatten_json'. No exclusion criteria or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes inclusive vs exclusive behavior beyond schema defaults. No annotations, but basic behavioral context is provided.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence plus parameter list. No fluff, front-loaded, efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers calculation logic and parameter meanings. Lacks output description but output schema exists. Minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage 0%, description adds meaning for all parameters (e.g., 'amount — Price amount', inclusive meaning). Compensates well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description states 'Calculate VAT amounts and totals' with clear verb and resource. Distinct from sibling calculator tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use vs alternatives. No exclusions or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the estimation based on activity, weight, duration, and intensity, but does not discuss precision, underlying MET values, or any limitations. Adequate but not deep.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: one main sentence followed by a clear bulleted parameter list. It is front-loaded and efficient, though slightly more verbose than necessary for the parameter details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has only 4 simple parameters, and the description explains all inputs thoroughly. An output schema exists, so the description does not need to cover return values. Complete for this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description fully compensates by listing example activities, specifying units (kg, minutes), and defining intensity options (light, moderate, vigorous) with a default. Adds significant meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Estimate calories burned during physical activities.' This is a specific verb+resource combination that distinguishes it from other calorie-related tools like bmr_calc or tdee_calc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. While the description implies use for estimating activity calories, it does not mention when not to use it or compare to siblings like bmr_calc or body_fat_calc.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool removes whitespace and comments, but does not disclose if it performs additional transformations (e.g., variable renaming) or handles syntax errors. This is adequate but incomplete.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short, front-loaded with purpose, and includes a parameter list. Every sentence is necessary, and there is no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and the presence of an output schema, the description covers the main aspects. Minor gap: no mention of error handling or input validation for invalid JavaScript.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning beyond the input schema by explaining the 'code' parameter as 'JavaScript source code to minify.' Schema coverage is 0%, so this is crucial and well-done.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Minify JavaScript code by removing whitespace and comments,' using a specific verb and resource. It distinguishes from siblings like minify_css and minify_html.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives or any prerequisites. The description lacks context about when to choose minify_js over other code minifiers or transformers.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes basic behavior (generating tints/shades) and parameters, but does not disclose algorithm details, return format, or any side effects. With no annotations, more depth would improve transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: two sentences plus parameter list. No fluff, front-loaded with purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, existence of output schema, and complete parameter explanations, the description is fully adequate. No missing details needed for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Compensates for 0% schema coverage by explaining both parameters: hex_color with an example and steps with a default. Adds meaning beyond bare schema types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Generate tints (lighter) and shades (darker) of a base color' with a specific verb and resource. It distinguishes from sibling tools like complementary_color or color_mix by specifying a unique operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as color_mix or color_harmony. The description lacks context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must disclose behavior. It mentions 'real-time exchange rates' but does not clarify if the operation is read-only, has side effects, or any limitations. Basic disclosure, but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with a clear purpose statement followed by usage context and parameter details. No unnecessary words, and the important information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the purpose, parameter semantics, and supported currencies (160+). It does not detail the output format, but an output schema exists. Minor gap: could mention that the result is a converted amount.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, but the tool description lists each parameter with meaning, default values, and ISO code format. This fully compensates for the schema gap and adds valuable detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it converts currencies using real-time rates. It uses a specific verb and resource. However, it does not explicitly differentiate from sibling tool 'currency_cross', which might serve a similar purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives usage contexts like financial calculations and price comparison, but lacks explicit guidance on when not to use this tool or alternatives. It does not mention the sibling tool 'currency_cross' as an alternative.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden of behavioral disclosure. It lacks details on handling nested objects, error behavior, encoding, or output format specifics beyond 'CSV format'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two clear sentences, front-loading the purpose. The parameter description is integrated cleanly without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the output schema exists (not shown) and the tool is simple, the description does not address edge cases like nested objects or malformed JSON, leaving some completeness gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds meaning by specifying 'JSON string (object or array of objects)', clarifying acceptable input types beyond the schema's generic 'string'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Convert JSON object or array to CSV format', which is a specific verb+resource. The sibling tool 'convert_csv_to_json' distinguishes this as the reverse operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description advises using this to transform API responses or structured data into CSV, providing clear context. However, it does not explicitly exclude cases like deeply nested JSON or mention alternative conversion tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description adequately explains the tool's behavior: it uses free APIs and geocoding, and lists the returned data. It does not disclose potential latency or rate limits, but the core transparency is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with no wasted words, front-loads the purpose, and uses clear structure with separate sections for description and parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists, the description sufficiently covers what the tool returns. It lacks mention of units or error handling, but for a simple tool, it is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% coverage, but the description adds a clear parameter explanation with an example ('London'), which compensates beyond the schema's minimal 'City' title.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves current weather for any city, specifying the data sources and output fields. It implicitly distinguishes from forecast tools by mentioning 'current weather', but does not explicitly differentiate from siblings like 'get_forecast'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use the tool (get current weather for a city) and what it does, but provides no guidance on when not to use it or which alternative tools (e.g., 'get_forecast', 'get_air_quality') might be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It correctly states the core functionality (escape/unescape HTML entities) but omits any additional traits like performance, error handling, or side effects. It is adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two short sentences plus a bulleted parameter list. Every word adds value, with no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, the description covers the essential information. The presence of an output schema means return values do not need to be described. However, a brief example or note about HTML entity recognition could enhance completeness slightly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description fully compensates by explaining the meaning of both 'text' (text with HTML) and 'mode' (escape or unescape with default). This adds significant value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Escape or unescape' and the resource 'HTML entities in text', making the tool's purpose unambiguous. It distinguishes from sibling tools like string_escape or url_encode_decode that handle different escaping contexts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide guidance on when to use this tool versus alternatives, nor does it specify when to choose escape vs unescape beyond the mode parameter. No exclusions or context are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It explicitly states that the tool removes whitespace and comments, which is sufficient for a simple one-parameter tool. However, it does not mention if it preserves HTML semantics or handles special cases like conditionals.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: two sentences that state the purpose and list the parameter. Every sentence is necessary and there is no waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, output schema exists), the description is complete. It explains the input and the transformation, and no further context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description compensates by explaining the parameter: 'html — HTML content to minify.' This adds basic meaning beyond the schema, but no extra details like format constraints or examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Minify HTML by removing whitespace and comments,' which is a specific verb and resource. It distinguishes itself from sibling tools like code_minify_js and minify_css by specifying HTML.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool vs alternatives such as minify_css or code_minify_js. It lacks context about prerequisites, when not to use, or comparison with other minification tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must cover behavioral traits. It lists the target conventions but does not disclose how the tool handles edge cases (e.g., invalid names, mixed conventions) or any side effects. It is adequate for a simple transformation tool but could be more transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: two sentences. The first sentence clearly states the purpose. The parameter list is formatted as a list, which is efficient but could be more structured (e.g., using markdown). Overall, it is appropriately sized with minimal waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema (not shown), the description is reasonably complete. It covers input parameters and supported conventions. It does not discuss return values, but the output schema likely covers that. It lacks details on error handling or unsupported inputs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain parameters. It does so by describing 'name' and 'target', listing valid values for target. This adds meaning beyond the basic type and default. However, it could be more precise about what 'name' accepts (e.g., whether spaces are allowed).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Convert identifier names between naming conventions.' It specifies the action (convert) and the resource (identifier names). This effectively distinguishes it from sibling tools like convert_case or swap_case that handle general text case transformations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. While the purpose is clear, the description lacks information on prerequisites, exclusions, or specific contexts where this tool is preferred over similar tools like 'convert_case' or 'slugify_text'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry burden. It discloses the generation action and style options but omits details like randomness seed, determinism, or side effects. Adequate for a simple generator.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise lines: a clear purpose sentence followed by a clean parameter listing. Front-loaded and efficient without waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool (1 optional param, output schema exists), the description covers purpose and parameter choices fully. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% coverage, but description enriches the sole parameter 'style' by listing allowed values and default, adding meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Generate a random hex color' with specific verb and resource, and mentions optional color families, distinguishing it from sibling tools like color_mix or color_harmony.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., list_color_names, color_palette). Only parameter options are listed without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It mentions the AI model ('Powered by DeepSeek V4 Flash') but fails to address important aspects like token limits, cost implications, reversibility, or handling of inappropriate input. The description lacks sufficient disclosure for a generative AI tool with no safety annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: a single introductory sentence, a usage sentence, and a formatted parameter list. Every sentence adds value, and there is no redundancy. It is front-loaded with the core purpose, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 5 parameters and an output schema, the description covers all parameters and the AI model, enabling correct invocation. It is missing potential details like output format (though output schema exists), rate limits, or maximum input length, but these are not critical given the output schema and parameter defaults.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the tool description fully compensates by listing all 5 parameters with explanations, defaults, and enum-like examples for 'tone' and 'format'. The description adds meaning beyond the schema, such as the specific options for tone (professional, casual, persuasive, etc.) and format (paragraph, bullet_points, single_sentence).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Rewrite content with AI — change tone, length, audience, or format.' It specifies the verb (rewrite), resource (content), and scope (AI-driven transformation). This distinguishes it from sibling tools like 'paraphrase' or 'simplify_text' which are more narrow in scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides usage context: 'Use this to repurpose content for different channels' and mentions SEO, social media, and technical content adaptation. However, it does not explicitly say when not to use this tool or offer alternatives. No sibling comparisons or exclusions are given, so an agent might misuse it for simple paraphrasing when a specialized tool might be better.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It correctly identifies the tool as a calculator (non-destructive), but does not disclose return format or any side effects. Minimal but not misleading.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one sentence for purpose and three bullet points for parameters. No wasted words, front-loaded with main function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity and existing output schema, the description is mostly complete. It covers the calculation inputs and purpose, though it does not specify the return format (likely covered by schema).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. It provides clear explanations for all three parameters, including units and default for dividends, adding meaning beyond the schema's type and title.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates total stock return including price change and dividends. The verb 'Calculate' and resource 'stock return' are specific, distinguishing it from sibling financial tools like investment_calculator or dividend_calc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description does not mention any context, prerequisites, or exclusions, which is a significant gap given the variety of sibling financial calculators.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior. It indicates the tool is a calculator (non-destructive, read-only) and lists parameters, but does not explain error handling, input validation, or output units. The output schema exists but is not referenced.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with an efficient structure: a single-line purpose followed by a parameter list. No redundant sentences. Every line contributes useful information, and the purpose is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers all parameters and their roles, but lacks details on the output format (e.g., VO₂ max units) and potential constraints (e.g., realistic value ranges). Given the output schema exists, the omission is minor but reduces completeness slightly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates fully. Each parameter gets a clear meaning: 'resting_hr' as 'Resting heart rate in bpm', 'method' with defaults ('resting' or 'exercise'), and 'weight' as optional for exercise. This adds value beyond the schema's simple titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Estimate VO₂ max using resting heart rate or exercise test', which is a specific verb ('estimate') and resource ('VO₂ max'). It distinguishes itself from sibling health calculators (e.g., bmr_calc, body_fat_calc) by focusing on a unique metric and methodology.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like bmr_calc or tdee_calc. It does not mention prerequisites, preferred use cases, or exclusions. An explicit comparison or context for selection is missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It states the tool finds the nearest web-safe color, implying a deterministic read operation, but does not disclose details like tolerance or algorithm. The output schema covers return format, so a score of 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence followed by the parameter line. It front-loads the purpose and includes only necessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and an output schema, the description covers the essential information: purpose, input format, and example. No gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has no description (0% coverage). The description adds meaning by specifying the format (no #) and providing an example, which goes beyond the schema's type and title.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool finds the nearest web-safe color for a given hex color. It specifies the input format and provides an example, distinguishing it from sibling color tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide guidance on when to use this tool versus alternatives like convert_color or color_named. It lacks explicit when-to-use or when-not-to-use instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It lists parameters and defaults but does not disclose potential side effects, error handling, output format, or constraints (e.g., date format, timezone handling). The output schema exists but is not referenced.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: a brief purpose sentence, a usage sentence, and a parameter list. No fluff. The structure is front-loaded with purpose. Minor improvement could be bullet points for parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 6 parameters (0 required) and an output schema, the description covers the main operations and parameters but lacks details on edge cases, default behavior per op, and validation. It is adequate for a calculator tool but leaves some gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides a clear parameter list with brief explanations for each (op, date1, date2, days, months, years), which adds meaning beyond the schema's just names and defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs date arithmetic and difference calculations, and lists specific use cases (find days between dates, add/subtract time, get date info). This distinguishes it from sibling date tools like calculate_age or calculate_business_days.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says when to use the tool (for finding days between dates, adding/subtracting time, getting date info). However, it does not provide exclusions or comparisons to alternative sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It mentions the calculation is Shannon entropy but does not disclose any additional behavioral traits like side effects, input length limits, or output format. The existence of an output schema partially compensates.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting of a single sentence about purpose followed by a parameter listing. Every word serves a purpose, and the format is easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter tool with an output schema (likely returning a number), the description covers the concept and parameter adequately. It could mention entropy range or behavior for empty strings, but overall it is sufficient for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description lists the only parameter 'text' and states it is the string to calculate entropy of. Since schema description coverage is 0%, this minimal added context is helpful. However, it does not specify constraints like maximum length or character encoding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific function: calculating Shannon entropy of a string, which measures randomness or information content. This verb+resource combination is distinct from sibling tools like char_count or word_frequency.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains what the tool does but provides no guidance on when to use it versus other text analysis tools (e.g., analyze_readability, text_stats). It lacks any 'when to use' or 'alternatives' statements.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but description states outputs. Does not disclose if password is stored or state any side effects; however, for a stateless check, basic transparency is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first defines purpose, second documents the single parameter. No fluff, exactly the needed information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool is simple (1 param, has output schema). Description mentions return types, sufficient for agent invocation without over-specification.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% coverage, but description adds meaningful parameter label and purpose ('Password to evaluate'), compensating for schema silence.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states action ('Check password strength') and specific outputs (score, crack time estimate, feedback). Unambiguous among siblings like generate_password or hash_text.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description implies use for password strength evaluation but provides no context on when to use vs alternatives or when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description discloses that the tool returns HTTP status and server info, but lacks details on error handling, timeouts, or any side effects. It is somewhat transparent but could be more explicit about behavior when the domain is unreachable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two main sentences and a parameter section. It front-loads the core function and usage guidance without any unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no nested objects) and the existence of an output schema, the description covers the purpose, usage, and return type adequately. It does not explain the output structure, but that is compensated by the output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description includes a 'Parameters' section that repeats the domain parameter with an example, adding minimal context beyond the schema. For a single parameter, the provided format hint is helpful but not extensive.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks if a domain has a valid SSL/TLS certificate and is reachable, using specific verbs and resources. It distinguishes from sibling tools like analyze_url or http_client by focusing on SSL validity and serving over HTTPS verification.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly advises using this tool to verify HTTPS before making requests, providing clear context. It does not mention when not to use or alternatives, but the guidance is sufficient given the tool's specific purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It describes parameter formats and defaults but does not disclose error handling, validation, output format, or any side effects. This is insufficient for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Highly concise: two sentences for purpose/usage, then a clear parameter list. No redundancy or fluff. Front-loads key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, usage, and parameters in sufficient depth. An output schema exists (not shown), so the lack of return value explanation is acceptable. However, could be improved by mentioning output format or error behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates well by detailing each parameter: accepted formats for 'value' (both hex and RGB), defaults for 'from_format' and 'to_format'. This adds significant meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Convert a color value between hex and RGB formats.' This specific verb+resource combination distinguishes it from sibling color tools like hex_to_hsl or hsl_to_rgb. Examples of hex (#FF0000) and RGB (rgb(255, 0, 0)) further clarify.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly provides usage context: 'Use this when working with CSS colors, design systems, or anywhere you need to translate between hex and RGB representations.' However, it does not mention when not to use or provide alternatives among the many sibling color conversion tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description should fully disclose behavior. It only states the basic conversion function without any detail about error handling, behavior when both parameters are provided, or size limits. This is a significant gap for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (two short paragraphs) and front-loaded with the main purpose. The parameter list is well-structured. It could be slightly more concise but effectively conveys necessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema (not shown but indicated), the description adequately covers the input semantics. It explains the two-parameter setup and their uses. However, it does not address edge cases like both parameters provided or empty input, which leaves minor gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description fully compensates by explaining each parameter in detail: 'html — HTML content to convert to markdown' and 'markdown — Markdown content to convert to HTML.' It also clarifies the requirement to provide at least one parameter, adding meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Convert between HTML and Markdown formats' with specific verbs and resources. It distinguishes itself from sibling conversion tools (e.g., convert_case, convert_color) by focusing on this bidirectional conversion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear usage context: 'transform web content into clean markdown or convert markdown to HTML for display.' It mentions the condition 'Provide at least one parameter.' However, it does not explicitly exclude alternative tools or specify when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description carries full burden. Discloses parameter defaults and ranges but does not mention error behavior for invalid input or output format. Adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise: purpose in first sentence, usage scenarios, then clean parameter list. No unnecessary words, front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given output schema exists, description doesn't need to detail return values. Covers tool purpose, usage context, and parameter semantics. Missing potential detail on input validation but adequate for a simple conversion tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage; description compensates by explaining each parameter: num as 'The number string to convert', from_base with default and range, to_base with default and range. Adds meaning beyond schema types and titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Convert numbers between different bases (hex, decimal, octal, binary)' with specific verb and resource. Provides use case examples like data inspection, color values, memory addresses. Distinguishes from sibling tools like binary_convert by indicating general base conversion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Gives context for usage ('low-level data inspection, color values, or memory addresses') but lacks explicit when-not-to-use or alternatives to sibling tools like binary_convert. No exclusion criteria provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It states basic behavior (counts syllables) but does not disclose handling of edge cases (hyphenated words, numbers), language assumptions, or algorithm type. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences plus a parameter list. Purpose is front-loaded in first sentence. No wasted words. Efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given simplicity (one param, output schema exists), description covers purpose, usage context, and parameter. Missing details on return value format (though output schema may cover) and multi-word phrase handling, but overall adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has no description for the 'text' parameter (0% coverage). Description adds 'The word or phrase to count syllables in', which provides basic meaning but lacks constraints on length, allowed characters, or whitespace handling. Barely compensates.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb 'Count' and resource 'number of syllables in a word or phrase'. It specifies use cases (poetry, readability, linguistics) which distinguishes it from sibling tools like word_count or analyze_readability.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description gives explicit use contexts (poetry, readability, linguistic applications) but does not mention when not to use or suggest alternative tools. The guidance is clear but lacks exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description does not disclose any behavioral traits beyond the basic functionality. It lacks information about edge cases (e.g., negative discounts, zero original price) or output format. With no annotations, more transparency is expected.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences plus a bullet-like parameter list. It is front-loaded with the primary purpose and immediately provides parameter details. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists, the description does not need to explain return values. However, it could be more complete by including an example or noting the output format. It covers the core functionality well.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning to all three parameters: original price, discount amount/percentage, and type (percent vs fixed). Since the input schema has 0% description coverage, the description compensates well by explaining the semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Calculate the final price after a discount (percentage or fixed amount).' It uses a specific verb ('calculate') and resource ('final price'), and distinguishes itself from sibling tools like tip_calculator, percentage_calculator, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the type parameter ('percent' or 'fixed') and implies usage for discount calculations, but does not provide explicit guidance on when to use this tool versus alternatives. Given many sibling calculators, more explicit context would be helpful.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the full behavioral burden. It discloses three actions (get, set, delete) and notes persistence across sessions, but omits details like error behavior (e.g., missing key), concurrency semantics, or data size limits. The mention of 'KV-backed' helps but is insufficient for a mutation-focused tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences plus a parameter list. The first sentence immediately conveys the purpose. The parameter list is clearly separated and uses plain language. Every sentence adds value with no fluff, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (3 parameters, no nested objects) and the existence of an output schema, the description covers the essential aspects: purpose, parameters, and actions. It lacks examples or edge-case behavior but is complete enough for typical usage. Sibling tools are unrelated, so no comparative context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds meaning by explaining 'key' as 'Unique file key', 'value' as 'file content' for set actions, and listing action options (get, set, delete) with defaults. This goes beyond the plain schema, making parameter usage clearer, though it could explicitly enumerate action values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Read or write persistent file storage across sessions (KV-backed)'. This provides a specific verb-resource pair and distinguishes it from sibling tools, most of which are unrelated (e.g., calculators, text analysis). It establishes the tool's core functionality succinctly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains what the tool does but gives no guidance on when to use it versus alternatives. It mentions 'KV-backed' but doesn't contrast with other storage tools or suggest scenarios where this tool is appropriate or inappropriate. Lack of exclusion criteria or sibling references limits its usefulness.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description must bear full burden. It fails to disclose critical behavioral traits: randomness source, determinism, side-effect-freeness, or any constraints on large count generations. Only parameter constraints are given.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely efficient: single sentence for purpose, one sentence for usage guidance, then clear parameter bullets. No redundant or extraneous information. Front-loaded and well-organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequately covers inputs and usage, but lacks behavioral context (randomness, uniqueness, side-effects). Output schema exists, reducing need for return value description, but gaps in transparency lower completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema description coverage, the description fully explains both parameters: count (range 1-100, default 1) and format (options: standard, json, array, default standard). This adds crucial meaning beyond the schema types and defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Generate one or more UUID v4 (random) identifiers' – a specific verb-resource pair that clearly distinguishes it from sibling tools like generate_nanoid or generate_ulids. Also provides usage examples (database records, API resources) reinforcing purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use this when you need unique identifiers...' providing clear guidance on appropriate contexts. Does not explicitly mention when not to use or compare to alternative tools, but the context is sufficient given sibling variety.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It fails to disclose any behavioral traits such as data freshness, rate limits, authentication requirements, or output structure. The description only covers purpose and parameters, leaving significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with no unnecessary text. It uses a clear two-sentence introduction followed by parameter details, making it easy to scan. Every sentence serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the moderate complexity and the presence of an output schema (not shown), the description is mostly complete. It covers country support, default values, and usage. However, it lacks information about the output format or error handling, which would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds substantial meaning beyond the schema (which has 0% coverage). It explains that 'country' is a two-letter code with default 'GB' and supported values 'GB', 'US', 'IE'. For 'year', it states default as current year (though schema lists 2026, a minor discrepancy) and gives an example. This compensates well for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get public holidays by country and year' with a specific verb and resource. It includes usage scenarios like checking bank holidays and planning. The tool is distinct from all listed siblings, which are unrelated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit usage contexts are provided (e.g., 'check bank holidays, plan around public holidays, or calculate working days'). However, no exclusions or alternatives are mentioned, and the description does not specify when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It states the tool returns 'ISO week number and year' but does not mention edge cases (e.g., date near year boundaries), error handling for invalid dates, or the exact output format. This lack of detail is a significant gap for a simple tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: it opens with the main action, then provides usage context and parameter details. Every sentence is necessary, and there is no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has one optional parameter and an output schema (according to context signals), the description covers the essential aspects: purpose, usage, and parameter explanation. However, it lacks behavioral details such as valid date ranges or what happens with invalid input, which would push completeness to a 5.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, but the description explains the parameter 'date' with an example format ('e.g. 2025-06-07') and default behavior ('Defaults to today if empty'). This adds meaning beyond the schema, which only has a title and type.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Get the ISO week number and year for a given date.' It uses a specific verb ('Get') and identifies the resource (ISO week number and year). This distinguishes it from other date-related tools like get_season or calculate_date.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context for use: 'Use this to determine the week number of the year following ISO 8601 standards, useful for reporting and scheduling.' It indicates when to use the tool but does not explicitly mention alternatives or when not to use it, which would warrant a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description adds input range constraints (0-360 for hue, 0-100 for saturation and lightness) that are absent from the schema, but does not disclose output range, clamping, error handling, or other behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with front-loaded purpose and a clean parameter list. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema (not shown), description adequately covers purpose and parameter ranges. Lacks only minor details like default or clamping behavior, but overall sufficient for a simple conversion tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite schema coverage being 0%, description adds meaningful context by specifying expected ranges for each parameter, which the schema lacks (only type number). Provides clear semantic expectation beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Convert HSL values to RGB color', specifying the exact direction of conversion, distinguishing it from sibling tools like rgb_to_hsl or hex_to_hsl.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance. Among many color conversion siblings, it only implies the use case by its name and description, but does not mention alternatives or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It only describes the basic lookup action without mentioning idempotency, error handling (e.g., invalid extension), or whether it is read-only.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: two sentences that immediately convey purpose and the optional parameter behavior. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple lookup with one parameter and an existing output schema, the description covers core usage. However, it could be more complete by briefly noting the output format or behavior for unknown extensions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning beyond the bare input schema by explaining the parameter with an example ('File extension (e.g. 'pdf', 'jpg')'), compensating for the 0% schema description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Look up MIME types by file extension'), distinguishes from sibling lookup tools (e.g., lookup_html_entity, lookup_http_code), and includes the special case of an empty parameter for a full list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly tells when to leave the parameter empty for a full list, but does not discuss when to prefer this tool over alternatives or any exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description states the three operations but does not disclose edge cases, performance characteristics, or any side effects. Since there are no annotations, the description carries the full burden; it is adequate but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one sentence for purpose, then a bullet-style parameter list. It front-loads the key information and wastes no words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two parameters, the description covers the operations and parameters. It does not describe return values, but an output schema exists (not shown) which likely handles that. Missing return format description prevents a 5.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning by explaining the 'operation' parameter's allowed values and the role of 'value'. With 0% schema coverage, this compensates well, though enumerating the operation values explicitly would earn a 5.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly lists three specific operations: check primality, find next prime, and factorize. It uses strong action verbs and distinguishes this tool from other number operations among siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide guidance on when to use this tool versus alternatives like factorial_calculator or fibonacci_sequence. It implicitly covers its own usage but lacks explicit when-not or comparison with siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It mentions the output (article text, title, metadata) but does not disclose error handling, rate limits, authentication needs, or behavior for non-article URLs. This is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with two sentences and a parameter line. It is front-loaded with the purpose, contains no redundant information, and every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter, and an output schema exists (reducing need to describe return values). The description covers the key aspects: what it does, the primary output, and the input. It could mention support for different URL types or content extraction limitations, but overall it is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the single parameter 'url' is described as 'URL to read content from' in the description, adding minimal meaning beyond the schema's type. While more detail (e.g., supported protocols, encoding) would be beneficial, the description compensates adequately for the lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Read and extract') and defines the resource ('clean text content from any URL'). It also lists the return type (article text, title, metadata), clearly differentiating from sibling tools like 'web_scrape' or 'scrape_meta_tags' which may return raw HTML or specific meta tags.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for extracting clean text from URLs, but does not explicitly state when not to use it or provide alternatives. Given the sibling list includes many similar tools, more explicit guidance would improve clarity, but the current phrasing is sufficient for most use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the core behavior (escaping regex characters) but does not detail which characters are escaped, edge cases, or performance. Adequate but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence plus a parameter list, highly concise and front-loaded. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-param tool with an output schema, the description adequately explains input and action. It does not describe the output format explicitly, but the output schema likely handles that. Minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds parameter documentation: 'text — String to escape for regex use.' This adds meaning beyond the schema's type and title, compensating for the lack of param descriptions in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Escape' and specific resource 'special regex characters in a string' for the purpose 'literal matching'. It distinguishes from siblings like 'string_escape' and 'test_regex'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage (escaping strings for regex) but does not provide explicit guidance on when to use versus alternatives or when not to use. No explicit contextual advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so description carries full burden. It only states the basic function without disclosing error handling, rate limits, or what happens on failure. Minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, with one sentence for purpose and a clear parameter list. No unnecessary words, front-loaded with the core function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with only one parameter. An output schema exists, so return values are covered elsewhere. However, lack of error handling or permission details is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema only defines ip_address with type string. The description adds a usage example (e.g., '8.8.8.8') and specifies it's an IP address, which provides meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs reverse DNS lookup (IP to hostname), which is a specific verb-resource pair. It distinguishes from sibling tools like dns_lookup (forward lookup) and dnssec_check.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a concise purpose and parameter example, implying when to use it. No explicit when-not-to-use or alternatives, but context from siblings and simplicity of tool makes it clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It describes the basic rounding operation but does not detail edge cases (e.g., rounding zero, negative numbers) or tie-breaking rules. For a simple mathematical function, this is adequate but lacks comprehensive transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting of a single introductory sentence followed by a parameter list. Every sentence is necessary and information-dense, with no wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (not shown), the description does not need to explain return values. The tool is simple, and the description covers the core functionality. A minor omission is the lack of explicit rounding rule (e.g., standard rounding), but this is common knowledge for significant figures.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates by clearly explaining each parameter: 'value — Number to round. sig_figs — Number of significant figures (default: 3).' This adds meaningful context beyond the schema's type and default information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Round a number to a specified number of significant figures.' It uses a specific verb ('Round') and a specific resource (number with significant figures), making the purpose unambiguous and distinct from sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide explicit guidance on when to use this tool versus alternatives. While the purpose is clear, there is no mention of when not to use it (e.g., for decimal place rounding) or comparison to related tools like scientific_notation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. States it checks syntax, domain, and disposable providers. Lacks details on return format and network dependencies, but sufficiently transparent for a verification tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Concise: two short paragraphs plus parameter line. No wasted words, front-loaded with purpose, well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers input and checks performed. Missing details on output format and error cases, but output schema likely covers return values. Adequate for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but description includes a parameter description ('email — The email address to verify (required)') which adds basic meaning. Minimal but adequate for a single obvious parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb 'Verify' with specific resource 'email address'. Lists specific checks (syntax, domain, disposable) distinguishing from siblings like 'email_domain_check'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit use cases (sign-up, form submission, contact list cleaning) but does not mention when not to use it or differentiate from sibling tool 'email_domain_check'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not detail return format, formula used, or potential error behavior. Since annotations are absent, the description carries full burden but provides minimal behavioral insight beyond the calculation intent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one sentence for purpose followed by a clean parameter list. No extraneous words, well organized, and easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool is a simple calculator with an output schema (not shown) likely describing return values, the description sufficiently covers inputs. It could mention output unit (e.g., liters) but is adequate for its complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds meaningful explanations for each parameter: weight in kg, activity minutes with default, and temperature with allowed values. This compensates for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Calculate recommended daily water intake' with a specific verb and resource. It distinguishes itself from sibling tools like bmr_calc or calorie_burn which handle different health metrics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use or when not to use this tool versus alternatives. The context of parameters (weight, activity, climate) implies usage scenarios, but there is no direct statement of suitability or exclusion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden. It specifies constraints (non-negative integers, r ≤ n) but does not disclose the output format, error handling, or edge cases. It is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise with three short paragraphs. It uses a clear structure: purpose, usage, and parameter details. No redundant or unnecessary sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple combinatorics tool with an existing output schema, the description covers input parameters and usage context. It lacks mention of output format or edge cases, but overall is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% (only titles and types). The description adds full meaning: explains what n and r represent, their constraints, and their relationship. This is essential and compensates entirely.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates both nCr (combinations) and nPr (permutations), with specific verb+resource. It distinguishes itself from siblings like factorial_calculator or prime_operations by naming both operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says 'Use this for combinatorics and probability calculations,' which gives context but does not explicitly state when not to use or mention alternatives. It lacks exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must bear the full burden. It identifies the tool as a lookup (read-only) operation, but does not explicitly confirm it has no side effects, rate limits, or other behavioral nuances. The description is adequate but not highly transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear statement of purpose, followed by a list of retrievable properties and parameter details. It is concise (approximately 70 words) and front-loaded with the main action. A minor improvement would be to reduce redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 optional parameters, no enums, output schema exists but not shown), the description covers the essentials: what the tool does, what parameters are available, and a usage constraint. It does not need to explain return values due to the output schema, making it sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds significant value by explaining the two parameters ('symbol' and 'search'), giving examples for 'symbol', and clarifying that at least one parameter is required. However, the explanation for 'search' is vague ('by name or property').
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Look up chemical elements from the periodic table.' It specifies the verb (look up) and resource (chemical elements), and distinguishes itself from sibling tools like 'list_currencies' by being specific to the periodic table.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description tells the user to use this tool to find element properties and explicitly states the need to provide at least one parameter. However, it does not mention when not to use it or suggest alternatives, though no direct alternatives exist among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses the two modes (encode/decode) but does not mention error handling (e.g., invalid Base64 input) or output format details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise: two short paragraphs plus a parameter list. Every sentence adds value, and the purpose is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity and presence of an output schema, the description covers the essential operations. A brief note about invalid input handling would improve completeness, but it's adequate for most uses.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description provides clear, detailed explanations for both parameters (text and mode) including their values and defaults, fully compensating for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool encodes or decodes Base64 text. It provides a specific verb-resource pair but does not explicitly distinguish from sibling tools like encode_base32 or encode_base85.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit use cases (encode for text-safe transport, decode previously encoded data). However, it lacks guidance on when not to use it or alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full behavioral transparency burden. It discloses that the tool uses a free service without API key, returns up to 5 results with specific fields, and requires a query. However, it omits details like rate limits, error handling, or response format beyond the listed fields.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, using a few short sentences to convey purpose, service, output, and parameter. It is front-loaded with the main action. While efficient, it could eliminate the minor redundancy in listing return fields (already part of output schema).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has only one required parameter and an output schema (not shown but present), the description is fairly complete. It explains the purpose, input, and output informally. Missing aspects like error states or usage limits are minor, as the output schema likely covers structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'query' is described as an address or place name with examples ('London', '10 Downing Street'). Since schema description coverage is 0%, the description adds essential meaning beyond the schema's minimal 'Query' title. It clarifies the parameter's purpose and typical usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: forward geocoding an address or place name to coordinates. It specifies the service (Nominatim, free, no key) and output fields (lat, lon, display_name, type, importance) with a result limit. It distinguishes itself from sibling 'reverse_geocode' by focusing on forward geocoding.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions that it uses Nominatim (free, no key), implying suitability for non-commercial use, but it does not explicitly state when to use this tool versus alternatives or provide exclusions. There is no guidance on alternative geocoding tools or scenarios where this might not be appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes the core behavior (indenting each line) but does not discuss edge cases like empty lines or special characters. No annotations exist, so the description bears full responsibility but remains adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences plus a parameter list; every word serves a purpose. No fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple text transformation tool with an output schema, the description covers the essential functionality. Minor omission: does not mention output format or handling of edge cases, but acceptable given simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All three parameters (text, count, char) are explained with their defaults and roles, adding significant meaning beyond the schema's field names and types. Schema coverage is 0%, so the description fully compensates.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it indents each line of text by a specified count of a character, which distinguishes it from sibling tools like pad_text (which adds padding) and wrap_text (which wraps lines).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this vs alternatives, but the purpose is straightforward and easily inferred from the description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full burden. It describes the standard edit operations (insert, delete, substitute) but does not disclose edge cases (e.g., empty strings) or performance considerations. Merely adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences plus a parameter list. No redundant information. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple function with two string inputs and a numeric output, the description fully explains what it does and what the parameters mean. The presence of an output schema further reduces the need to describe return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no description coverage (0%), so the description compensates by explicitly naming parameters and defining them ('The first string', 'The second string'). This adds meaning beyond the schema's bare type and title.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates Levenshtein distance between two strings and explains what it measures (number of single-character edits). The verb 'Calculate' and resource 'Levenshtein distance' are specific, and the explanation distinguishes it from general string comparison tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides usage context ('Use this to measure how many single-character edits are needed'), but does not explicitly mention when not to use it or suggest alternative tools for similar purposes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It describes calculations but lacks details on assumptions (e.g., fixed rate, no fees) or side effects. For a read-only computation tool, it is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: one line for purpose, then a clear bullet list of three parameters. No wasted words; front-loaded with the most important info.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
All three parameters are described, outputs (payments, total interest, schedule) are listed. An output schema exists, so return format detail is not needed. Complete for a simple calculation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, but the description adds clear meanings: 'Loan amount', 'Annual interest rate (e.g. 5.5 for 5.5%)', 'Loan term in months.' This compensates well for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool calculates loan payments, total interest, and full repayment schedule. This specific verb+resource distinguishes it from siblings like amortization_calc or simple_interest_calc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides parameter explanations but no explicit guidance on when to use this versus alternatives (e.g., simple_interest_calc, mortgage_calculator). Usage is implied, but no exclusions or comparisons are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It lists operations and parameter roles but omits behavioral details such as error handling, matrix dimension constraints, or return format. Adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the core purpose, followed by a clean parameter list. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description covers purpose and all parameters. Some missing context (e.g., dimension constraints) but overall sufficient for a moderate-complexity tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema description coverage, the tool description provides clear descriptions and examples for all three parameters: operation values, matrix_a format, and matrix_b optionality. This fully compensates for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool performs matrix operations and lists four specific operations: add, multiply, transpose, determinant. This clearly distinguishes it from sibling tools, none of which are matrix-specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives, but the sibling list implies it's unique for matrix operations. Lacks when-not-to-use or alternative tool references.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the core behavior (validation) but does not mention side effects (none expected), return format (covered by output schema), or error handling (e.g., exception on invalid JSON). The output schema partially compensates, but the description could add more behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short (two sentences plus parameter list) and front-loaded with the main purpose. It avoids unnecessary detail, but the parameter list could be integrated more smoothly. Overall, it's efficient but not maximally concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description need not explain return values. It covers the essential input semantics and purpose. However, for a validation tool, mentioning that it returns validation errors or success could aid understanding. Still, it is reasonably complete for its simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description is essential. It adds one-line explanations for both parameters: 'json_str — JSON string to validate' and 'schema — Optional JSON Schema to validate against.' This provides clarity beyond the bare schema, though it doesn't elaborate on acceptable formats or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool validates JSON syntax and optionally against a JSON Schema. It uses specific verbs ('validate') and resources ('JSON string'), and it distinguishes itself from sibling tools by being the only JSON validation tool in the list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies two use cases: syntax-only validation (without schema) and full validation (with schema). However, it lacks explicit guidance on when to prefer this tool over alternatives, though no direct sibling competes. The 'optionally' keyword gives a clue but no definitive when-to-use or when-not-to-use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, so description carries burden. Describes input formats and output format options but lacks details on error handling, timezone, or invalid input behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short paragraphs, front-loaded with purpose, then parameter details. No filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Simple tool; description covers key usage. Missing description of return format (likely depends on format param) but output schema may provide it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage 0%, so description compensates with concrete examples of acceptable formats for 'value' and common values for 'format'. Adds meaning beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it converts between Unix epoch and human-readable date formats. Distinct from sibling conversion tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use: translate Unix timestamps to ISO 8601 or date strings back to Unix timestamps. No negative cases but clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description must detail behavior. It describes what is looked up but omits behavioral aspects like read-only nature, rate limits, authentication needs, or error conditions. Adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two paragraphs, first sentence hits main purpose, parameter described with bullet. No wasted words, but could be slightly more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple nature of the tool and presence of an output schema, the description fully covers the input and expected output (DNS records and SSL info). No gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'domain' has 0% schema coverage, but the description adds an example format ('example.com') and clarifies it's a domain name, adding value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Explicitly states it looks up DNS records (A, AAAA, MX, NS, TXT, CNAME) and SSL info. Distinguishes from siblings like dns_whois_lookup and check_ssl_certificate by combining both DNS and SSL in one tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear use cases: domain research, troubleshooting, infrastructure verification. However, does not explicitly mention when not to use it or suggest alternatives for specific tasks (e.g., reverse DNS).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the tool encodes/decodes and mentions the default mode, but does not disclose error handling, padding behavior, or return format. The output schema likely covers return structure, but behavioral details are minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with purpose. Every sentence contributes value: purpose, use case, and parameter details. No fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description covers essential aspects: purpose, parameters, and typical use. Minor omission: no mention of input validation or case sensitivity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It explains both parameters: text (required string) and mode (defaults to 'encode', with values 'encode' or 'decode'). This adds meaning beyond the schema's bare titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool encodes or decodes text using Base32 encoding, with a specific verb and resource. It distinguishes itself from sibling tools like encode_base64 by noting it uses only A-Z and 2-7, making it suitable for human-readable tokens.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context for when to use Base32 encoding (compact, case-insensitive, human-readable) and compares it to Base64. However, it does not explicitly mention when not to use it or list alternative encoding schemes like Base32hex.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral transparency. It states the operation is a flip, which is non-destructive and returns results. No contradictions exist. It does not mention randomness quality, but that is implied.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences, front-loading the purpose and then detailing the parameter. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema (which explains return values), the description is complete enough. It covers the purpose and parameter fully, though it could mention that multiple coins return a list of results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description defines the count parameter as 'Number of coins to flip' with a default of 1, adding meaning beyond the schema. Since schema coverage is 0%, the description fully compensates for the single parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: flipping one or more coins to get heads/tails results. It specifies the verb 'flip' and resource 'coins', and distinguishes from sibling random tools like roll_dice or random_color by being coin-specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide explicit guidance on when to use this tool versus alternatives (e.g., roll_dice for dice, generate_random_numbers for numbers). The context of coin flipping is clear, but no when-not-to-use suggestions or sibling comparisons are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses parameters and defaults but lacks details on behavioral traits like randomness or reproducibility. Adequate for a simple generation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Concise and well-structured: one sentence for purpose, one for usage, then clear parameter list. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, usage, and parameters adequately. Output schema exists, so return values are not needed. Minor gap: no mention of edge cases or error behavior, but acceptable for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With schema coverage at 0%, the description effectively explains both parameters, including allowed values for 'type' ('paragraphs', 'sentences', 'words') and range for 'count' (1-100). Adds value beyond schema defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates Lorem Ipsum placeholder text, with a specific verb ('Generate') and resource. It distinguishes itself from other text generation tools (e.g., generate_random_data) by specifying the type of text.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear usage scenarios (mockups, wireframes, design drafts) but does not explicitly state when not to use or list alternatives among other text tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It mentions defaults and customizability but lacks details on randomness source, security, or performance. For a simple ID generator, it adequately discloses behavior but could be more thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loaded with purpose, and structured with a clear parameter list. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 optional params, no required), the description covers purpose, usage, and parameter details. With an output schema present, the return format is not needed. Minor missing details like error handling don't detract significantly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description adds significant value by explaining both parameters: length (default 21) and alphabet (custom string, default A-Za-z0-9_-). This goes beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Generate Nano ID strings' and explains they are compact, URL-safe unique identifiers. It differentiates from siblings like generate_uuid and generate_password by emphasizing URL-friendly, collision-resistant, and customizable properties.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description advises using for 'short unique IDs suitable for URLs, tokens, or database keys,' providing clear context. However, it does not explicitly exclude alternatives like UUIDs or offer direct comparisons, though the properties imply the niche.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It describes the output as Base64-encoded data and explains default parameter values. However, it does not explicitly state that the tool is read-only or has no side effects, nor does it mention any prerequisites or limitations beyond parameter ranges.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear summary, usage note, and parameter list. It is appropriately sized with no superfluous text, though the parameter list could be condensed slightly without loss of clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 7 parameters and an output schema exists, the description adequately covers input details and mentions the return format (Base64-encoded data). It does not need to explain the output schema further since that is provided separately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must fully explain parameters. It does so comprehensively: for each of the 7 parameters, it provides the data type, default value, allowed values or ranges, and a brief explanation (e.g., 'ECC – Higher levels allow more damage before the code becomes unreadable'). This adds significant meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Generate a QR code image and return it as Base64-encoded data', providing a specific verb (generate) and resource (QR code image). This clearly distinguishes it from all sibling tools, none of which generate QR codes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use this when you need to encode a URL, text, or other data into a QR code image that can be displayed or embedded in documents/web pages.' This gives clear context for when to use the tool, though it does not explicitly mention when not to use it or provide alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description covers the core behavior (calculations) and parameter format but does not disclose any side effects, permissions, or output specifics. It is adequate but lacks depth beyond the basic functionality.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loaded with purpose, and efficiently structured with a clear overview, usage context, and parameter details. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description covers the essential aspects: what it does, how to use it, and parameter details. It could be more exhaustive (e.g., listing all shapes and exact dimension requirements) but is sufficient for its purpose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, so the description adds substantial value by naming the parameters, listing allowed shape values, and providing examples of dims JSON format. This compensates well for the schema's lack of description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates 'area, perimeter, or volume for common geometric shapes' and provides specific examples like rectangles, circles, triangles, etc., distinguishing it from sibling tools that focus on other types of calculations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use this for quick geometry math' and lists supported shapes, giving clear context. However, it does not explicitly state when not to use it or mention alternatives, leaving a slight gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It transparently explains the underlying API (Open-Meteo, free, no key) and the geocoding step, and lists the returned pollutants. It does not mention rate limits or error handling, but the key behavioral traits are covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences plus a param line. Every word adds value, and the most important information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the single parameter and existence of an output schema, the description adequately covers what the tool does and returns. It mentions the API source and data points. Minor missing details about geocoding failures or return format could be included, but overall it is sufficient for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates well by explaining the 'city' parameter as a required city name with an example ('London'). This adds meaning beyond the schema's bare 'string' type.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets current air quality data for any city, specifying the output (European AQI, US AQI, PM2.5, etc.). It is specific and distinct from sibling tools like get_weather or get_forecast.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly guide when to use this tool over alternatives. It implies use for air quality queries but offers no exclusions or comparisons to similar tools, leaving the agent to infer context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses external API dependencies and response elements (temps, precipitation, weather codes), but lacks details on error handling (e.g., unrecognized city) or rate limits. No annotations present, so description carries burden.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise paragraphs, front-loaded with main purpose, no redundant sentences. Efficiently structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, parameter details, and dependencies. Output schema likely provides return format details, so missing response structure is acceptable. Minor omission: no mention of error cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Adds meaning to the single parameter 'city' with a description and example ('e.g., 'London''), compensating for 0% schema description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb 'Get', specific resource '7-day weather forecast', and scope 'any city'. Distinguishes from sibling 'get_weather' by specifying duration and free API source.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
States when to use (free, no API key) and explains geocoding dependency, but does not explicitly list when not to use or compare with alternatives like 'get_weather'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes what data is extracted but does not disclose limitations, error behavior, or performance characteristics. No annotations provided, so description carries burden; it is adequate but not exhaustive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Concise at three sentences, front-loaded with purpose, then usage, then parameter details. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema presumably available, and one simple parameter, description covers purpose, usage, and parameter adequately for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single 'url' parameter is explained with a clear example and usage context. Schema provided no parameter description, so description compensates well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states extraction of Open Graph metadata, title, description, and favicon from a URL. Distinguishes from sibling tools like 'scrape_meta_tags' by focusing specifically on OG metadata for link previews.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit use cases: link previews, content summarization, social media card extraction. Does not mention when not to use or alternatives, but context is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It states the tool produces a 'cryptographic hash' (one-way), but does not disclose additional behavioral traits such as determinism, performance characteristics, or limitations (e.g., unsuitability for password storage without salting). The description is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: a single purpose sentence, a brief usage paragraph, and bullet-like parameter descriptions. Every sentence adds value, and the structure makes it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the core functionality and usage scenarios. Since an output schema exists, the description does not need to explain return values. It does not mention edge cases (e.g., empty text or invalid algorithm), but for a straightforward hash function, this is acceptable. Minor gap in explaining the relationship to sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds significant meaning: it explains each parameter (text required, algorithm options with recommendations, encoding options with defaults). This goes beyond the schema's raw type definitions, providing context like 'SHA-256 and SHA-512 are recommended for security-sensitive use.'
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Generate a cryptographic hash of input text' and distinguishes from sibling tools like compare_hashes by focusing on one-way hashing. The specific verb 'generate' combined with 'cryptographic hash' leaves no ambiguity about the tool's function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit use cases: 'password hashing, data integrity checks, digital signatures, or any scenario requiring a one-way hash.' While it does not explicitly exclude inappropriate uses, it strongly implies usage context. Alternatives are not named but are implicitly distinct (e.g., compare_hashes for comparing precomputed hashes).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Discloses basic conversion behavior and root parameter default, but does not mention error handling for invalid JSON, encoding, or output structure details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Description is two sentences plus parameter list, front-loaded with purpose. Every sentence adds value with no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations but presence of output schema, description covers purpose, parameters, and use cases. Missing error handling or output format hints, but overall complete for a simple conversion tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but description adds meaning to both parameters: json_str as 'the JSON string to convert' and root as 'name of the root XML element (default: 'root').' No constraints like valid JSON mentioned, but adds clear semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Convert a JSON string to XML format' and specifies use cases for legacy systems, SOAP APIs, and configuration files. Implicitly distinguishes from sibling xml_to_json by focusing on JSON-to-XML direction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use: 'when you need XML output from JSON data for legacy systems, SOAP APIs, or configuration files.' Does not mention when not to use or explicitly name alternatives, but context is sufficient for typical use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It states the tool is for lookups, implying it is read-only and non-destructive, but does not explicitly mention safety, side effects, or any required permissions. This is adequate for a simple read operation but lacks details like rate limits or data freshness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences followed by a parameter list. The key information is front-loaded. The parameter list is somewhat redundant with the schema but does not detract. It could be slightly more structured (e.g., separating usage notes), but overall it is efficiently written.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists (not shown), the description does not need to explain return values. The tool is simple—a single optional parameter with a clear default behavior. The description sufficiently covers input semantics and result expectations for a lookup tool, and the context signals indicate no additional complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, but the tool description adds meaning to the 'entity' parameter by calling it a 'Search term' and contextualizing it with the purpose description that mentions 'name, code, or character.' It also explains the behavior when the parameter is left empty. This adds significant semantic value beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Look up HTML entities by name, code, or character.' It also specifies the behavior when the parameter is empty ('Leave empty for full list'), which defines the scope and differentiates from sibling tools that are unrelated to HTML entity lookup.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides guidance on when to use the tool (for HTML entity lookups) and gives a specific usage instruction: leaving the parameter empty returns the full list. However, it does not explicitly mention when not to use it or provide alternatives, which is acceptable given the specificity of the tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It explains the operations but does not disclose any behavioral traits such as precision, error handling, or edge cases. For a simple calculator, this is adequate but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: a one-sentence purpose followed by a clear, bulleted parameter list. Every sentence adds value without unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 4 parameters and an output schema (not shown), the description covers all necessary input semantics. It could be slightly richer (e.g., clarifying that both total and percent are not both required), but it is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning beyond the input schema by explaining the valid values for 'operation' ('of' or 'what') and specifying when 'total' and 'percent' are required. This compensates for the 0% schema description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Calculate percentages: find what % X is of Y, or what is X% of Y.' The name also reinforces this, making it distinct from sibling calculator tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the two operations ('of' and 'what') and which parameters are required for each. It provides clear context for when to use each mode, though it does not explicitly exclude other tools or mention when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry the full burden. It describes actions but does not disclose behavioral traits such as randomness source, potential side effects (none), or edge cases (e.g., non-positive sides or count). The existence of an output schema partially compensates, but more transparency would be beneficial.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core action in the first sentence, followed by a clean parameter list. Two sentences and no wasted words; every part earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with an output schema, the description is complete. It covers purpose, parameters, and defaults. No additional context is needed given the tool's low complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explains both parameters in natural language (sides and count) with default values, adding significant meaning beyond the input schema which only provides type and default. Schema description coverage is 0% but the description fully compensates, making parameter semantics excellent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Roll one or more dice with specified number of sides,' which is a specific verb+resource combination. It distinguishes itself from sibling tools like flip_coin by explicitly mentioning dice.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance is provided. The usage is implied from the description but alternatives among siblings are not discussed. For a simple tool this may suffice but better would be to mention it's for dice simulation not general random number generation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It describes the calculation but lacks warnings about edge cases (e.g., vertical line when x1=x2) or return format. Basic but adequate for a pure calculation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences plus a clean list. Every sentence adds value, no redundancy. The structure is easy to scan and well-organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with 4 required parameters and no nested objects, the description covers the main functionality. Missing edge case handling but acceptable. Output schema may define return values, so completeness is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema descriptions are missing (0% coverage), so the description provides all parameter meaning. Each parameter is explained with coordinate roles, adding significant value beyond the schema titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates slope, intercept, and equation from two points. Uses specific verb 'calculate' and resource 'slope, intercept, equation'. No sibling tools overlap, so no differentiation needed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The purpose is clear and implies usage context. No explicit when-to-use or alternatives are needed because no sibling tool performs the same function. However, it could be improved by adding explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the burden. It states it 'return all matches' but does not discuss behavior like what happens with invalid patterns or performance. Adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with two short paragraphs. The first clearly states purpose and return, the second lists parameters. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (implied by 'has output schema: true'), the description appropriately focuses on input and purpose. It covers matching groups and verification. Could mention regex flavor, but not essential.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description separately explains each parameter: regex (pattern with example), text (text to test), flags (default 'g'). Adds meaningful context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool tests a regular expression against text and returns all matches, using a specific verb ('Test') and resource ('regular expression'). It distinguishes from sibling tool 'regex_escape' which escapes regex patterns.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit use cases: 'debug regex patterns, extract matching groups, or verify patterns before using in your code.' It does not mention when not to use it or alternatives, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It mentions returning each differing line with old/new values but omits details like max text length, encoding, or whitespace handling. Adequate but not exhaustive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (5 lines) and well-structured, with a clear purpose sentence followed by usage guidance and parameter explanations. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (not shown), the description adequately covers input and return behavior. It specifies line-by-line output with old/new values, sufficient for a text diff tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds meaning by naming parameters 'text_a' and 'text_b' with clear roles ('before' and 'after' versions). This compensates for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Compare' and resource 'two texts', specifying line-by-line differences. It is distinct from sibling tools as no other diff tool exists.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly says 'Use this to find what changed between document versions', providing clear context. No when-not or alternatives are needed given no sibling diff tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It describes the input (TOML string) and output (JSON) but does not discuss error handling, encoding issues, or limitations. For a simple conversion, the transparency is adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise: two sentences plus a parameter note. It front-loads the core purpose and provides a concrete example. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the input sufficiently. Since an output schema exists (as per context signals), the description need not explain return values. For a straightforward conversion tool, it is complete enough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The parameter 'toml' is described as 'TOML-formatted string to convert', adding meaning beyond the schema which only provides the title. Since schema coverage is 0%, the description fully compensates for the missing schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the verb 'convert' and the resources 'TOML format to JSON'. It distinguishes itself from siblings like ini_to_json or convert_csv_to_json by specifying the format. The use case example further clarifies the tool's purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use this to transform TOML configuration files (e.g. pyproject.toml) into JSON for programmatic access', which provides clear context when to use. While it doesn't mention when not to use, the sibling tool list implicitly provides alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It states it expects TSV text with header row and produces JSON arrays, but lacks details on edge cases, error handling, or format strictness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: two sentences plus parameter explanation. The purpose is front-loaded, and every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one input, clear conversion) and existence of an output schema (not shown), the description is fairly complete. It mentions the output is 'structured JSON arrays', which is sufficient, though it could mention error conditions or format constraints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'tsv' has 0% schema description coverage, but the tool description compensates by explaining it is 'TSV text with header row and data rows (tab-separated)'. This adds meaningful context beyond the schema's type string.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Convert' and the resource 'TSV to JSON', and explains it transforms TSV text into structured JSON arrays. It distinguishes from sibling tool convert_csv_to_json by specifying TSV format.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says 'Use this to transform TSV data from spreadsheets or database exports', providing clear context. It does not explicitly mention when not to use or alternative tools, but the use case is well-defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It implies a read-only operation but doesn't explicitly state it's non-destructive or discuss error handling, rate limits, or response format. Minimal but adequate for such a simple tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Description is brief (4 sentences), front-loaded with the purpose, and each sentence adds value. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and presence of an output schema, the description covers purpose, usage context, and parameter details. It doesn't describe the output, but that is presumably handled by the output schema. Adequate for a basic check tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description adds meaningful detail for the sole parameter api_key: format ('gh_') and where to create one. This compensates for the lack of schema description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description states 'Check your wallet credit balance.' and 'see how many credits you have remaining.' This clearly identifies the action (check) and resource (wallet credit balance), distinguishing it from siblings like wallet_buy and wallet_create.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use (to see remaining credits) and mentions credits are used for AI tools, guiding context. It also points to wallet_buy for purchasing more, providing an alternative but lacks explicit when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the creation of a wallet and API key, the key prefix 'gh_', and the optional email parameter. However, it lacks details on side effects, idempotency, or whether authentication is required, which are important for a setup tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences plus a single parameter line, with no unnecessary words. The main action is front-loaded, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool with one optional parameter and an existing output schema, the description covers the essential purpose and usage context. It could mention potential duplicate creation behavior, but overall it is complete enough for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must add value. It explains the 'email' parameter is 'Optional email address for payment receipts,' which provides meaningful context beyond the schema's type and title.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Create a new wallet and get an API key,' specifying the verb (create), resource (wallet), and output (API key). It distinguishes from sibling tools like wallet_balance and wallet_buy, which operate on existing wallets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use this to get started with the GadgetHumans credit system,' indicating this is the first step. While it does not explicitly list when not to use it or name alternatives, the context from sibling names is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It explains that the tool fetches the URL content, strips HTML tags (scripts, styles, nav, etc.), converts to markdown, has a 5-second timeout, and requires a valid API key. This is sufficient transparency for a simple scrape tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured with a clear overview, process details, and limitations. It uses bullet points for the parameter list, minimizing cognitive load. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has only one parameter and a straightforward behavior. The description covers input, process, constraints, and output format (markdown). An output schema exists, so detailed return value explanations are not necessary. Minor gaps include no mention of error handling or rate limiting.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides only the parameter name and type with no description (0% coverage). The description adds meaningful information: 'url — The full URL to scrape (e.g. 'https://example.com/page').' This explains what constitutes a valid URL, adding value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Scrape a URL and return clean markdown text.' It specifies the verb (scrape) and resource (URL), and distinguishes itself from siblings like scrape_meta_tags and read_url by emphasizing the markdown conversion and paid-only restriction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions that the tool is paid-only and requires an API key, and a 5-second timeout. However, it does not explicitly state when to use this tool versus other scraping or URL tools, nor does it provide exclusions or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that it returns decimal, hex, binary, and character values. It does not detail potential side effects, but since it's read-only, that's expected. No annotations exist, so the description carries the full burden, but it provides minimal extra behavioral context beyond the obvious.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single focused sentence plus a parameter note. It is front-loaded and concise with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with no parameters and an output schema, the description fully covers what the tool does and what it returns. No additional context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so baseline is 4. The description explicitly states 'no parameters needed', which adds clarity beyond the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get', resource 'complete ASCII table', and specifies the columns (decimal, hex, binary, character). This distinguishes it from sibling tools, none of which provide an ASCII table.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It indicates when to use (to get the ASCII table) but does not explicitly mention when not to use or provide alternative tools. However, given its simplicity, the implied usage is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, so description must cover behavior. Explains weekend skipping and defaults, but lacks details on return format, handling of invalid dates, or inclusion of holidays.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise, two short paragraphs plus a clear parameter list. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists (not shown) so description covers what's needed for usage. Could mention edge cases like negative days, but overall complete for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but description fully documents each parameter: date format and default, days default, direction options. Adds significant value beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool calculates business days by adding/subtracting working days that skip weekends. Distinct from siblings like 'calculate_date' which likely includes all days.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit use cases (project planning, SLA calculations) but does not mention when not to use or alternatives for calendar day arithmetic.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the use of Nominatim for geocoding and output in both kilometres and miles, providing reasonable behavioral context without annotations. It does not discuss failure modes or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loaded with the core purpose, and structured with a brief method explanation and parameter list. No redundant sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists, the description still covers inputs, method, and outputs (km and miles) sufficiently for a simple two-parameter tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning beyond the schema by providing examples (e.g., 'London', 'Paris') and clarifying that parameters are city names, compensating for 0% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies 'Calculate the great-circle (Haversine) distance between two cities' with geocoding via Nominatim, clearly differentiating from sibling tools like distance_2d that might operate on coordinates.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for city names but does not explicitly state when to use this tool versus alternatives or mention any exclusions (e.g., if coordinates are available).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full burden. It lists supported units and parameters but does not disclose error handling, precision, or behavior for invalid inputs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a clear overview followed by a parameter list. Every sentence adds value, no fluff, and the purpose is stated upfront.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers supported conversions and parameter details. An output schema exists but its content is unknown; however, the description adequately equips an agent to select and use the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, but the description explains each parameter's role and gives examples (e.g., 'c', 'm', 'kg'), adding significant meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Convert between measurement units: temperature, length, or weight' with specific examples, distinguishing it from sibling conversion tools like area_convert or volume_convert.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description advises 'Use this for quick unit conversions without lookup tables,' providing clear context for when to use this tool. However, it does not explicitly exclude usage or list alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Explains the encoding mechanism and overhead ratio, but does not disclose error handling, invalid input behavior, or output format details (e.g., delimiters, character set). Without annotations, description carries full burden.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Highly concise with a front-loaded purpose statement and clear parameter list. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers input parameters and encoding concept well. Lacks details about the output format (though output schema may exist) and error handling. Still fairly complete for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning beyond the schema by specifying the exact values for mode (encode/decode) and clarifying that text is the input string. Since schema has no parameter descriptions, this fully compensates and provides examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb (encode/decode) and resource (text) using Base85 encoding. It distinguishes from siblings like encode_base64 by mentioning improved efficiency and specifying the Ascii85 variant.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly recommends using this for efficient encoding over Base64, providing a clear use case. Lacks explicit guidance on when not to use or alternative scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions 'real-time' data and the source (Binance), but does not disclose potential side effects, rate limits, authentication requirements, or whether the data is cached. For a read-only price query, the transparency is moderate but could be improved.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured. It starts with the purpose, followed by usage context, and ends with parameter details in a clear list. Every sentence is necessary and adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema, the description does not need to detail return values, but it still mentions 'prices, 24-hour price changes, and market data.' It covers the parameter adequately. However, it could mention any limitations (e.g., number of symbols, availability of obscure coins) for full completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds substantial meaning beyond the input schema, which only has a string property with a default. It explains the format (comma-separated names or tickers), provides a clear default, and gives multiple examples. This fully compensates for the 0% schema description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves real-time cryptocurrency prices from Binance, specifying the verb 'get' and the resource (crypto prices). It distinguishes itself from sibling tools like convert_currency or wallet_balance by focusing on price data with 24-hour changes and market data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says when to use the tool (to check current crypto prices, 24-hour changes, and market data). It does not provide when-not-to-use guidance or mention alternatives, but the usage context is clear and sufficient for typical scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It describes what is returned but does not disclose any behavioral traits like data freshness, caching, or authentication requirements. For a simple listing tool, this is adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise with two short, clear sentences. No unnecessary words. The parameters section is redundant but not harmful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that no parameters are needed and there is an output schema (not shown), the description is sufficiently complete. It covers what the tool does without omissions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, and schema coverage is 100%. The description adds no parameter info, which is acceptable since none exist. Baseline for 0 params is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns a list of all currencies with specific fields (ISO codes, symbols, country usage). It distinguishes itself from siblings like list_countries or convert_currency.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description is clear on when to use it: to get a list of currencies. However, it does not explicitly mention when not to use it or suggest alternatives, but the purpose is unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, and description doesn't explicitly state read-only or side effects. However, as a list operation, it's reasonable to assume no mutation, but could be clearer.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with the essential information front-loaded. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Simple tool with output schema, so minimal description is adequate. Could hint at return format, but not required given output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but description adds complete enumeration of category values and clarifies default behavior ('leave empty for all'), compensating fully.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'Get' and resource 'list of emojis', with category filtering. Distinct from any sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Tells user to leave empty for all emojis and lists valid categories. Could be more explicit about when to use vs alternatives, but no sibling overlap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must bear the burden of behavioral disclosure. It states that the tool returns 'descriptions and categories,' implying read-only behavior. However, it does not detail any side effects, authorization needs, or rate limits. For a simple lookup, this is minimally adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences containing all necessary information. It is front-loaded with the tool's purpose and follows with parameter guidance. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, a single parameter, and the presence of an output schema (which likely documents the return format), the description is complete enough for an agent to understand and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, but the description adds essential meaning: 'code — HTTP status code (e.g. 404). Leave 0 for all codes.' This clarifies the parameter's purpose and usage beyond the schema's minimal type and default.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Look up HTTP status code descriptions and categories.' It uses a specific verb ('look up') and resource ('HTTP status code descriptions and categories'), and it is distinct from sibling tools which are mostly utilities for calculations, text processing, and data conversion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides usage guidance by explaining the parameter: 'code — HTTP status code (e.g. 404). Leave 0 for all codes.' This tells the agent when to use the tool (to get info on a specific code or all codes). It does not explicitly mention when not to use it or alternatives, but the context is clear for such a specific tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so description carries full burden. It discloses the masking behavior and keeps ends visible. It does not cover edge cases like very short text, but for a simple transformation, it is adequately transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise with a clear purpose statement followed by a bullet list of parameters. No superfluous information; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with 4 parameters and an output schema, the description covers input semantics well. It does not describe the return value, but the output schema exists to cover that. Could be slightly more complete by mentioning that output is a masked string.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description lists all parameters with explanations (e.g., 'text — Text to mask (e.g. email, credit card, phone)') and defaults. This compensates fully, adding meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Mask parts of sensitive text while keeping ends visible.' It uses a specific verb-resource pair and distinguishes from siblings by specifying the masking behavior and examples of text types (email, credit card, phone).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description implies usage by giving examples (email, credit card, phone) but does not explicitly state when to use this tool over alternatives or when not to use it. No guidance on selection among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the full burden. It explains the conversion direction but does not mention error handling, character set limitations, or other behavioral details. For a simple tool, this is adequate but could be improved.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: one sentence for purpose, one for usage, then a list of parameters. No unnecessary text, well-structured, front-loaded with the main purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists (not shown), the description doesn't need to explain return values. It covers both encode and decode modes, parameter details, and default values. It's complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% with no parameter descriptions, so the description adds value by explaining both parameters: 'text' as the string and 'mode' with explicit options and default. This clarifies usage beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Convert text to or from Morse code.' It specifies the resource (text and Morse code) and the action (encoding/decoding), distinguishing it from sibling text manipulation tools like Caesar or ROT13 ciphers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use the tool: 'Use this to encode text into dots-and-dashes Morse code, or decode Morse code back into readable text.' It provides clear context but does not mention when not to use it or alternatives, though no direct sibling tool exists.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does not disclose limitations (e.g., handling of numbers, special characters) or output format beyond the output schema. The behavior seems straightforward but lacks detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two short paragraphs and a parameter list. The purpose is front-loaded in the first sentence, making it efficient and easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple conversion tool with one parameter and an output schema, the description covers purpose, usage context, and parameter sufficiently. No critical gaps are present.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although schema coverage is 0%, the description explicitly names the parameter and clarifies its role ('The text to convert to NATO phonetic words'), adding meaning beyond the bare schema type.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts text to the NATO phonetic alphabet representation, using a specific verb and resource. This distinguishes it from sibling tools like morse_code or caesar_cipher.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear use case ('useful for clear radio/phone communication') but does not explicitly mention when not to use or suggest alternatives among sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the outcome (get a link) and pricing, but does not discuss authorization requirements or rate limits. Adequate for a simple tool but not deeply transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with four short sentences. The first sentence states the purpose, and subsequent sentences provide essential context. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and the presence of an output schema, the description fully covers the tool's purpose and pricing model. It is sufficiently complete for the agent to understand when and how to use it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so the description need not explain them. The baseline score of 4 applies as no additional parameter information is required.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it provides a link to buy credits for the wallet. It uses a specific verb 'Get a link to buy' and resource 'credits for your wallet', and distinguishes from sibling tools like wallet_balance and wallet_create by focusing on purchasing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use (to purchase credits) and provides context about cost and credit consumption. It lacks explicit when-not-to-use or comparison with alternative tools, but the context is clear for the intended use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Discloses cost (~1 credit per call) and return value contents (content, token usage, cost). Does not mention error handling or rate limits, which would improve transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Concise and well-structured: purpose, prerequisites, usage, then parameter details in bullet-like format. Every sentence adds value; no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters, output schema exists, and no annotations, the description covers purpose, prerequisites, cost, parameter details, and return value hints. It is sufficiently complete for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, description adds crucial details: messages must be valid JSON array string with at least one message, model default and options, temperature range, max_tokens default, and api_key format requirement. Greatly enhances understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool sends a chat completion request to a specific model (DeepSeek V4 Flash) through a proxy. This distinguishes it from sibling tools like 'summarize' or 'translate' which are different AI tasks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use ('get AI responses') and prerequisites (API key with credits, obtained via wallet_create or wallet_buy). Does not mention alternatives, but siblings don't compete directly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full burden. It notes 'secure random passwords' but lacks details about the random source, performance, or edge cases. Adequate for a simple generator but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a front-loaded purpose sentence followed by clear parameter definitions. No wasted words, every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, return values are covered. The description fully explains input parameters and the tool's function, making it complete for a password generator.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description explicitly lists all 6 parameters with ranges, defaults, and what values control (e.g., 'numbers — Include digits 0-9'), adding essential meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Generate one or more secure random passwords' and distinguishes this tool from sibling generators (e.g., generate_random_numbers, generate_uuid) by specifying the use case for passwords.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use this when a user needs a strong, random password — for account creation...', providing clear context. However, it does not mention when not to use or alternative tools for non-password random generation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the outputs (title, description, keywords, slug) and character constraints. It does not mention any side effects or risks, but the tool is inherently read-only (generates metadata) so no concerns.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (5 lines) and well-structured, using a clear list for parameters. Every sentence provides useful information with no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Even without an output schema shown, the description covers the main aspects. It could mention that the tool is non-destructive, but overall it is complete for a generative tool with simple inputs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description provides meaningful explanations for both parameters (url and topic) and clarifies that at least one is required. This adds significant value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states it generates SEO-optimized title, meta description, keywords, and slug, with specific character limits. It clearly identifies the verb (Generate) and resource (SEO metadata), distinguishing it from sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description advises 'Use this when publishing content' and explains the two parameters (url or topic). It does not explicitly state when not to use or provide alternatives, but the context is clear for a content publishing scenario.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It explains the tool pings each endpoint and returns a status report with UP/DOWN states, and notes it returns JSON. It lacks explicit mention of non-destructive nature but implies it via 'check' and 'verify'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with purpose. Every sentence adds value: purpose, usage context, return format. Could be marginally more concise but no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple health check tool with no parameters and an output schema (implied), the description is complete. It states what endpoints are checked, how result is returned (JSON summary), and usage context. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and schema coverage is 100% (empty schema). The description adds no parameter info, but baseline is 4 for 0 parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks health/availability of all 11 API Hub endpoints. It uses specific verb 'check' and resource 'health and availability', distinguishing it from sibling tools which are unrelated (e.g., age_appropriate, web_scrape).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use this to verify that the MCP server and upstream API hub are reachable', providing clear context for when to use. However, it doesn't mention when not to use or suggest alternatives, though for a health check this is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description implies a read-only operation with no side effects, but does not explicitly state that. However, since no annotations are provided and the tool is a data retrieval with an output schema, the description provides sufficient transparency about the returned data fields.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the purpose, and each sentence adds necessary information. There is no redundancy or extraneous text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters, output schema exists), the description is complete. It specifies what the list contains, leaving detailed return structure to the output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, and the description explicitly states 'no parameters needed', confirming the input schema. Schema description coverage is 100%, and the description adds the value of clarifying that no input is required.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a list of all countries with specific fields (ISO codes, calling codes, continent). It uses the verb 'Get' and resource 'list of all countries', distinguishing it from sibling list tools like list_currencies or list_languages.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The description is self-contained but does not mention limitations or when other tools might be more appropriate. For a simple, parameterless tool, this is minimally adequate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that data is stored in Cloudflare KV and persists indefinitely, and details the behavior of each action (get, set, delete). No annotations are provided, so the description carries the full burden; it does so adequately.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loads the main purpose, and uses bullet points for parameter details. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and the tool's simplicity, the description covers input semantics thoroughly. It could mention error handling or limits, but is complete for typical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description adds significant value by explaining each parameter's purpose, including conditional usage for 'value' and enumeration of 'action' with defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb (read/write) and resource (persistent agent memory across sessions), distinguishing it from stateless agent behavior. The tool's purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly advises using this tool when agents need persistent memory across sessions, contrasting with statelessness. It does not mention exclusions or alternative tools, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It explains the computation (years, months, days) and the optional 'as_of' parameter defaulting to today. No side effects or destructive behavior is relevant, and the description is transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences and a bullet list of parameters. It front-loads the purpose and efficiently conveys all necessary information without waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema (not shown), the description covers the core functionality. It could include a brief example or note about return format, but it is still adequate for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds essential meaning: birthdate is required and in ISO format, as_of is optional with default today. This goes beyond the schema's type and title, providing clear usage guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Calculate precise age from a birthdate' with a specific verb and resource. It distinguishes itself from sibling tools like 'calculate_bmi' or 'calculate_date' by focusing on age computation in years, months, and days.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use this to compute someone's age...' and provides context for when to use it. It does not explicitly state when not to use or name alternatives, but the purpose is clear enough given the tool's specific function.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It discloses that the tool returns pros/cons, comparison points, and a final verdict, which gives a good sense of behavior. It does not mention any side effects or limitations, but for a read-only comparison tool, this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, with a brief introductory sentence, usage guidance, and a clean parameter list. Every sentence is informative without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (2 string parameters, no enums, no nested objects) and the presence of an output schema, the description covers all necessary aspects: purpose, usage, and parameter semantics. It is complete for an agent to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, but the tool description compensates by adding parameter descriptions (e.g., 'item_a — First item to compare (e.g. "Herman Miller Aeron".'). This adds meaning beyond the schema's titles, helping the agent understand the expected format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('compare') and resource ('two products, services, or options'), clearly stating the output is a structured comparison with verdict. Among many siblings, only 'pros_cons' is remotely similar, but this tool is distinct in producing a side-by-side comparison with verdict.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly advises use for 'buying decisions, feature comparisons, or evaluating alternatives', providing clear context. However, it does not mention when not to use or list alternative tools, but the example usage is sufficient for guiding the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses non-verification of signatures, lists decoded parts (header, payload, signature), and mentions base64 decoding. Could add what happens on invalid input, but current detail is strong.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three short, front-loaded sentences with no redundancy. Every sentence adds value: purpose, usage note, parameter explanation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given output schema exists, return values are covered. Description includes purpose, usage, and parameter detail. Complete for a single-parameter tool with no additional complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% but the description adds a parameter description: 'token — The full JWT token string (3 dot-separated base64 parts).' This compensates by explaining the required format beyond the schema's simple type and title.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Decode a JWT token into its header, payload, and signature parts' with a specific verb and resource, clearly distinguishing it from siblings like 'encode_base64' or 'verify_jwt'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use this to inspect JWT tokens without verifying signatures', providing clear context and conditions. No when-not or alternatives are given, but it suffices for a simple inspect tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden. It explains that the tool computes the missing value from two provided ones. This is sufficient for a straightforward math tool, though edge cases (e.g., all non-zero) are not addressed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief (two sentences plus a parameter list) and front-loaded with the key purpose. Every line is necessary and adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists (not shown but present), the description does not need to detail return values. It covers the essential usage for a simple tool, though it could mention how to interpret the result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description must compensate. It explains each parameter (mass, volume, density) and the convention 'leave 0 if unknown,' which adds significant meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Calculate density, mass, or volume given any two values.' It uses a specific verb and resource, and the context of sibling tools (e.g., force_calc) confirms it is distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates when to use this tool: when two of the three values are known. It specifies to leave the unknown as 0, which provides clear guidance. However, it does not explicitly mention scenarios where all three are provided or negative values.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but description discloses generation behavior and parameter defaults. No side effects or contradictions; adequate for a simple generator.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences plus bulleted parameter list. Front-loaded with purpose, no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all essential aspects for a simple 2-param tool with output schema present. Could mention return format, but output schema compensates.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description compensates fully: explains 'type' with enumerated values and 'count' with default. Adds meaning beyond schema fields.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'generate' and resource 'random data' with explicit types (numbers, strings, booleans, dates, mixed), distinguishing it from sibling tools like generate_random_numbers or generate_lorem_ipsum.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Specifies use case 'for testing' and lists data types, giving clear context. Could explicitly mention when not to use or compare to siblings, but purpose is well-defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that omitting the IP returns the requester's own IP, and that data includes location, ISP, timezone. Could mention potential errors or data source, but acceptable for a simple lookup.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Efficiently structured: purpose, usage paragraph, parameter details. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers essential aspects: what the tool does, parameter details, default behavior, and typical use cases. Could mention error handling or support for IPv6, but sufficient for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explains the ip_address parameter with an example and default behavior ('If empty or omitted, returns data for the requester's own IP'), adding meaning beyond the schema's title and type.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Get geolocation data for an IP address' with specific verb and resource. Distinguishes from sibling tools like geocode (address to coordinates) and reverse_geocode (coordinates to address) by focusing on IP lookup.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear usage context: fraud detection, analytics, geo-targeting, debugging. Does not specify when not to use it or mention alternatives, but the use cases are well-defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses that it returns all sizes if no size given and provides dimensions in both mm and inches. Lacks mention of any limitations or side effects, but as a read-only lookup, this is acceptable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Description is extremely concise: 4 sentences with front-loaded purpose and a separate parameters section. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 param, no annotations, output schema exists), description covers key behaviors. Could mention that it supports both metric and imperial units explicitly, but overall sufficient for a lookup tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description compensates fully. It explains the 'size' parameter with concrete examples ('A4', 'Letter', 'Legal', 'B5', 'C4') and clarifies behavior for empty string. Adds significant meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states action ('Look up') and resource ('standard paper sizes') with specific series (ISO A, B, C, US). Distinguishes from sibling tools by being exclusively about paper sizes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use ('find dimensions in mm and inches') and behavior for empty parameter. Does not explicitly mention alternatives or when not to use, but context implies specialization.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, but description explains it returns feed metadata and up to 20 latest entries with specific fields. Could mention error handling or what happens if feed fails, but acceptable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise and well-structured: summary, usage advice, then parameter details. No wasted sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Has output schema so return format is covered. Description covers purpose, usage, and parameter. Could add error handling details but not necessary given output schema existence.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage for the url parameter; description provides full context: the URL of the feed with an example, compensating completely.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it parses RSS or Atom XML feeds into JSON with entries. Distinct from all sibling tools, none of which handle feeds.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says to use for monitoring news feeds, blog updates, or any RSS/Atom source. Does not mention alternatives or when not to use, but context is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that the tool returns emails, social links (with examples), and phone numbers. It does not mention limitations like dynamic content or rate limits, but for a basic extraction tool, the transparency is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with three sentences: a clear purpose statement, two usage contexts, and a parameter explanation. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the single parameter and presence of an output schema, the description adequately covers what the tool returns (emails, social links, phone numbers) and how to use it. No additional context is needed for a straightforward extraction tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the parameter 'url' lacks schema-level documentation. The description compensates fully by specifying it must be a full URL and providing an example, adding critical meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it extracts email addresses, social media links, and phone numbers from any URL. The verb 'extract' and the specific resource 'contacts' make the purpose unambiguous, and the tool is clearly distinguishable from siblings like 'extract_entities' or 'parse_phone_number'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly provides use cases such as lead generation, finding contact information on company websites, and researching business contacts. It does not specify when not to use the tool or mention alternatives, but the given contexts are clear and sufficient for typical usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It explains parameter behavior (inclusive ranges, default values, uniqueness option) but does not disclose return format or performance characteristics. Since randomness is inherently non-destructive, the description adequately covers behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured. The first sentence states the core purpose, followed by usage context. Parameters are listed clearly with defaults, each earning its place. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema (not shown), the description is complete. It defines all parameters and provides usage context. The sibling tools include many random generators, but the description sufficiently distinguishes this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides clear, detailed semantics for each parameter: min (inclusive, default 0), max (inclusive, default 100), count (how many, default 1), unique (whether unique, default false). This adds significant value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates random numbers within a range and provides concrete examples (dice rolls, lottery, sampling). The verb 'generate' and resource 'random numbers' are specific, distinguishing it from sibling random generators like flip_coin or generate_password.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use the tool ('when you need one or more random integers for dice rolls, lottery numbers, sampling, or any randomized selection'). It does not specify when not to use it or mention alternatives, but for a simple tool, this is sufficient guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It states the behavior (generation of ULIDs), properties (26-character, URL-safe, sortable), and the count parameter. No side effects or destructive actions exist, but it could mention idempotency or uniqueness guarantees.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: two sentences and one bullet point. It front-loads the main purpose, provides usage context, and details the parameter efficiently with no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, output schema exists), the description covers everything needed: what it does, when to use, and parameter details. The output schema handles return format, so the description is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description explicitly explains the 'count' parameter: its purpose, default value (1), and effect. This adds significant meaning beyond the schema's type and default.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Generate' and the resource 'ULIDs', and distinguishes from siblings by specifying the unique property of ULIDs (lexicographically sortable with timestamp). It also briefly explains what ULIDs are, leaving no ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use this when you need sortable unique identifiers that encode a timestamp', providing clear context for when to choose this tool. It does not explicitly exclude alternatives but the mention of sortability differentiates it from siblings like generate_uuid.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description clearly states behavior: maps date to season with hemisphere option. Defaults are mentioned. No annotations exist, so description carries full burden; it is sufficient though could mention output type (but output schema handles that).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two succinct sentences plus a parameter list. Front-loaded with purpose. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and presence of an output schema, description covers all needed aspects: what it does, parameters, defaults. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% coverage, but description fully explains both parameters: date format and default, hemisphere options and default. Adds meaning beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Determine') and specific resource ('astronomical season'). It clearly distinguishes from siblings like get_week_number or calculate_date by stating the exact output (season name) and hemispheres.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use: 'Use this to find which season a date falls in...'. No alternative or when-not-to-use guidance is needed since no sibling tool performs this function.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description adequately discloses the tool is a non-destructive calculator. It lacks edge-case handling but is sufficient for a simple physics calculation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with only three sentences, no wasted words, and front-loads the core purpose and formula. Parameter list is well-organized and readable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema shown, the context confirms its existence. The description fully covers the input behavior for a 3-parameter calculator, making it complete for its complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema property descriptions are empty (0% coverage), but the tool description fully explains each parameter (mass in kg, velocity in m/s, momentum in kg·m/s) and the convention of leaving unknown as 0, adding significant meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Calculate momentum, mass, or velocity using p = mv', clearly identifying the tool's function and the physical formula. This distinguishes it from sibling tools like force_calc or kinetic_energy_calc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains that parameters should be left as 0 if unknown, implying exactly two values must be provided to compute the third. It provides implicit guidance but could explicitly state the usage rule.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the tool's behavior (solving proportions) without side effects. No annotations are provided, but the simple nature of the tool makes its behavior transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one clear sentence followed by a bullet-like list of parameters. Every sentence is necessary and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple calculator with an output schema, the description provides all needed information to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description explains each parameter (a, b, c, d, solve) with roles and defaults, adding significant meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool solves proportions (find missing term in a:b = c:d). It uses a specific verb and resource, and is distinct from sibling tools which are other calculators.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Though no explicit when-not is given, the description explains parameter usage (a, b, c, d, solve) and defaults. It is clear how to use the tool, and siblings don't overlap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully describes the tool's behavior: it uses Nominatim, returns display name, structured address components, and OSM identifiers. However, it does not mention rate limits, terms of use, or what happens on error, which would elevate transparency further.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and well-structured. It starts with a clear purpose statement, then lists parameters in a readable format. Every sentence adds value, and there is no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (2 required numeric parameters) and the presence of an output schema, the description is fully complete. It explains what the tool does, what it returns, and the data source, leaving no critical gaps for an AI agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries the full burden. It clearly explains each parameter: lat and lon, indicating they are required and providing example values (e.g., 51.5). This adds significant meaning beyond the bare schema definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Reverse geocode coordinates to a human-readable address.' It uses a specific verb-resource pair, distinguishes from sibling 'geocode' (forward geocoding), and provides concrete examples of output components.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions the underlying service (Nominatim, free, no key) and lists required parameters with examples. While it does not explicitly contrast with siblings like 'geocode', the differentiation is implicit due to the reverse vs. forward distinction. A slightly more explicit 'when to use' statement would push it to 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It accurately describes the tool's behavior as encoding or decoding. However, it could specify the encoding scheme (e.g., standard URL encoding) and whether it handles all characters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, using only a few sentences to convey purpose and parameters. No unnecessary text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and the presence of an output schema, the description is complete. It covers purpose, parameters, and usage context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema description coverage, the description fully explains both parameters: text as the string to encode/decode, and mode with default and options. This adds meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool encodes or decodes URL/URI strings, distinguishing it from related tools like url_parse. It uses a specific verb and resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear usage context: 'Use this to safely encode special characters for URLs or decode percent-encoded URL strings.' It mentions default mode but does not explicitly exclude alternatives or when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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