Hi-AI

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation2/5
Multiple tools have overlapping purposes that could cause confusion, such as analyze_problem, break_down_problem, and step_by_step_analysis all focusing on problem decomposition; enhance_prompt and enhance_prompt_gemini both targeting prompt improvement; and analyze_prompt, analyze_requirements, and generate_prd all dealing with requirements analysis. While descriptions provide some differentiation, the boundaries between these tools are unclear, leading to potential misselection.
Naming Consistency4/5
The tools mostly follow a consistent verb_noun naming pattern (e.g., analyze_complexity, create_user_stories, delete_memory), which is predictable and readable. There are minor deviations like auto_save_context (which uses a hyphen-like structure) and start_session (which is more imperative), but overall the naming is coherent and follows a clear convention throughout the set.
Tool Count2/5
With 36 tools, the count feels excessive for a general-purpose AI assistant server, leading to potential cognitive overload and redundancy. While the domain is broad (covering analysis, memory, coding, etc.), many tools could be consolidated (e.g., multiple analysis tools), making the surface heavy and less scoped than ideal for efficient agent use.
Completeness3/5
The tool set covers a wide range of domains like analysis, memory management, coding, and UI, but there are notable gaps in lifecycle coverage. For example, in memory operations, there are save, delete, update, list, search, and recall tools, which is fairly complete, but in analysis, there is no clear update or delete for generated artifacts like PRDs or roadmaps. The surface is functional but not fully cohesive for end-to-end workflows.
Average 2.5/5 across 36 of 36 tools scored. Lowest: 1.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
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.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only provide a title, so the description carries full burden for behavioral disclosure. It fails to describe what the analysis does (e.g., outputs prioritization, insights), any side effects, or operational constraints. No contradictions with annotations exist, but the description is insufficient for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness1/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is repetitive and poorly structured, with redundant phrases ('requirements analysis|what we need|requirements analysis|what we need|analyze requirements|essential features') that add no value. It lacks front-loading of key information and wastes space without improving clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and minimal annotations, the description is incomplete. It does not explain what the analysis produces (e.g., prioritized list, insights), leaving the agent uncertain about the tool's purpose and results. For a 4-parameter tool with behavioral ambiguity, this is inadequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, providing clear parameter documentation. The description adds no parameter-specific information beyond what the schema already states. Baseline score of 3 applies as the schema adequately covers parameter semantics without additional value from the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description is tautological, repeating the tool name ('analyze requirements') without specifying what analysis entails. It adds redundant phrases ('requirements analysis', 'what we need', 'essential features') but fails to articulate the actual function or output. No distinction from sibling tools like 'analyze_complexity' or 'analyze_problem' is provided.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does 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 is given. The description does not mention context, prerequisites, or exclusions. With sibling tools like 'analyze_complexity' and 'analyze_problem', the lack of differentiation leaves the agent without direction on tool 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 beyond a basic title, so the description carries full burden for behavioral disclosure. The description only vaguely suggests applying rules/standards but doesn't reveal whether this is a read-only analysis, a mutation that changes code, whether it requires specific permissions, what the output format might be, or any rate limits. For a tool with no annotation coverage, this leaves critical behavioral traits undisclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness1/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is poorly structured and repetitive with phrases like 'apply rules|apply standards|apply rules|apply standards|follow conventions|apply' that don't form coherent sentences. It appears to be keyword stuffing rather than meaningful content. This wastes space without providing useful information and fails to be front-loaded with clear purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no output schema and minimal annotations (only a title), the description should provide more complete context about what the tool actually does and returns. The current description is completely inadequate - it doesn't explain what 'quality rules' are, what resources they're applied to, what the expected outcome is, or any behavioral characteristics. For a tool with 2 parameters and no output documentation, this leaves too many gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both parameters having clear descriptions and enum values in the schema. The description adds no additional information about parameter meaning, constraints, or usage beyond what's already documented in the schema. With high schema coverage, the baseline score of 3 is appropriate since the schema does the heavy lifting for parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description is a tautology that essentially restates the tool name 'apply_quality_rules' with repetitive synonyms like 'apply rules', 'apply standards', 'follow conventions'. It doesn't specify what quality rules are being applied, to what resources, or what the actual outcome is. While it suggests applying rules/standards/conventions, this is too vague to distinguish from sibling tools like 'validate_code_quality' or 'get_coding_guide'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance on when to use this tool versus alternatives. There's no mention of context, prerequisites, or comparison to sibling tools like 'validate_code_quality' or 'get_coding_guide' that might serve similar purposes. The agent receives no help in deciding when this specific tool is 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 carries the full burden of behavioral disclosure. The description only repeats the tool's purpose without explaining how it behaves—such as whether it searches recursively, returns multiple matches, handles partial names, or provides error messages. This leaves significant behavioral gaps for a tool with 3 parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is repetitive and poorly structured, with redundant phrases like 'find function|where is class|variable location|find function|where is|locate'. It lacks front-loading of key information and wastes space on synonyms instead of providing useful content, making it inefficient despite its brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 parameters, no annotations, no output schema), the description is incomplete. It fails to explain what the tool returns, how results are formatted, or any behavioral nuances, leaving the agent with insufficient context to use the tool effectively beyond basic parameter input.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with clear descriptions for all parameters, including an enum for 'symbolType'. The description adds no additional meaning beyond what the schema provides, so it meets the baseline score of 3 for high schema coverage without compensating value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description is a tautology that essentially restates the tool name 'find_symbol' with synonyms like 'find function', 'where is class', 'variable location', and 'locate'. It doesn't specify what the tool actually does beyond the name, nor does it distinguish this tool from its sibling 'find_references' which appears to serve a related purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does 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 provides no context about appropriate use cases, prerequisites, or comparisons to sibling tools like 'find_references', leaving the agent with no usage 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?
Annotations only provide a title, so the description carries full burden. It fails to disclose key behavioral traits: whether this is a read-only operation, if it requires specific permissions, what the output looks like (e.g., real-time monitoring vs. historical analysis), or any side effects. The vague 'inspect' doesn't clarify if it passively observes or actively intercepts requests. No contradictions with annotations exist, but the description adds minimal value beyond the title.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is poorly structured and repetitive ('network|API calls|check requests' appears multiple times), wasting space without adding clarity. It's not front-loaded with key information; instead, it's a jumbled list of synonyms. While brief, it fails to be concise in a useful way—each repetition doesn't earn its place, making it inefficient rather than succinct.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 parameters, no output schema, minimal annotations), the description is inadequate. It doesn't explain what 'inspect' entails operationally, what the tool returns, or how it integrates with the broader context of sibling tools. Without output schema or rich annotations, the description should provide more context on behavior and results, but it falls short, leaving significant gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents parameters (url, filterType, includeHeaders). The description adds no meaning beyond this—it doesn't explain how parameters interact (e.g., how filterType applies to the URL) or provide usage examples. Baseline 3 is appropriate as the schema does the heavy lifting, but the description doesn't compensate with any additional insights.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description is tautological, essentially repeating the tool name with slight variations ('network|API calls|check requests|network traffic - Inspect network requests'). It doesn't specify what 'inspect' means operationally (e.g., monitoring, logging, analyzing) or what resource is being inspected beyond the vague 'network requests'. While it mentions 'network traffic', it doesn't clearly distinguish this from sibling tools like 'monitor_console_logs'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does 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 doesn't mention any context, prerequisites, or exclusions. Given sibling tools like 'monitor_console_logs' that might overlap in monitoring functionality, the lack of differentiation is a significant gap. There's no indication of when this tool is appropriate or what problems it solves.
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 only provide a title ('Think Aloud'), so the description carries full burden. It states the tool 'generates' something but doesn't specify what format the output takes (text stream? structured reasoning? internal process?), whether this is purely internal thinking or produces user-visible output, or any behavioral constraints. The description adds minimal value beyond the name/title.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a jumbled string of synonyms and examples ('think about|consider|what do you think|think about it|let me think|reasoning') followed by a dash and the core function. This format is inefficient and lacks clear structure. While brief, it's poorly organized rather than concisely informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 3 parameters, no output schema, and minimal annotations, the description is inadequate. It doesn't explain what 'think-aloud reasoning process' means in practice, what format the output takes, or how this differs from other reasoning tools on the server. The agent would struggle to understand what this tool actually produces.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the schema already documents all three parameters well. The description adds no additional parameter information beyond what's in the schema. The baseline of 3 is appropriate when the schema does the heavy lifting, though the description doesn't compensate with any usage examples or context for the parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'think about|consider|what do you think|think about it|let me think|reasoning - Generate think-aloud reasoning process' is tautological - it essentially restates the tool name 'think_aloud_process' with synonyms and examples. While it indicates this generates a thinking process, it doesn't specify what kind of output or format this produces, nor does it distinguish this from sibling tools like 'step_by_step_analysis' or 'create_thinking_chain'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does 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 sibling analysis and reasoning tools (analyze_problem, step_by_step_analysis, create_thinking_chain, etc.), there's no indication of what makes this 'think-aloud' approach distinct or when it's preferable to other reasoning methods.
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 only provide a title ('Validate Code Quality'), which doesn't add behavioral information. The description doesn't disclose any behavioral traits beyond the vague action of validation. It doesn't mention what the tool actually does (e.g., returns a score, generates a report, flags issues), whether it's read-only or has side effects, performance characteristics, or error handling. For a tool with no informative annotations, this leaves the agent with minimal operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single run-on string of synonyms ('quality|review|check|quality|review code|check quality|validate|code review - Validate code quality') that is repetitive and poorly structured. It's not front-loaded with clear information; instead, it wastes space on redundant terms. While brief, this isn't effective conciseness—it's under-specification masked as brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of code quality validation (which could involve various analyses and outputs), the description is inadequate. There's no output schema, and the description doesn't explain what the tool returns (e.g., a report, scores, recommendations). With annotations providing only a title and no behavioral details, the description fails to compensate, leaving significant gaps in understanding how to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all parameters (code, type, strict, metrics) with descriptions and enums. The description adds no additional meaning about parameters beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline score is 3 even with no param info in the description, which applies here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description is a tautology that essentially restates the tool name 'validate_code_quality' with synonyms like 'review', 'check', and 'validate'. It doesn't specify what validation actually entails (e.g., static analysis, linting, metrics calculation) or what constitutes 'quality'. While it mentions 'code review', this is vague and doesn't clearly differentiate from sibling tools like 'suggest_improvements' or 'apply_quality_rules'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does 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 doesn't mention any context, prerequisites, or exclusions. With many sibling tools related to code analysis (e.g., 'analyze_complexity', 'check_coupling_cohesion', 'suggest_improvements'), the lack of differentiation makes it unclear when this specific validation tool is 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?
Annotations only provide a title ('Generate PRD'), which adds no behavioral information beyond the description. The description itself doesn't disclose any behavioral traits: it doesn't indicate whether this is a read-only operation, what permissions might be needed, whether it modifies existing data, rate limits, or what the output format might be. For a tool with minimal annotations, the description carries the full burden and 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.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief but inefficiently structured. It front-loads with redundant synonyms ('PRD|product requirements document|product requirements|requirements document|spec document') that don't add value, followed by the core function. While concise in length, the repetition wastes space that could be used for more helpful information. It's not appropriately sized for a tool with 6 parameters and no output schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, no output schema) and minimal annotations, the description is incomplete. It doesn't explain what the tool actually does with the inputs (e.g., generates a structured document, fills a template, uses AI), what the output looks like, or how it relates to sibling tools. The description fails to compensate for the lack of output schema and behavioral annotations, leaving significant gaps in understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with each parameter clearly documented (e.g., 'productName' as 'product or feature name', 'productVision' as 'high-level vision and goals'). The description adds no parameter semantics beyond what's already in the schema. According to the scoring rules, when schema_description_coverage is high (>80%), the baseline score is 3 even with no param info in the description, which applies here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description is essentially a tautology that restates the tool name with synonyms ('PRD|product requirements document|product requirements|requirements document|spec document') followed by 'Generate Product Requirements Document'. While it clarifies that the tool generates PRDs, it doesn't specify what kind of generation this is (e.g., from structured inputs, templates, AI-powered creation) or how it differs from sibling tools like 'analyze_requirements' or 'create_user_stories'. The description lacks a specific verb+resource combination that distinguishes this tool's unique function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does 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 doesn't mention any context, prerequisites, or exclusions. Given multiple sibling tools that might overlap with requirements analysis (e.g., 'analyze_requirements', 'create_user_stories', 'feature_roadmap'), the absence of usage guidelines leaves the agent guessing about appropriate scenarios for this specific PRD generation 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 beyond a title, so the description carries the full burden of behavioral disclosure. It only states the action ('List saved memories') without detailing what a 'memory' entails, how results are returned (e.g., format, pagination), or any constraints like rate limits or authentication needs. This leaves significant gaps in understanding 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.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise but poorly structured, using a pipe-separated list of synonyms followed by a dash and the main phrase. This format is somewhat cluttered and not front-loaded with clear information, though it avoids unnecessary verbosity. It could be more straightforwardly phrased for better readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It does not explain what 'memories' are, how they are stored or retrieved, or what the return values look like. For a tool with no structured behavioral hints, this leaves too much ambiguity for effective use by an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with clear descriptions for both parameters ('category' and 'limit'). The description adds no additional meaning about parameters beyond what the schema provides, such as examples of categories or default behaviors. Since the schema does the heavy lifting, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'list|saved items|show saved|what memories - List saved memories' is tautological, essentially restating the tool name 'list_memories' with synonyms. It does not specify what a 'memory' is in this context or distinguish this tool from sibling tools like 'search_memories' or 'recall_memory', leaving the purpose vague beyond the basic action implied by 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 Guidelines1/5
Does 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 sibling tools like 'search_memories' (which might allow more flexible querying) or 'recall_memory' (which might retrieve a specific memory), nor does it specify any context, prerequisites, or exclusions 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 beyond a basic title, so the description carries the full burden of behavioral disclosure. The description mentions 'prioritize' which implies some kind of ordering or ranking operation, but doesn't explain what the tool actually does behaviorally: Does it modify existing memories? Create new prioritized views? Return sorted lists? How does it determine importance? Without annotations and with minimal description, the behavioral characteristics are largely opaque.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise ('Prioritize memories by importance'), but this brevity comes at the cost of clarity and completeness. While it's front-loaded and wastes no words, it's arguably under-specified rather than appropriately concise. The keywords at the beginning ('important|priority|prioritize|what matters') appear to be search terms rather than part of the functional description, which is unconventional.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that this is a 5-parameter tool with no output schema and no behavioral annotations, the description is insufficiently complete. It doesn't explain what the tool returns, how the prioritization works, what 'importance' means in this context, or how the parameters influence the outcome. For a tool that presumably performs some non-trivial operation on memories, more context is needed to understand its function and appropriate use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all parameters are documented in the schema itself. The description adds no information about any parameters beyond what's already in the schema descriptions. It doesn't explain how these parameters relate to the prioritization process or what the tool does with them. The baseline score of 3 reflects adequate parameter documentation coming entirely from the schema, not from the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Prioritize memories by importance' is essentially a tautology that restates the tool name 'prioritize_memory' with minimal added meaning. While it clarifies the resource ('memories') and the action ('prioritize'), it lacks specificity about what prioritization entails or how it differs from sibling tools like 'list_memories', 'recall_memory', or 'save_memory'. The description doesn't explain what 'prioritize' means in this context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does 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. There are multiple memory-related sibling tools (list_memories, recall_memory, save_memory, update_memory, delete_memory, search_memories), but the description offers no context about when prioritization is appropriate versus listing, recalling, or searching memories. No explicit when/when-not statements or alternative recommendations are present.
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 only provide a title ('Recall Memory'), which adds no behavioral hints. The description doesn't disclose any behavioral traits: it doesn't state if this is a read-only operation (implied by 'retrieve' but not explicit), what happens if the key doesn't exist (e.g., returns null or error), or any rate limits or authentication needs. For a tool with minimal annotations, the description carries full burden and fails to provide necessary context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise but poorly structured. It's a single phrase with pipe-separated synonyms, which is inefficient and lacks front-loading of key information. While it avoids verbosity, the structure doesn't effectively communicate purpose or usage, making it less helpful than a more organized sentence would be.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no output schema and minimal annotations, the description is incomplete. It doesn't explain what is returned (e.g., memory content, metadata, or error handling), nor does it cover behavioral aspects like idempotency or side effects. For a retrieval tool with siblings, more context is needed to guide the agent effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with clear descriptions for 'key' and 'category' parameters. The description adds no meaning beyond the schema—it doesn't explain what a 'memory key' represents, how categories are used, or provide examples. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, but the description doesn't compensate or enhance understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'recall|remember|what was|remind|retrieve - Retrieve from memory' is tautological, essentially restating the tool name 'recall_memory' with synonyms. It doesn't specify what resource is being retrieved (e.g., stored data, context, or specific memory entries) or distinguish it from sibling tools like 'list_memories', 'search_memories', or 'retrieve_memory' (though the last isn't listed). The pipe-separated synonyms add no clarity about the actual function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does 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 doesn't mention sibling tools like 'list_memories' (for listing all memories) or 'search_memories' (for broader searches), nor does it specify prerequisites, such as needing a saved memory first. There's no 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide only a title ('Analyze Complexity'), which does not cover behavioral traits like read-only status or side effects. The description adds minimal context by implying analysis (likely read-only) but does not disclose details such as computational cost, rate limits, or output format. With annotations offering little, the description carries more burden but remains insufficient 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.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is poorly structured and repetitive ('complexity|how complex|complexity|how complex|difficulty'), wasting space without adding value. It is not front-loaded with essential information, and the formatting with pipes and dashes reduces readability. While brief, it fails to be concise in a meaningful way due to redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (analyzing code with metrics), lack of output schema, and minimal annotations, the description is incomplete. It does not explain what the analysis returns, how results are interpreted, or any limitations. For a tool with two parameters and no output schema, more context is needed to guide effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with clear documentation for 'code' and 'metrics' (including an enum). The description does not add meaning beyond the schema, as it lacks parameter-specific details. According to the rules, with high schema coverage (>80%), the baseline score is 3, reflecting adequate but not enhanced parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'complexity|how complex|complexity|how complex|difficulty - Analyze code complexity' is tautological, restating the tool name 'analyze_complexity' with redundant phrases. It does not specify what 'analyze' entails or distinguish this tool from sibling tools like 'validate_code_quality' or 'check_coupling_cohesion', which might also assess code aspects. The purpose is vague beyond the basic concept of analyzing complexity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does 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 sibling tools like 'validate_code_quality' or 'check_coupling_cohesion', nor does it specify contexts or prerequisites for usage. Without any usage instructions, the agent lacks direction on appropriate application.
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 only provide a title ('Check Coupling & Cohesion'), which doesn't cover behavioral traits like read-only or destructive hints. The description doesn't add any behavioral context beyond the name, such as what the analysis entails, output format, or any constraints. However, it doesn't contradict annotations, so it's scored as 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.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is repetitive and poorly structured, with redundant terms like 'coupling|cohesion' repeated and a fragmented format ('dependencies check|module structure - Check coupling and cohesion'). It's not front-loaded with clear information, wasting space without adding value, making it inefficient rather than concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (analyzing code for coupling and cohesion with 3 parameters), lack of output schema, and minimal annotations, the description is incomplete. It fails to explain what the tool returns, how results are interpreted, or any usage context, leaving significant gaps for an agent to understand and use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with clear descriptions for all three parameters (code, type, checkDependencies). The description adds no additional meaning about parameters beyond what the schema provides, such as explaining how 'code' should be formatted or what 'checkDependencies' entails. Baseline score of 3 is appropriate given high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description is tautological, essentially restating the tool name 'check_coupling_cohesion' with variations like 'coupling|cohesion|coupling|cohesion|dependencies check|module structure - Check coupling and cohesion'. It doesn't specify what the tool actually does beyond checking these metrics, failing to distinguish it from sibling tools like 'analyze_complexity' or 'validate_code_quality' in a meaningful way.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does 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 provides no context, prerequisites, or exclusions, leaving the agent with no information on appropriate scenarios for invoking this tool compared to other analysis tools in the sibling 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?
Annotations provide a title ('Create Thinking Chain') but no behavioral hints (e.g., readOnlyHint, destructiveHint). The description implies a creation action ('Create sequential thinking chain'), which suggests a write operation, but does not disclose any behavioral traits such as side effects, permissions needed, or output format. It adds minimal context beyond the annotations, which are sparse, resulting in a baseline score.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise but under-specified and poorly structured. It consists of a list of synonyms followed by a vague action, which does not effectively communicate purpose. While brief, it wastes space on tautological repetition rather than providing useful information, making it inefficient and not front-loaded with key details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no output schema and annotations are minimal, the description is incomplete. It fails to explain what a 'thinking chain' is, how it is used, or what the output might look like. For a creation tool with behavioral implications, this lack of context leaves significant gaps 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.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with clear descriptions for 'topic' and 'steps'. The description does not add any meaning beyond the schema, as it mentions no parameters. With high schema coverage, the baseline score is 3, as the schema adequately documents the parameters without needing extra explanation in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description is tautological, essentially restating the tool name 'create_thinking_chain' with synonyms like 'thinking process', 'chain of thought', 'reasoning chain', 'thought flow', and 'sequential thinking'. It does not specify what the tool actually does beyond creating something related to thinking. It fails to distinguish from siblings like 'think_aloud_process' or 'step_by_step_analysis', 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 Guidelines1/5
Does 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 provides no context, prerequisites, or exclusions. Given siblings like 'think_aloud_process' and 'step_by_step_analysis', the lack of differentiation is a significant gap, leaving the agent with no basis 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?
Annotations provide a title ('Get Coding Guide') but no hints like readOnly or destructive. The description doesn't add behavioral traits beyond implying a retrieval action ('Get'), but it doesn't disclose details such as data sources, rate limits, authentication needs, or output format. Since annotations are minimal, the description carries more burden but only offers basic intent without operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is repetitive and poorly structured, with redundant synonyms ('guide|rules|convention' repeated) and lacks front-loaded clarity. It wastes space on synonyms instead of providing actionable information, making it inefficient and hard to parse quickly for an AI agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no output schema and minimal annotations, the description is incomplete. It doesn't explain what the tool returns (e.g., a text guide, a structured document, or an error message), nor does it cover behavioral aspects like error handling or dependencies. For a retrieval tool with two parameters, this leaves significant gaps in understanding how to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with clear descriptions for both parameters ('name' and 'category'). The description doesn't add any meaning beyond the schema, such as examples or constraints. With high schema coverage, the baseline is 3, as the description doesn't compensate but also doesn't detract from the well-documented parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description is a tautology that essentially restates the tool name 'get_coding_guide' with synonyms ('guide|rules|convention|standards|best practices'). It doesn't specify what action is performed (e.g., retrieve, display, or analyze) or what resource is accessed. While it mentions 'Get coding guide,' this is too vague to distinguish it from siblings like 'apply_quality_rules' or 'validate_code_quality' that might involve coding standards.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does 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. It doesn't mention any context, prerequisites, or exclusions, nor does it refer to sibling tools. For example, it doesn't clarify if this is for retrieving predefined guides versus generating new ones, leaving the agent to guess based on 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?
Annotations only provide a title ('Step-by-Step Analysis'), so the description carries the full burden of behavioral disclosure. It mentions 'detailed' and 'step-by-step' but does not explain what the tool actually does behaviorally—e.g., whether it generates a list, provides explanations, iterates through sub-tasks, or has side effects. No information on permissions, rate limits, or output format is given.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is inefficiently structured with repetitive phrases ('step by step|one at a time|gradually|step by step|one by one|gradually') that waste space without adding value. It is not front-loaded with clear purpose, and the redundancy reduces clarity rather than enhancing it.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations beyond title, no output schema, and a general-purpose tool with 3 parameters, the description is incomplete. It fails to explain what the tool outputs, how it behaves, or its role among many analysis-focused siblings. For a tool that likely produces structured analysis, more context is needed to guide effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters (task, context, detailLevel) with descriptions and enum values. The description adds no meaning beyond this, not even hinting at how parameters affect the analysis. With high schema coverage, the baseline is 3, as the description doesn't compensate but also doesn't detract.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Perform detailed step-by-step analysis' is a tautology that essentially restates the tool name 'step_by_step_analysis' with minimal elaboration. While it includes the verb 'perform' and resource 'analysis', it lacks specificity about what kind of analysis or what distinguishes it from sibling tools like 'break_down_problem' or 'think_aloud_process'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 sibling tools focused on analysis (e.g., 'analyze_complexity', 'analyze_problem', 'break_down_problem'), there is no indication of context, prerequisites, or exclusions. The repetitive phrasing 'step by step|one at a time|gradually' hints at a methodical approach but fails to specify 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?
Annotations only provide a title ('Suggest Improvements'), which doesn't cover behavioral traits like read-only vs. destructive operations, authentication needs, or rate limits. The description adds minimal context by implying the tool analyzes code for improvements, but it doesn't disclose specific behaviors such as whether it modifies code, requires specific permissions, or has limitations. Since annotations are sparse, the description carries more burden but still falls short of rich behavioral disclosure, earning a baseline score.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is poorly structured and repetitive, with phrases like 'improve|make better' duplicated and a disorganized list ('refactoring|improve|make better|refactor|optimize|enhance code - Suggest improvements'). It lacks front-loading of key information and includes redundant terms, making it inefficient and hard to parse. While brief, the repetition undermines conciseness, resulting in wasted space.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 parameters, no output schema, sparse annotations), the description is incomplete. It doesn't explain what the tool returns, how improvements are suggested, or any constraints (e.g., code language support, analysis depth). With no output schema and minimal annotations, the description should provide more context about the tool's operation and results, but it fails to do so, leaving significant gaps for agent understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with clear documentation for 'code', 'focus' (with enum values), and 'priority' (with enum values). The description doesn't add any meaningful semantics beyond the schema—it doesn't explain parameter interactions, default behaviors, or usage examples. Given the high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'improve|make better|refactoring|improve|make better|refactor|optimize|enhance code - Suggest improvements' is tautological, essentially restating the tool name 'suggest_improvements' with synonyms. It doesn't specify what kind of improvements (e.g., code quality, performance) beyond the generic 'improve code', nor does it clearly distinguish from siblings like 'validate_code_quality' or 'apply_quality_rules'. The repetition of phrases ('improve|make better' appears twice) adds noise without clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does 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 doesn't mention any context, prerequisites, or exclusions, and fails to differentiate from sibling tools such as 'validate_code_quality' or 'apply_quality_rules', which might overlap in purpose. Without explicit or implied usage instructions, the agent lacks direction for tool 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?
The description provides minimal behavioral information beyond what the annotations suggest. The annotations only provide a title ('Analyze Problem'), so the description carries the full burden of behavioral disclosure. While it mentions the tool breaks down problems into structured steps, it doesn't describe what those steps look like, whether this is a read-only analysis or if it modifies data, what the output format might be, or any limitations of the analysis. For a tool with no meaningful annotations, this is inadequate 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.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is poorly structured with multiple verbs separated by pipes ('analyze this|how to approach|break this down|problem analysis|examine|investigate') followed by a dash and the core description. This format is confusing and not front-loaded with the most important information. While brief, the pipe-separated list adds noise without clarity, making it less effective than a single clear sentence would be.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's apparent complexity (problem analysis with structured steps), the lack of annotations, and no output schema, the description is insufficiently complete. It doesn't explain what 'structured steps' means, what format the analysis takes, whether there are limitations on problem types or domains, or how this differs from similar sibling tools. For an analysis tool in a crowded namespace with no structured output documentation, this description leaves too many questions unanswered.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no specific information about parameters beyond what the schema already provides. With 100% schema description coverage (both parameters have descriptions in the schema), the baseline is 3. The description doesn't explain how the 'problem' and 'domain' parameters interact, provide examples of valid inputs, or clarify edge cases. It simply repeats the tool's function without enhancing parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool's purpose as 'Break down complex problem into structured steps', which is clear but somewhat vague. It doesn't specifically distinguish this tool from sibling tools like 'break_down_problem' or 'step_by_step_analysis', which appear to have similar functions. The description includes multiple verbs ('analyze', 'approach', 'break down', 'examine', 'investigate') but lacks specificity about what makes this tool unique.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 multiple sibling tools that seem related (analyze_complexity, analyze_prompt, break_down_problem, step_by_step_analysis), there's no indication of when this specific 'analyze_problem' tool is appropriate versus those other analysis tools. The description doesn't mention any prerequisites, constraints, or typical 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?
Annotations only provide a title ('Find References'), so the description carries the burden of behavioral disclosure. It implies a read-only search operation ('find'), which aligns with no destructive hints, but doesn't add context like rate limits, authentication needs, or what 'references' entails (e.g., exact matches, partial matches, scope). It's minimal but not contradictory.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is poorly structured and repetitive, with redundant synonyms ('where used|references|usages|find usage|references|where used') and a final phrase that restates the idea. It's not front-loaded with clear information, and the repetition adds no value, making it inefficient rather than concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations beyond title, no output schema, and a 4-parameter tool, the description is incomplete. It doesn't explain what 'references' means in output, how results are returned, or any behavioral nuances. For a tool that likely returns complex data (references in a codebase), this leaves significant gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all four parameters (symbolName, filePath, line, projectPath) with clear descriptions. The description adds no meaning beyond this, such as explaining how parameters interact or providing examples. Baseline 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description is a tautology that restates the tool name with synonyms ('where used|references|usages|find usage|references|where used'), then repeats 'Find symbol references' which is essentially the tool name. It doesn't specify what type of symbol (code symbol, data symbol, etc.) or what context (codebase, documentation, etc.), making it vague rather than specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 include 'find_symbol', which might be related for locating definitions, but the description doesn't mention this or any other context for usage. It lacks explicit when/when-not statements or named alternatives.
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 beyond a title, so the description carries full burden. It mentions 'preview' which implies read-only/non-destructive behavior, but doesn't explicitly state this. No information about permissions, rate limits, output format, or what 'preview' actually generates (ASCII representation as hinted in title). The 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.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is poorly structured with a confusing pipe-separated list of verbs followed by the actual purpose. The front-loaded content ('create page|build UI|design component|make page|develop page') is misleading and doesn't earn its place. Only the last part 'Preview UI before coding' is useful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 5 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what the preview output looks like (ASCII representation), how it's displayed, or what value it provides. The title hints at 'ASCII' but the description doesn't mention this crucial aspect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all 5 parameters. The description adds no parameter-specific information beyond what's in the schema. Baseline score of 3 is appropriate since the schema does all the parameter documentation work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool's purpose as 'Preview UI before coding' which is clear but vague. It lists alternative verbs like 'create page|build UI|design component|make page|develop page' which adds confusion rather than clarity. The purpose is understandable but not specific about what 'preview' entails or how it differs from actual creation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 mentions 'before coding' which implies a pre-implementation context, but there's no comparison with sibling tools (none of which appear to be UI-related). 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description states 'Update existing memory', which implies a mutation operation, consistent with the tool name. No annotations are provided to contradict this (only a title annotation exists), so there's no contradiction. However, the description lacks behavioral details beyond the basic action—it doesn't specify permissions needed, whether updates are idempotent, error conditions (e.g., if the key doesn't exist), or side effects. With no annotations to rely on, this leaves gaps in understanding 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.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise but poorly structured and redundant. 'update|modify|change|edit memory' lists synonyms without adding value, and '- Update existing memory' repeats the same idea. This wastes space without improving clarity. A single, clear phrase would be more effective, making this under-specified rather than efficiently concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a mutation operation with 3 parameters, no output schema, and no annotations beyond title), the description is incomplete. It doesn't address key contextual aspects like what 'memory' refers to in this system, expected outcomes, error handling, or how it differs from sibling tools. For a tool that modifies data, more guidance is needed to ensure correct usage by an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with clear descriptions for 'key', 'value', and 'append' parameters in the input schema. The description adds no additional semantic context about parameters beyond what's already documented in the schema (e.g., it doesn't explain format of 'key' or how 'append' interacts with 'value'). Given the high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract from the schema's documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'update|modify|change|edit memory - Update existing memory' is tautological, essentially restating the tool name 'update_memory' with synonyms. It doesn't specify what type of memory is being updated (e.g., key-value storage, session memory) or what resource is affected, beyond the generic term 'memory'. This provides minimal clarification beyond the name itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 sibling tools like 'save_memory', 'delete_memory', 'list_memories', 'recall_memory', 'prioritize_memory', and 'search_memories', the description fails to differentiate this update operation from creation, deletion, retrieval, or other memory manipulations. There's no mention of prerequisites, such as requiring an existing memory key.
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 beyond a title, so the description carries the full burden. It states the tool analyzes prompt quality and provides improvement suggestions, which implies a read-only analysis with constructive feedback. However, it lacks details on behavioral traits like rate limits, authentication needs, or what specific aspects of 'quality' are evaluated, leaving 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.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single run-on string with synonyms separated by pipes, making it poorly structured and hard to parse. It includes redundant terms ('analyze prompt' and 'evaluate prompt') without clear organization, reducing readability and efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete. It vaguely states the purpose but lacks details on what the analysis entails, how results are returned, or behavioral context, making it insufficient for an agent to fully understand the tool's operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents the 'prompt' and 'criteria' parameters adequately. The description does not add any meaning beyond what the schema provides, such as examples of criteria or how analysis is performed, resulting in a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description lists synonyms ('analyze prompt|rate this|score|how good|prompt quality|evaluate prompt|assess') which vaguely indicate the tool's purpose but lack specificity about what 'analyze' entails. It mentions 'provide improvement suggestions' which adds some clarity, but doesn't distinguish it from sibling tools like 'enhance_prompt' or 'suggest_improvements' that might 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 Guidelines2/5
Does 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 is provided. The description does not mention when-not scenarios or compare to siblings such as 'enhance_prompt' or 'suggest_improvements', leaving the agent to infer usage based on tool names 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?
Annotations only provide a title, so the description carries the burden of behavioral disclosure. It mentions 'Gemini API prompting strategies' and lists specific techniques (Few-Shot, Output Format, etc.), which adds some context about the enhancement approach. However, it doesn't describe the output format, potential side effects, or how the enhancement is applied (e.g., returns a modified prompt vs. suggestions). With no annotations to rely on, this is a minimal but not comprehensive disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is poorly structured and repetitive, with 'gemini strategies|quality improvement' listed twice, reducing clarity. It's front-loaded with keywords but lacks coherent sentences. While brief, the repetition and lack of flow make it inefficient, as it doesn't earn its place with useful information beyond the initial intent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and minimal annotations, the description is incomplete. It doesn't explain what the enhanced prompt looks like, how quality is measured, or any limitations (e.g., token limits, strategy interactions). For a tool with 3 parameters and no structured output info, more context is needed to guide effective use, making this inadequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents parameters like 'prompt', 'agent_role', and 'strategies'. The description doesn't add any meaning beyond this—it doesn't explain how 'agent_role' influences enhancement or what the strategies entail in practice. With high schema coverage, the baseline is 3, as the description doesn't compensate with extra insights.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool enhances prompts using Gemini API strategies, which provides a general purpose. However, it's vague about what 'enhance' specifically means (e.g., rewriting, adding structure, optimizing) and doesn't clearly distinguish from sibling tools like 'enhance_prompt' (without Gemini) or 'suggest_improvements'. The repetition of 'quality improvement' adds noise but doesn't clarify the unique value.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 doesn't mention when to choose it over 'enhance_prompt' (the sibling tool) or other prompt-related tools like 'analyze_prompt' or 'suggest_improvements'. The description lists strategies but doesn't explain scenarios where this tool is appropriate, leaving usage unclear.
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 only provide a title ('Feature Roadmap'), so the description carries the full burden of behavioral disclosure. It states the tool 'Generate[s] development roadmap', implying a creation or output action, but doesn't specify what the output entails (e.g., text, timeline, visual), whether it's read-only or modifies data, or any constraints like rate limits. This leaves behavioral traits largely undefined, though it doesn't contradict the minimal annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise but poorly structured and repetitive, with redundant keywords ('roadmap|schedule|timeline|roadmap|timeline|project plan|development schedule') that don't add value. It's front-loaded with noise before the core purpose ('Generate development roadmap'), wasting space without improving clarity. A more effective structure would state the purpose directly without the keyword clutter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 parameters, no output schema, and minimal annotations), the description is incomplete. It doesn't explain what the generated roadmap includes, its format, or how to interpret results, leaving gaps for a tool that likely produces structured planning output. With no output schema and sparse annotations, the description should provide more context about the tool's behavior and output to be fully helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with all parameters well-documented in the input schema (e.g., 'projectName' as 'Name of the project', 'timeframe' with enum values). The description adds no additional meaning beyond the schema, such as explaining how parameters interact (e.g., how 'teamSize' affects the roadmap) or providing examples. With high schema coverage, a baseline score of 3 is appropriate as the schema handles most of the parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate development roadmap' states the tool's purpose with a clear verb ('Generate') and resource ('development roadmap'), but it's vague about what exactly is generated and repeats keywords ('roadmap', 'timeline') without adding specificity. It doesn't distinguish this tool from potential siblings like 'format_as_plan' or 'generate_prd', which might serve similar planning functions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 doesn't mention any context, prerequisites, or exclusions, such as when to choose this over 'generate_prd' for product requirements or 'format_as_plan' for general planning. Without such guidance, the agent must infer usage from the tool name and parameters 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?
Annotations only provide a title, so the description carries the burden of behavioral disclosure. It mentions 'monitor' and 'debug output', implying real-time or duration-based logging capture, but doesn't specify if it's passive observation, requires browser automation, or has side effects like network requests. No rate limits, authentication needs, or output format details are included, leaving gaps in behavioral understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a keyword list ('console log|check errors|show logs|console|check logs|debug output|console errors - Monitor browser console'), which is inefficient and lacks structure. It's front-loaded with synonyms but doesn't form a coherent sentence, wasting space on repetition (e.g., 'console' appears multiple times) rather than providing clear, actionable information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and minimal annotations, the description is incomplete. It doesn't explain what the tool returns (e.g., log entries, error counts) or behavioral aspects like how monitoring works (e.g., via browser automation, API calls). For a tool with 3 parameters and debugging complexity, more context on operation and results is needed to be fully helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents parameters (url, logLevel, duration). The description adds no additional meaning beyond the schema, such as examples or constraints (e.g., URL must be accessible, duration limits). With high schema coverage, the baseline is 3, as the description doesn't compensate but doesn't detract either.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool monitors browser console logs, which is a clear purpose, but it's phrased as a keyword list rather than a coherent sentence. It doesn't distinguish from sibling tools like 'inspect_network_requests' or 'validate_code_quality', which are also debugging-related tools. The description lacks specificity about what 'monitor' entails operationally.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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. Sibling tools include 'inspect_network_requests' for network debugging and 'validate_code_quality' for code analysis, but the description doesn't mention these or specify contexts like debugging web applications versus other scenarios. Usage is implied only through the keyword 'debug output'.
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 only provide a title ('Start Session'), so the description carries the full burden of behavioral disclosure. It mentions 'Start session with context', implying initialization and context loading, but doesn't detail what 'context' includes, whether this is a read or write operation, or any side effects like authentication needs or rate limits. It adds minimal value beyond the title, but doesn't contradict annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is poorly structured and not front-loaded. It starts with confusing pipe-separated terms ('hi-ai|hello|start|begin session') before stating the purpose, which wastes space and could mislead. While brief, this inefficiency reduces clarity, making it less helpful for an agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and minimal annotations, the description is incomplete. It doesn't explain what the tool returns, how 'context' is defined, or the implications of starting a session (e.g., session ID, duration, or interaction with other tools). For a tool with 4 parameters and no structured output info, this leaves significant gaps in understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all four parameters (greeting, loadMemory, loadGuides, restoreContext) with clear descriptions. The description adds no additional meaning about parameters beyond implying 'greeting' through 'hi-ai|hello|start|begin session', which is redundant. Baseline 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool's purpose with 'Start session with context', which is a clear verb+resource combination. However, it begins with ambiguous terms like 'hi-ai|hello|start|begin session' that could confuse the agent about whether these are synonyms or parameters, and it doesn't differentiate from sibling tools like 'restore_session_context' or 'auto_save_context', leaving the scope vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 doesn't mention prerequisites, timing, or comparisons to siblings such as 'restore_session_context' or 'auto_save_context', which might handle similar session-related tasks. This lack of context makes it hard for an agent to decide when 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.
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 mentions 'systematic analysis' and 'methodical approach' but doesn't disclose behavioral traits like what the 9 steps actually are, whether this is a read-only analysis tool, what kind of output to expect, or any limitations. The description is too vague about the tool's actual behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise but poorly structured. It starts with a keyword list ('reasoning framework|systematic analysis|...') that doesn't form a coherent sentence, then follows with the actual description. While brief, the keyword preamble adds noise without clear value, and the description could be more front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 3 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what the 9-step framework entails, what kind of analysis results to expect, or how this differs from other analysis tools. The lack of behavioral transparency and output information leaves significant gaps for an agent trying to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the baseline is 3. The description doesn't add meaningful parameter semantics beyond what's already in the schema - it mentions 'analyze complex problems' which aligns with the 'problem' parameter, but provides no additional context about parameter usage, constraints, or relationships.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool applies a 9-step reasoning framework to analyze complex problems systematically. It specifies the verb ('apply') and resource ('9-step reasoning framework'), but doesn't explicitly differentiate from sibling tools like 'step_by_step_analysis' or 'think_aloud_process' that might offer similar analytical approaches.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 multiple sibling tools for analysis (analyze_complexity, analyze_problem, step_by_step_analysis, etc.), there's no indication of what makes this reasoning framework approach distinct or when it's most 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?
Annotations only provide a title ('Format as Plan'), so the description carries the full burden of behavioral disclosure. It mentions formatting into 'clear plans' but doesn't specify output format (e.g., markdown, plain text), whether it's read-only or mutates data, or any constraints like rate limits. The description adds minimal context beyond the title, leaving gaps in behavioral understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with the core purpose, but the list of synonyms ('as a plan|organize|checklist...') is somewhat redundant and could be more structured. It's efficient overall, with no wasted sentences, though it could be slightly more polished.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and minimal annotations, the description is incomplete. It doesn't explain what the tool returns (e.g., formatted text, structured data), and with 4 parameters and sibling tools that might overlap, more context is needed for the agent to use it effectively. The description fails to compensate for the lack of structured output information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description doesn't add any meaning beyond what's in the schema—it doesn't explain how parameters interact (e.g., how 'priority' affects the plan) or provide usage examples. Baseline 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool 'Format content into clear plans' which indicates its purpose, but it's vague about what constitutes a 'plan' and doesn't distinguish from sibling tools like 'break_down_problem', 'create_thinking_chain', or 'step_by_step_analysis' that might have overlapping functionality. The list of synonyms ('as a plan|organize|checklist|format as plan|make a plan|organize this|checklist') adds some context but doesn't clarify the specific verb+resource combination.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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. It doesn't mention any context, prerequisites, or exclusions, and with many sibling tools that might handle similar tasks (e.g., 'break_down_problem', 'create_thinking_chain'), the agent is left without clear direction on tool 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?
Annotations only provide a title ('Auto-Save Context'), so the description carries the burden of behavioral disclosure. It mentions 'auto-save and compress', hinting at automation and data reduction, but lacks details on how compression works, what gets saved (e.g., overwrites, appends), authentication needs, rate limits, or side effects. No contradiction with annotations exists, but it adds minimal 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise with a single phrase listing synonyms and the core action. It's front-loaded with key terms, but the synonym list ('commit|checkpoint|backup|compress|auto-save') is somewhat redundant and could be streamlined. Overall, it's efficient with minimal waste, though slightly cluttered.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, no output schema, minimal annotations), the description is incomplete. It covers the basic purpose but lacks details on behavior, output format, or integration with sibling tools. Without an output schema, the description should ideally hint at return values, but it doesn't. It's minimally adequate but leaves significant gaps for an agent to understand full usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with all parameters well-documented in the schema (e.g., urgency levels, context types). The description doesn't add any meaning beyond the schema, such as explaining parameter interactions or use cases. With high schema coverage, the baseline score is 3, as the description doesn't compensate but also doesn't detract.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description lists synonyms (commit, checkpoint, backup, compress, auto-save) and states 'Auto-save and compress context', which gives a vague purpose of saving and compressing context. However, it doesn't specify what 'context' refers to (e.g., conversation state, memory, session data) or distinguish it from sibling tools like 'save_memory' or 'restore_session_context', leaving ambiguity about the exact resource and operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 is provided. The description doesn't mention when it's appropriate (e.g., during long conversations, before breaks) or when not to use it, nor does it reference sibling tools like 'save_memory' or 'restore_session_context' for comparison. Usage is implied by the name and description but not clearly defined.
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 behavioral disclosure. It states the action is deletion, implying a destructive mutation, but doesn't specify whether this is permanent, reversible, requires specific permissions, or has side effects (e.g., affecting related memories). For a destructive tool with zero annotation coverage, this is a significant gap 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded, using a single phrase with synonymous verbs for clarity. Every word earns its place by emphasizing the deletion action and target resource without redundancy or unnecessary elaboration. It efficiently communicates the core purpose in minimal text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity as a destructive operation with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., permanence, error handling), usage context relative to siblings, and expected outcomes. For a mutation tool in a memory management system, this leaves critical gaps for an agent to operate safely and effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the single parameter 'key' documented as 'Memory key to delete'. The description adds no additional meaning beyond this, such as explaining what constitutes a valid key format or where to obtain it. With high schema coverage, the baseline score of 3 is appropriate, as the schema adequately defines the parameter without extra description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('delete') and resource ('specific memory') with multiple synonymous verbs for emphasis. It distinguishes from sibling tools like 'list_memories', 'recall_memory', 'save_memory', and 'update_memory' by specifying deletion rather than listing, retrieving, creating, or modifying. However, it doesn't explicitly differentiate from 'prioritize_memory' or 'search_memories' in terms of when deletion is appropriate versus those operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 doesn't mention prerequisites (e.g., needing to know the memory key from 'list_memories' or 'recall_memory'), exclusions (e.g., not for bulk deletion), or comparisons to siblings like 'update_memory' for modification instead of deletion. The agent must infer usage from the tool name and context 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?
Annotations only provide a title ('Restore Session'), with no hints on read-only or destructive behavior. The description adds minimal behavioral context by implying a restoration action, but it doesn't disclose details like whether this overwrites current context, requires specific permissions, or has side effects. With no annotations to rely on, the description carries the burden but offers limited transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with key verbs, using minimal words to convey the core action. However, it could be more structured by clarifying the tool's scope or differentiating it from siblings, but it avoids redundancy and is efficiently phrased.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations beyond a title, the description is incomplete for a tool with 3 parameters and behavioral implications. It covers the basic purpose but lacks details on return values, error conditions, or integration with sibling tools, making it minimally viable but with clear gaps in context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with clear descriptions and enums for parameters. The description adds no additional meaning beyond the schema, such as explaining the impact of 'restoreLevel' or 'filterType' choices. Baseline score of 3 is appropriate as the schema adequately documents parameters without description enhancement.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the action ('restore|revert|go back|recover') and resource ('session context'), making the purpose clear. However, it does not differentiate from sibling tools like 'recall_memory' or 'list_memories' that also deal with session or memory retrieval, leaving ambiguity about when to choose this tool over others.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is provided on when to use this tool versus alternatives. The description implies it's for restoring session context, but it doesn't specify scenarios, prerequisites, or exclusions, such as whether it requires a previously saved session or how it differs from tools like 'recall_memory'.
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 provide only a title, so the description carries the full burden. It indicates this is a write operation ('save'), but doesn't disclose behavioral traits like persistence guarantees, overwrite behavior, or access controls. The description adds minimal context 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single phrase using synonyms, making it front-loaded and efficient. However, the pipe-separated synonyms ('remember|save|store|memorize|keep') feel slightly redundant rather than additive, slightly reducing clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a write operation with no annotations and no output schema, the description is insufficient. It lacks crucial context about what 'saving to long-term memory' entails operationally—such as success indicators, error conditions, or how this differs from sibling tools like 'update_memory'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are well-documented in the schema. The description adds no additional meaning about parameters like key/value semantics or category usage. Baseline score of 3 is appropriate since the schema handles parameter documentation adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with multiple synonyms for 'save' and specifies the target as 'long-term memory', making it evident this is a storage operation. However, it doesn't differentiate from sibling tools like 'update_memory' or 'prioritize_memory', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 'update_memory' or 'prioritize_memory'. The description merely restates the action without context about appropriate scenarios or exclusions, 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds minimal behavioral context beyond what annotations provide. Annotations only include a title ('Create User Stories'), so the description carries most of the burden. It indicates this is a generation/creation tool, but doesn't disclose important behavioral traits like whether this creates persistent artifacts, typical output format, limitations on input complexity, or how it handles different requirement types. The description is functional but lacks operational transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at just 8 words, with no wasted language. It's front-loaded with the core purpose ('Generate user stories from requirements') and includes relevant synonyms upfront. However, the repetition of 'user story' three times in the synonym list feels redundant rather than helpful, slightly detracting from optimal efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and minimal annotations, the description provides basic completeness for a generation tool but leaves significant gaps. It states what the tool does but doesn't describe output format, quality characteristics, limitations, or integration context. For a tool that transforms requirements into structured user stories, more context about the transformation process and results would be helpful, though the concise nature keeps it at minimum viable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the input schema already documents all 4 parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema - it doesn't explain relationships between parameters, provide examples of valid 'features' or 'userTypes' inputs, or clarify how parameters interact. The baseline score of 3 reflects adequate but minimal value addition given comprehensive schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate user stories from requirements' which is a specific verb+resource combination. It distinguishes itself from sibling tools like 'analyze_requirements' or 'generate_prd' by focusing specifically on user story creation rather than analysis or broader documentation. However, it doesn't explicitly contrast with these alternatives in the description text itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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. While sibling tools like 'analyze_requirements' and 'generate_prd' exist for related tasks, the description doesn't mention them or provide context about when user story generation is appropriate versus other requirement documentation approaches. There's no mention of prerequisites, typical workflows, 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?
Annotations provide a title but no behavioral hints (e.g., readOnlyHint, destructiveHint). The description adds minimal behavioral context beyond the basic action—it mentions searching 'by content' but doesn't disclose details like search scope (e.g., full-text vs. keywords), result format, pagination, or error handling. With no annotations to rely on, the description carries the burden but offers only basic transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the core action ('search memories by content'), using minimal words. However, the pipe-separated verb list ('find|search|look for|query') is slightly redundant and could be streamlined without losing clarity, preventing a perfect score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (search function with 2 parameters), no annotations, and no output schema, the description is incomplete. It covers the basic purpose but lacks details on behavioral traits (e.g., search behavior, result structure) and output expectations, which are critical for an agent to use it effectively. The description is adequate as a minimum but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with clear descriptions for both parameters ('query' and 'category'). The description adds no additional meaning beyond what the schema provides—it doesn't explain query syntax, category options, or interaction between parameters. Given high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but doesn't detract.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('find|search|look for|query') and resource ('memories'), and specifies the search mechanism ('by content'). It distinguishes from siblings like 'list_memories' by focusing on content-based search rather than listing. However, it doesn't explicitly differentiate from 'recall_memory' or 'find_references', which slightly limits sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 'list_memories' (for browsing all memories) or 'recall_memory' (for retrieving specific memories by ID). It lacks explicit when/when-not instructions or named alternatives, offering only implied usage through the action 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?
Annotations only provide a title ('Break Down Problem'), so the description carries the burden of behavioral disclosure. It describes the tool's function (decomposition) but lacks details on behavioral traits such as output format, computational limits, or error handling. No contradiction with annotations exists, but the description is minimal 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded, using a single sentence with synonyms to reinforce the purpose. Every word earns its place, avoiding redundancy and maintaining clarity without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given 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 output schema) and minimal annotations, the description is adequate but incomplete. It covers the basic purpose but lacks context on output, error cases, or integration with sibling tools, making it minimally viable but with clear gaps for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with clear descriptions for all parameters (problem, maxDepth, approach). The description adds no additional semantic context beyond what the schema provides, such as examples or usage tips. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but doesn't detract either.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as breaking complex problems into sub-problems with specific verbs like 'break down,' 'divide,' and 'decompose.' It distinguishes from some siblings like 'analyze_complexity' or 'step_by_step_analysis' by focusing on decomposition rather than analysis or execution. However, it could be more specific about the resource or domain (e.g., 'problem-solving tasks') to fully differentiate from all siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 'analyze_problem' or 'step_by_step_analysis.' It lacks context about prerequisites, exclusions, or comparisons with sibling tools, leaving the agent to infer usage based on the name and description 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?
Annotations only provide a title ('Get Current Time'), with no hints on read-only or destructive behavior. The description adds minimal behavioral context by implying it retrieves real-time data, but doesn't disclose rate limits, authentication needs, or output format. With low annotation coverage, the description carries more burden but offers only basic operational insight.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded, using a single phrase with synonyms to convey the core function without unnecessary details. Every word earns its place, making it efficient and easy to parse, though this conciseness comes at the cost of depth in other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (simple time retrieval), no output schema, and rich schema coverage, the description is minimally adequate. It covers the basic purpose but lacks details on return values, error handling, or integration context. With annotations sparse, it should do more to compensate, but the simplicity of the tool keeps it from being severely incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, documenting both parameters (format with enum, timezone). The description adds no parameter-specific information beyond what the schema provides, such as default behaviors or examples. Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't compensate with additional semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('get current time') and synonyms ('what time', 'time now'), making it unambiguous. However, it doesn't differentiate from siblings since there are no other time-related tools in the sibling list, so it doesn't need to distinguish from alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 lists synonyms but doesn't mention context, prerequisites, or exclusions. Given the sibling tools are unrelated (e.g., analyze_complexity, save_memory), there's no explicit comparison, leaving usage unclear beyond the basic purpose.
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 beyond the title, so the description carries the full burden. It describes the tool's behavior as transforming prompts, which is clear, but lacks details on output format, potential side effects, or limitations. This is adequate given the absence of annotations but misses opportunities to add richer context like response structure or constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise and front-loaded, using a single sentence with no wasted words. It efficiently communicates the core purpose and key enhancement types, making it easy to scan and understand quickly. Every element earns its place without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given 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 output schema, no annotations beyond title), the description is complete enough for basic use but lacks depth. It covers the purpose and enhancement types, but without output schema or rich annotations, it should ideally explain more about the transformation process or result format to fully compensate for missing structured data.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters (prompt, context, enhancement_type) with descriptions and enums. The description adds minimal value beyond this by mentioning enhancement types in a list, but does not explain parameter interactions or provide additional semantics. Baseline 3 is appropriate as the schema handles most of the documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('Transform vague requests into clear, actionable prompts') and distinguishes it from siblings like 'analyze_prompt' or 'enhance_prompt_gemini' by focusing on transformation rather than analysis or alternative enhancement methods. The title annotation 'Enhance Prompt' reinforces this, but the description adds valuable specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through phrases like 'Transform vague requests' and lists enhancement types (clarity, specificity, context, all), providing clear guidance on when to use it for prompt improvement. However, it does not explicitly state when not to use it or name alternatives like 'enhance_prompt_gemini', which slightly limits differentiation from siblings.
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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