Agent.ai MCP Server

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation3/5
Many tools are well-differentiated within their domains, but the presence of parallel v2 and v3 versions (e.g., meeting_prep vs. meeting_prep_v3) and overlapping contact/outreach research tools create ambiguity. Agents may struggle to choose between similar tools.
Naming Consistency4/5
Most tools follow a consistent domain_subdomain_action pattern with underscores. However, a few tools lack domain prefixes (e.g., `process_video`, `search`) and hubspot tools use dots, causing minor inconsistency.
Tool Count2/5
177 tools is excessive for any server, even one covering multiple domains. The count is inflated by parallel v2/v3 variants and many render functions that could be consolidated. It would be overwhelming for an agent to navigate.
Completeness4/5
Within each subdomain (file conversion, social media, meeting prep, outreach, etc.), the tool surface is thorough, covering creation, analysis, rendering, and pipeline steps. Minor gaps exist (e.g., no YouTube upload), but overall coverage is strong.
Average 3.2/5 across 177 of 177 tools scored. Lowest: 1.3/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
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This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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{
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}
```
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description should disclose behavioral traits, but it does not mention any side effects, required permissions, or consequences of creation. The agent has no insight into what happens during engagement creation.
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 extremely short but lacks necessary detail, making it an under-specification rather than effective conciseness. It does not front-load critical information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (9 parameters, 3 required, no output schema) and the absence of annotations, the description is severely incomplete. It fails to explain return values, effects on HubSpot, or any constraints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no meaning beyond the input schema, which already provides descriptions for 67% of parameters. The tool description does not clarify any parameter relationships, constraints, or usage patterns.
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 'Create HubSpot Engagement' essentially restates the tool name without specifying the types of engagements (e.g., note, call, email) or how it differs from sibling tools like hubspot.v2.create_object. It provides minimal differentiation.
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 is given on when to use this tool versus alternatives such as hubspot.v2.create_object or other engagement-related tools. The description lacks any context about prerequisites or use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only says 'Update HubSpot Object' without any details on mutation effects, required permissions, idempotency, error handling, or rate limits. This is a total failure to inform the agent of consequences.
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 sentence, but it is underspecified rather than concise. It adds no value beyond the name, failing to earn its place. A good concise description is informative in few words; this is merely short.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
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, 5 required, multiple object types and identification methods, no output schema), the description is completely inadequate. It does not explain how to use object_type, identification_method, properties, associations, or expected response format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 6 parameters but only 33% have descriptions (identifier_value and output_variable_name). The description adds no parameter information whatsoever. With low schema coverage, the description should compensate but does not.
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 HubSpot Object' is essentially a restatement of the tool name 'hubspot.v2.update_object'. It does not specify which object types are supported or differentiate from sibling tools like 'hubspot.v2.create_object' or 'hubspot.v2.lookup_object'. This tautology provides minimal 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?
No guidance is given on when to use this tool versus alternatives. Sibling tools include create, lookup, search, and get variants, but the description offers no context or exclusions. The agent has no way to determine appropriate 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 present, so the description must carry the full burden. It only states 'Create', implying mutation, but does not disclose any behavioral traits such as required permissions, side effects, or return values.
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 very concise (4 words) but at the expense of clarity. It is under-specified rather than efficiently informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema, annotations, and detailed parameter descriptions, the description fails to provide sufficient context for an agent to use the tool correctly. It does not cover what the tool returns or how to structure inputs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With only 25% schema description coverage, the description adds no additional meaning. It does not explain what the 'properties' or 'associations' parameters should contain, leaving significant ambiguity.
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 'Create HubSpot Object' states the verb and resource but is too vague. It does not specify the types of objects available (e.g., contacts, deals) nor distinguish from sibling tools like hubspot.v2.create_engagement or hubspot.v2.update_object.
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 is provided on when to use this tool versus alternatives. There is no mention of prerequisites, context, or when to choose this over other HubSpot operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, and the description fails to disclose any behavioral traits such as idempotency, permissions, data scope, or side effects. For a data retrieval tool, this omission is critical.
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 extremely brief (5 words) but fails to convey purpose effectively. It is not structured and does not earn its place as a tool-level description.
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?
With 4 parameters, no output schema, and no explanation of behavior, the description is incomplete. It does not explain what the tool returns, how depths affect results, or relationship between parameters.
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 coverage is 100% with all parameters described, so the baseline is 3. The tool description does not add extra meaning beyond the schema, but at least the schema is complete.
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 'The variable to retrieve from the agent's database' is a noun phrase, not a clear action statement. It implies retrieval but lacks an explicit verb, making it vague. Sibling tool 'store_variable_to_database' provides context, but the description itself is insufficient.
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 is provided on when to use this tool versus alternatives like 'store_variable_to_database' or other data retrieval tools. The description does not specify prerequisites, limitations, or appropriate contexts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, and the description provides no behavioral details like pagination, rate limits, or required permissions, leaving the agent uninformed.
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?
Description is overly brief, lacking essential details; conciseness is not effective when it omits needed information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 8 parameters, no output schema, and no annotations, the description fails to provide sufficient context for correct invocation.
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 coverage is 88%, so baseline is 3; description adds no additional meaning beyond what schema already provides.
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?
Description 'Get HubSpot Timeline Events' is generic and only restates the function of the tool without distinguishing it from sibling tools like 'get_engagements' or 'get_hubspot_object'.
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 provided on when to use this tool versus alternatives, such as other HubSpot data retrieval tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as read-only nature, authentication requirements, rate limits, or side effects. For a search tool, it is likely safe but this is not stated, leaving the agent uninformed.
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 extremely brief (2 words), which is under-specified. It does not front-load important information or structure details. Conciseness is not beneficial when it sacrifices completeness; every sentence should earn its place, and this description lacks substantive content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (8 parameters, many sibling tools, no output schema), the description is completely inadequate. It does not explain return values, pagination, sorting behavior, or how it relates to other HubSpot tools. The agent is left without essential context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 8 parameters but only 25% have descriptions. The description does not add any parameter information beyond the schema. For example, the 'filters' parameter lacks explanation of its format or usage. The description fails to compensate for the low schema coverage.
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 'Search HubSpot Objects' clearly states the action (search) and resource (HubSpot objects), but it does not differentiate from sibling tools like hubspot.v2.lookup_object or the general 'search' tool. The purpose is somewhat vague as it doesn't specify what kind of search or what objects are included, though the schema enum provides some context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. There is no mention of prerequisites, context, or exclusions. The description lacks any usage direction, making it difficult for an agent to decide between this and other search-related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description fails to disclose any behavioral traits. It does not specify whether tweets are public, the definition of 'recent', pagination behavior, or API limitations. As a result, the agent has no insight into the tool's operation beyond the name.
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 a single short sentence, which is concise, but it lacks any structure (e.g., bullet points, sections). It is front-loaded with the action but has minimal content beyond stating the obvious.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema, the description should explain the return format (e.g., list of tweet objects with fields). It does not address pagination, rate limits, or error handling. Given the tool's purpose, this is severely incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds no extra meaning beyond the parameter names and types. The type of 'recent_tweets_count' is 'string' but the schema description says 'number', which is ambiguous. The description does not clarify this or provide examples.
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 ('Fetch recent tweets') and the resource ('specified Twitter handle'), making the tool's purpose immediately apparent. It is distinct from sibling tools like 'get_twitter_users', which likely retrieves user profiles rather than tweets.
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, nor does it mention prerequisites, rate limits, or authentication. The phrase 'for social media tracking' only implies a use case but offers no actionable context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It only says 'renders a report' without stating whether it is read-only, whether it modifies state, or any permissions needed. The agent cannot infer if this is a safe read operation.
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 sentence, which is initially concise, but it is too terse for the information needed. It sacrifices necessary detail for brevity, making it under-specified rather than efficiently concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, output schema, and parameter descriptions, the description fails to provide a complete picture. It does not describe the report content, format, or how it integrates into the Heygen avatar workflow, leaving critical gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has two parameters (report_data and output_variable_name) with 0% description coverage. The description does not explain what report_data should contain (e.g., the avatar creation result) or how output_variable_name is used. This omission leaves the agent without guidance on how to supply or capture data.
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 verb 'Renders' and the resource 'photo avatar creation status as an HTML report', making the purpose understandable. However, it does not differentiate from many sibling tools that also render HTML reports (e.g., competitive_brief_render_brief_html, aeo_seo_research_render_research_report).
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?
There is no guidance on when to use this tool versus alternatives, nor any mention of prerequisites or context (e.g., that it should follow a photo avatar creation action). The description provides no usage conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only says 'Get', implying read-only, but fails to disclose pagination, rate limits, or behavior with large result sets. The schema includes result_limit but the description ignores it.
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 sentence, but it is under-specified and lacks structure. It does not front-load key information or earn its place; it essentially repeats the tool name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 8 parameters, no output schema, and no annotations, the description is severely incomplete. It does not explain what engagements are, how filtering works, or what the return format is, making it inadequate for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 88%, so the schema already documents most parameters. The description adds no additional meaning beyond what is in the schema, so baseline 3 is appropriate.
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 'Get HubSpot Engagements' which is a clear verb and resource, but it does not differentiate from sibling tools like hubspot.v2.create_engagement or hubspot.v2.get_timeline_events. It is minimally adequate but lacks distinguishing details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 such as search_objects or create_engagement. The description does not mention context or prerequisites for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It mentions personalization and an audit but doesn't explain whether the tool saves data, if it's idempotent, or what the audit reveals. Lacks depth for a generative tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence is concise but overly terse given the tool's complexity. It front-loads the purpose but omits necessary details, making it adequately structured but insufficiently 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 12 parameters, 4 required, and no output schema or parameter descriptions, this single-sentence description is far from complete. It fails to explain the role of most parameters, the nature of the audit, or the output format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no parameter details. The 12 parameters including prospect_name, channel, tone, etc. are not explained. The description adds no semantic value beyond parameter names.
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 it generates personalized email and LinkedIn message variants and mentions a transparent personalization audit. It distinguishes from sibling tools by focusing on drafting variants with an audit feature, though it doesn't explicitly compare with 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?
No guidance on when to use this tool versus other outreach tools like outreach_sequence_generate_outreach_sequence or outreach_strategist_generate_outreach_strategy. No prerequisites or exclusions mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It only states the tool discovers agents without disclosing behavioral traits like data source, freshness, rate limits, or result format. The schema covers defaults and enum but not runtime behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, efficient and front-loaded with key purpose. However, it could be more precise by aligning with actual parameters and avoiding the misleading 'tags' reference.
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 a large set of sibling tools, the description lacks explanation of return format, pagination behavior (despite page/limit params), and how results differ from other search tools. Incomplete for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% coverage with parameter descriptions, but the tool description adds confusion by referencing 'tags' which is not a parameter. It does not provide meaningful additional context beyond the schema, and the misleading claim reduces clarity.
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?
Description states it searches 'agents' with specific criteria, making verb and resource clear. However, it mentions 'tags' as a criterion while the input schema has no tags parameter, causing confusion. The name 'search' is generic and does not differentiate from many sibling search tools for different resources.
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 on when to use this tool versus the numerous sibling tools that search for specific entities (e.g., LinkedIn, companies, news). Implied usage is to search agents, but no explicit when/when-not or alternative suggestions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It states the tool 'generates' content, implying it does not post or store anything, but this is implicit. It does not mention side effects, required authorizations, rate limits, or what happens with missing inputs. The description lacks explicit safety or destruction details.
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 a single sentence of 14 words, making it concise. However, for a tool with six parameters and no annotations, the brevity leads to under-specification. While front-loaded with the core function, it sacrifices necessary detail. It earns a 3 as it is minimally adequate but inefficient in conveying usage 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 the tool has six parameters (two required), no output schema, and no annotations, the description is incomplete. It does not describe the output format (e.g., what 'social_content' contains), the workflow (e.g., prioritization of inputs), or how the result is used. A tool of this complexity requires more context to ensure correct invocation, which is lacking.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 17%, meaning only one parameter (output_variable_name) has a description in the schema. The tool description does not explain any parameter's meaning, format, or usage. For example, 'topic' is required but its role as the YouTube video topic is only implied by the description phrase 'from a YouTube video topic'. Parameters like 'video_url', 'key_takeaways', and 'target_audience' are entirely unexplained, requiring the agent to infer their purpose.
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: generating repurposed social media content for 5 specific platforms from a YouTube video topic. It uses a specific verb and resource, and distinguishes from the related sibling tool 'youtube_social_content_render_social_report' by focusing on generation rather than rendering. However, it does not differentiate itself from other social content generation tools like 'social_post_creator_generate_post_action', which also generates social posts from different inputs.
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, such as social post creators or planners. It does not mention prerequisites (e.g., need for a YouTube video topic) or situations where the tool should not be used. Context signals like 'when to use' or 'when not to use' are absent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It uses marketing language ('uncover', 'discover', 'synthesized') without disclosing data sources, side effects, or limitations. Does not clarify what actions it performs (e.g., reads emails, scrapes LinkedIn).
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 a single sentence, which is concise but overly vague. It front-loads action verbs but lacks specific detail. Every word feels generic rather than earning its place.
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 (7 parameters, multiple boolean toggles, no output schema), the description is insufficient. It does not explain output format, interaction between flags, or prerequisites. The description is too incomplete for an agent to reliably 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 covers 100% of parameters with good descriptions, enums, and defaults. The tool description adds no additional meaning beyond the high-level purpose; it does not elaborate on how parameters relate or should be combined.
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 it generates synthesized intelligence for meetings/deal prep, but it is vague and does not clearly differentiate from sibling tools like 'enrich_person', 'contact_research', or 'meeting_prep_*' tools. Lacks a specific verb-resource pair.
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 on when to use this tool versus alternatives. No when-not-to-use or exclusions provided. Among many similar tools, this omission reduces clarity for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It states the tool uses Breeze Intelligence but does not specify if it's read-only, requires permissions, or has side effects. The output is not described, and there is no indication of data usage or privacy implications.
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 a single sentence, which is concise but lacks substantive detail. It front-loads the purpose but sacrifices completeness for brevity. It could be improved with more focused 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 that it is a data enrichment tool with no output schema and two parameters, the description is incomplete. It does not explain what kind of enriched data is returned, how Breeze Intelligence works, or any prerequisites. This leaves the agent without enough context to fully leverage the tool.
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 for its two parameters (email and output_variable_name). The description does not add any additional meaning beyond what the schema already provides, so it meets the baseline with no added value.
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 it gathers enriched user data using Breeze Intelligence, which provides a specific verb, resource, and source. However, it does not differentiate from sibling tools like enrich_person or contact_research that may also enrich person data, leaving ambiguity about when to use this tool.
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 offers no guidance on when to use this tool versus alternatives. It mentions 'deeper analysis' but does not explain criteria for selection, nor does it exclude other tools like enrich_person. The sibling list includes many similar tools, making this gap significant.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as side effects, required permissions, rate limits, or any consequences of creating a timeline event.
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 a single sentence, which is concise, but it is too sparse to be informative. It earns its place by stating purpose, but could be improved with more structure.
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 8 parameters, 5 required, and no output schema or annotations, the description is incomplete. It does not explain return values, prerequisites, or integration 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 coverage is high at 88%, so the schema already documents most parameters. The description adds no additional meaning or context beyond what the schema provides.
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 'Create HubSpot Timeline Event' clearly states the verb and resource, but does not differentiate from sibling create tools like create_engagement or create_object, which also create HubSpot entities.
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. There is no context about prerequisites, when not to use, or examples of typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully convey behavior. It only says 'Look up HubSpot Object', omitting details like read-only nature, authentication requirements, rate limits, or what the response contains. This is insufficient for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that is front-loaded with the core action. However, it sacrifices informativeness for brevity; a slightly longer description would be more helpful.
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 no annotations, the description fails to explain return values, how to use 'output_variable_name', or that it supports multiple object types. The context is incomplete for a tool with 4 parameters.
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 75%, and the description adds no additional meaning beyond the schema. For example, it does not clarify the 'properties' parameter format or that 'object_id' defaults to a contact_id. The description is neutral here.
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 'Look up HubSpot Object' states a verb and resource, but it is vague and does not distinguish from sibling tools like 'get_hubspot_contact_object' or 'get_hubspot_object'. It lacks specificity about which object types or scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 the specific 'get_hubspot_contact_object' or 'get_hubspot_company_object'. There are no usage contexts or exclusions mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description lacks details on side effects, authentication needs, or rate limits. The phrase 'additional videos' is vague and does not clarify whether the tool is read-only or modifies state.
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?
One sentence with no fluff. It is appropriately sized but could be more structured to improve 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?
No output schema exists, yet the description does not explain return values or provide details on how the analysis works. The tool's behavior is under-specified.
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 coverage is 100% with descriptions for all four parameters. The description does not add extra meaning beyond what the schema already provides, 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 states 'Analyzes YouTube videos' but groups multiple outputs (transcripts, analysis, additional videos) without distinguishing from siblings like 'get_youtube_transcript'. The verb 'Analyzes' is generic, and the scope is unclear.
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 on when to use this tool versus alternatives such as 'get_youtube_transcript' or 'run_youtube_search'. Missing context on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states it renders an HTML preview. It does not disclose whether it is safe or destructive, whether it modifies state, or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, but it omits critical information about parameters and usage context. It is underspecified rather than appropriately 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 two parameters and no output schema, the description fails to explain how to use report_data (likely from a previous generation step) or what output_variable_name controls. The tool's place in a workflow is unclear.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the tool description does not explain the two parameters (report_data, output_variable_name). The defaults hint at purpose but are insufficient for an agent to populate them correctly.
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 renders a LinkedIn post as an HTML preview including copy, image, and first comment. This verb+resource+output combination is specific and distinguishes it from generation 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 guidance on when to use this tool versus alternatives like other render tools or when not to use it. There is no mention of prerequisites such as having a generated post first.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description fails to disclose any behavioral traits such as side effects, required permissions, or limitations beyond the basic fact that it generates a script.
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 a single concise sentence, but it sacrifices necessary detail for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 9 parameters and no output schema or annotations, the description is severely incomplete, leaving the agent without crucial context about script format, length options, or customization.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With only 11% schema description coverage and no parameter explanations in the description, the AI agent cannot infer the meaning or format of most parameters beyond the enum defaults.
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 uses a specific verb 'generates' and clearly identifies the resource as a 'production-ready YouTube script' for a given topic, distinguishing it from sibling tools like idea generation or article creation.
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, nor any prerequisites or context for appropriate 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 exist, so the description must disclose behavioral traits. It mentions generating packaging but omits details like whether it stores data, requires authentication, or has any side effects. The phrase 'for a new or existing video' is vague and lacks clear behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that covers the core purpose. However, it could be improved by adding structure or bullet points for readability. It is not overly verbose but lacks necessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 8 parameters, no output schema, and no annotations, the description is severely incomplete. It does not explain the output, how to use the generated packaging, or what to do with the result variable. A 1 is appropriate for such lack of completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With only 13% schema coverage, the description should clarify parameter meanings. It does not explain key parameters like input_mode, topic, video_url, or thumbnail_style. The general description fails to compensate for the sparse 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 that the tool generates YouTube packaging (titles, description, tags, thumbnails) for new or existing videos. It distinguishes from siblings like youtube_thumbnail_render_packaging_report by focusing on generation rather than rendering. However, it lacks specificity about the output format or structure.
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 such as youtube_script_writer_generate_youtube_script_action or youtube_social_content_generate_social_content_action. There is no mention of prerequisites or context for using this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as whether it modifies state, requires specific input formats, or has side effects. Minimal information beyond the basic rendering action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no wasted words, but it omits crucial information, making it too brief for effective use.
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?
Without an output schema, the description should explain what the HTML gallery contains and how the output variable is used. It does not provide enough context for an agent to correctly invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no meaning to the parameters. The default value '{{headshot_result}}' suggests a template but is not explained. The required 'output_variable_name' is not described.
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?
Description clearly states the tool renders generated headshots as an HTML gallery, using a specific verb and resource. It distinguishes from the sibling 'instant_headshot_run_headshot_generation' which generates headshots.
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, prerequisites (e.g., needing to have run headshot generation first), or alternatives among the many sibling tools for rendering reports.
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 that 'No LLM required,' which is a useful behavioral trait beyond the schema. However, with no annotations provided, the description carries the full burden of disclosing side effects or safety, and it fails to state whether the operation is read-only, modifies state, or has any constraints. It partially compensates but is incomplete.
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 two sentences, very concise and front-loaded. It efficiently conveys the core purpose and a key behavioral note. However, it could include brief parameter details without losing conciseness.
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 simple render tool with no output schema and no annotations, the description lacks key details: what is the return value (HTML string?), how is output_variable_name used, and what is the expected input format for 'qualification'. The agent may be uncertain about how to invoke and use the result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not explain the two required parameters ('qualification' and 'output_variable_name') at all. Despite 0% schema description coverage, the description adds no meaning regarding parameter format (e.g., JSON string, object) or purpose (e.g., what output_variable_name does). This is a significant gap.
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 that the tool renders a qualification report as professional HTML, using a specific verb ('Renders') and resource ('qualification report'). It distinguishes itself from sibling render tools (e.g., competitive_brief_render_brief_html) by focusing on qualification reports, though it could be more explicit about the input format.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 lead_qualifier_qualify_lead or other render tools. The description does not mention prerequisites, context, or exclusions, leaving the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description is minimal. It does not disclose any behavioral traits such as output format, supported languages, or latency, which are critical for an AI agent to use the tool correctly.
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 a single concise sentence that effectively conveys the tool's purpose with no unnecessary words.
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 simplicity (one parameter, no output schema), the description is minimal. It does not explain the return value, any restrictions, or required context, leaving the agent with insufficient information for confident 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% as the single parameter 'text_to_speech' is described. The description adds no additional meaning beyond the schema, which is adequate but not improved upon.
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 'Convert text to speech using AI to create audio outputs,' which specifies the verb (convert) and resource (text to speech). However, it does not differentiate from similar generative tools like generate_image, but the purpose is still clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. The description does not mention any prerequisites, limits, or specific use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states 'pause until the user confirms.' It fails to disclose what happens on confirmation (return value), how it handles rejection/timout, or side effects. This lack of detail is a significant gap.
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?
Extremely concise (4 words), but at the expense of completeness. While brevity is good, essential behavioral information is missing, making it under-specified.
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 simplicity (1 optional parameter, no output schema), the description should be adequate, but it is not. It fails to explain what happens after confirmation or the effect of omitting the message, leaving the agent with ambiguity.
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 coverage is 100%, so baseline is 3. The description adds no extra meaning beyond the schema's parameter description. The parameter is optional and not elaborated upon, so no additional value.
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 'Pause until the user confirms' clearly states the tool's action and resource (user confirmation). It distinguishes from siblings, as none are similar interaction tools. However, it could be more specific about the confirmation mechanism, so it's not a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when or when not to use this tool compared to alternatives. The description does not provide context for appropriate usage, leaving the agent to infer.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description does not disclose behavioral traits like whether it is read-only, side effects, or dependencies. Only states it 'renders' without explaining what that entails.
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?
Single sentence of 12 words is concise but lacks substance. It covers the basic purpose but misses important details that could be added without verbosity.
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 two parameters, no output schema, and many sibling render tools, the description is insufficient. It does not specify input format, output structure, or integration context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description does not explain the purpose or expected values of the two parameters (report_data, output_variable_name). Default values provide minimal hints but no explicit semantics.
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?
Description clearly states the verb 'renders', the resource 'cross-platform social content', and the output format 'HTML report with per-platform sections'. It differentiates from sibling render tools by specifying social content scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 like social_post_creator_render_post_report or social_performance_analyzer_render_analysis_report. Missing any context on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It does not disclose behavioral traits like input format requirements, side effects, or error conditions. For example, it is unclear what happens if report_data is missing or invalid.
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 a single sentence of 14 words, which is concise and front-loaded. However, the brevity comes at the cost of missing details that could be included without being verbose.
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?
For a render tool, the description lists some contents but lacks workflow context (e.g., it should mention generating research first) and does not describe the output format beyond 'HTML report'. The absence of an output schema places more burden on the description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description adds no meaning to the parameters. It does not explain what report_data expects (e.g., a JSON string or variable reference) or the purpose of output_variable_name. The defaults are present but not clarified.
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 renders AEO/SEO research as an HTML report and lists the content (keyword opportunities, citation gaps, recommendations). However, it does not differentiate from sibling tools that also render HTML reports for other domains.
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, such as the prerequisite aeo_seo_research_generate_research_action. No when-not-to-use or alternative tool names are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description must disclose behavioral traits but only states 'add or update'. It does not explain behavior when both create_if_missing and update_existing are true, error conditions, or side effects like overwriting data.
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 a single sentence, which is concise but too brief for the complexity. It could be restructured to front-load key details, but no wasted words.
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 5 parameters and many sibling tools, the description is incomplete. It does not mention return values (no output schema) or how it integrates with company research. The description leaves significant gaps for an AI agent to infer.
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 coverage is 100%, so baseline is 3. The description adds no extra meaning beyond the parameter descriptions; it does not clarify the relationship between domain and company_id or the purpose of output_variable_name.
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 verb 'add or update' and the resource 'company in HubSpot CRM', distinguishing it from read-only HubSpot tools like get_hubspot_company_object. However, it does not specify whether it syncs research data, leaving some ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 hubspot.v2.create_object or update_object. Missing prerequisites such as HubSpot integration requirements or permission needs.
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 merely states the function without disclosing behavioral traits like pagination, sorting, or behavior when no companies are tracked.
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 single sentence is concise but omits necessary details about filtering parameters and return value. It is appropriately short but lacks completeness for effective use.
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 4 parameters, no output schema, and no annotations, the description is too brief. It fails to explain filtering options or output format, leaving agents uncertain about 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 coverage is 100% with well-described parameters. The description adds no additional meaning beyond the schema, resulting in baseline score.
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 retrieves all companies tracked by the user, distinguishing it from sibling tools like search_companies which finds new companies. However, it does not explicitly differentiate itself from similar list 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?
No guidance on when to use this tool versus alternatives like company_research_v2_search_companies or company_research_v2_track_company. The context is implied but not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description bears full burden. It mentions rendering HTML but does not disclose read/write nature, side effects, or dependencies (e.g., requires prior conversion data). Minimal behavioral insight.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, efficient sentence with no redundant information. Brief but front-loaded with key purpose. Slightly room for improvement by adding parameter context.
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, no output schema, and 0% schema coverage, the description is incomplete. It doesn't explain how parameters work or the tool's role in a conversion workflow, leaving gaps for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% with no parameter descriptions. The description adds no meaning to report_data or output_variable_name, failing to compensate for the lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Renders' and the resource 'file conversion results' with specific output 'HTML report with download links and preview'. This distinguishes it from sibling tools like file_converter_convert_action and other render report 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 guidance on when to use this tool versus alternatives. No explicit context about prerequisites (e.g., needing a prior conversion step) or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It states 'retrieve semantic search results' but does not specify that the operation is read-only, how results are scored or chunked, or any authentication/rate limit requirements. The description adds minimal behavioral context beyond the generic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 10 words, which is concise but lacks necessary detail for a tool with 5 required parameters. While front-loaded, it is underspecified and could benefit from additional sentences to cover key aspects like return value or filtering behavior.
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 5 required parameters, no output schema, no annotations, and operates on user-uploaded files, the description is incomplete. It does not explain the format of results, how files are accessed, or any constraints. The description fails to provide sufficient context for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema already documents all 5 parameters adequately. The tool description adds no additional meaning or context beyond what is in the schema, meeting the baseline for parameter 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 retrieves semantic search results from user-uploaded files, using a specific verb and resource. However, it does not differentiate from the sibling tool 'get_data_from_builder_knowledge_base', which likely performs similar retrieval from a different source.
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, such as other search or retrieval tools in the sibling list. There are no explicit exclusions, prerequisites, or usage examples beyond what is implied by the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It fails to mention any behavior such as rate limits, pagination, result format, or what 'results' entails, leaving the agent uninformed.
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 a single, short sentence without extraneous text, but it is under-informative. It sacrifices necessary details for brevity, making it only moderately 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 simplicity (1 required param, no output schema), the description should explain what 'results' are returned (e.g., video titles, IDs). It fails to provide this context, leaving the agent uncertain about expectations.
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% as the single parameter 'query' is described in the schema. The tool description adds no additional meaning beyond what the schema already provides, meeting the baseline.
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 verb 'Perform a search', the resource 'YouTube', and the outcome 'return results for specified queries'. It effectively distinguishes this tool from siblings like get_youtube_channel and get_youtube_transcript.
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, nor are there any exclusions or context about when not to use it. The description lacks usage advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It only says 'execute serverless code' but omits critical details like execution environment, timeouts, security implications, or error handling. This is a significant gap for a tool that runs arbitrary code.
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 a single, front-loaded sentence that communicates the core purpose efficiently. However, it sacrifices necessary detail for brevity, which slightly lowers the score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool that executes user-provided code, the description is severely incomplete. It omits security warnings, execution constraints, output details, and integration context. No output schema or annotations exist to compensate.
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 coverage is 100% with clear parameter descriptions for language, code, and output variable. The description adds no extra meaning beyond the schema, so baseline score of 3 is appropriate.
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 executes serverless code within workflows, but it does not differentiate from many siblings like 'rest_call' or 'invoke_agent' that also perform complex operations. The verb 'execute' and resource 'code' are specific, but the scope is vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'invoke_llm' or 'rest_call'. The description lacks context for appropriate usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose behavioral traits like idempotency, side effects, or permissions. It only states it renders HTML, leaving behavior ambiguous.
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 a single concise sentence that is front-loaded with the verb. It is appropriately sized but lacks parameter 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 no output schema, no annotations, and two unexplained parameters, the description is incomplete. An agent cannot reliably use this tool without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description does not explain parameters (report_data, output_variable_name), their format, or expected values. Defaults are not clarified.
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 renders a social performance analysis as an HTML report and specifies contents (scorecard, top/bottom posts, action plan). It distinguishes from sibling render tools by focusing on social performance.
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 on when to use this tool vs alternatives, such as the sibling tool 'social_performance_analyzer_analyze_performance_action' which likely generates the analysis data. The description does not mention prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description must disclose behavioral traits. It only states 'renders', implying no destructive side effects, but fails to mention if input data is consumed, if any data is stored, or what happens on error. The description does not contradict annotations since none exist.
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 a single sentence that directly states the tool's function. It is front-loaded with the verb and resource, with no extraneous words.
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 too brief. It does not explain input format, output details beyond 'HTML report', or the typical workflow (e.g., use after generation action). The default value hints at a template variable but remains unexplained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain parameters. It does not mention 'report_data' (the packaging data) or 'output_variable_name' (the variable to store the HTML), nor does it explain the default template value. This is a significant gap.
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 verb 'renders' and the resource 'YouTube packaging' with examples (titles, description, tags, thumbnails), and specifies the output is an HTML report. It distinguishes from other YouTube tools by specifying the packaging report, but does not explicitly contrast with the sibling generation tool.
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 youtube_thumbnail_generate_packaging_action or other render tools. There is no mention of prerequisites, such as having generated packaging data first.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as side effects (e.g., API calls, data persistence), required permissions, or assumptions about input quality. For a generative tool with 11 parameters, this omission is significant.
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 a single sentence that lists many components, which is moderately concise but could be better structured (e.g., bullet points) to improve scanability. It is front-loaded with the main 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 11 parameters, no output schema, and no annotations, the description is insufficient. It outlines output contents but does not describe how inputs map to outputs, potential limitations, or expected behavior for edge cases (e.g., missing contact_name).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema coverage is only 9% (one parameter described), yet the description adds no parameter-level explanation. Parameter names are self-explanatory, but the description does not clarify format, defaults, or relationships (e.g., how pain_points interacts with objection playbook).
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 generates a 'structured Call Game Plan' and enumerates 8 specific components (e.g., pre-call intel, opening approach, objection playbook). It uses a specific verb ('Generates') and resource, and distinguishes itself from sibling tools (no other call game plan tool exists).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage 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 like outreach_drafter or meeting_prep. The description implies cold call preparation but does not specify contexts, prerequisites, or situations to avoid.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only says 'gather' without detailing what is returned (e.g., revenue, EPS), whether the operation is read-only, or if there are rate limits or other constraints. This lack of behavioral context reduces transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise and front-loaded. It contains no redundant words. However, it could be slightly more informative without sacrificing 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 lack of an output schema, the description should explain what kind of earnings information is returned (e.g., revenue, earnings per share). It does not, making it incomplete for an agent to fully understand the tool's output. The three parameters are well-covered by the schema, but the return value is opaque.
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% coverage with clear descriptions for all three parameters (company, quarter, year). The description adds no new meaning beyond summarizing the timeframe ('by quarter and year'). 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gathers earnings information for public companies by quarter and year. It uses a specific verb ('gather') and resource ('earnings information'), and differentiates from siblings like 'company_financial_profile' which likely provides broader financial data. However, it doesn't explicitly distinguish itself 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?
No guidance on when to use this tool versus alternatives like 'company_financial_profile'. The description implies it is for earnings by quarter/year but does not state exclusions or prerequisites (e.g., requiring a public company ticker).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description carries full burden. It only states retrieval of information without disclosing data freshness, limitations, or any side effects. Minimal behavioral insight beyond basic purpose.
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?
Single sentence, front-loaded with action verb 'Retrieve', efficient and to the point. No redundancy, but could benefit from more structured listing of outputs.
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, description provides only examples of returned fields (market cap, stock price), not a full specification. Leaves ambiguity about what 'detailed' encompasses. Adequate for a simple tool but not fully complete.
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 coverage is 100% with description of 'company' parameter. Description adds examples of returned data (market cap, stock price) but does not significantly enhance meaning beyond schema. Baseline score applies.
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?
Description clearly states it retrieves financial and company profile info for a stock symbol, with examples like market cap and last stock price. However, it does not distinguish itself from sibling tool 'company_financial_info' which likely has similar purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. No conditions or exclusions provided, leaving the agent to infer usage from purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only states the tool returns a JSON report. It omits whether the research is long-running, uses external APIs, requires cache, or has rate limits. The 'force_refresh' parameter hints at caching but is not explained in the description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with action and output. No waste. However, it could be more informative while remaining 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?
The tool has 19 parameters, no output schema, and no annotations. The description is too sparse to provide complete context about the research flow, synchronous vs asynchronous behavior, or how to interpret the JSON. Sibling tools indicate a rich ecosystem, but this description fails to connect.
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 coverage is 100%, so baseline is 3. The description adds no value beyond the schema; 'configurable sections' merely echoes the boolean flags. The parameter descriptions in schema are adequate, so the description's contribution is minimal.
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 verb 'Run' and resource 'comprehensive company research' with configurable sections and return of JSON report. While it distinguishes from siblings like 'start_research' by implying full execution, it doesn't explicitly differentiate from 'get_report' or 'answer_question'.
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 on when to use this tool vs alternatives. No prerequisites, no warnings about cost or time, no exclusions. The description does not help the agent decide when to choose this tool over others like 'company_research_v2_start_research'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states the output format but fails to mention side effects, state changes, or requirements (e.g., input must be a valid article). This 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence (14 words) that front-loads the action. While brief, it lacks structured details that could aid understanding. It earns a 4 for being efficient but not overly terse.
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 two parameters (one required), no output schema, and no annotations, the description is too sparse. It does not explain input formatting, return structure, or prerequisites, leaving significant gaps for an agent to correctly invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description does not explain the parameters beyond the schema's basic definitions. It mentions the report components but does not map them to 'report_data' or clarify the purpose of 'output_variable_name'. The description adds minimal value over the raw schema.
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 action (renders), the resource (generated article), and the output (HTML report with specific components like SEO metadata, article body, links, checklist). It is distinct from sibling tools such as 'content_creator_generate_article_action' which focuses on generation.
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 lacks prerequisites (e.g., 'Use after generating an article') or exclusions, and there is no differentiation from other render 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description does not disclose behavioral traits such as whether the operation is read-only, required permissions, rate limits, or what 'enriched' means in terms of data quality. The description is insufficient for an agent to understand side effects 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence with no unnecessary words. It is concise but lacks structural elements like sections or bullet points.
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 simplicity (1 param, no output schema), the description provides minimal context. It omits expected return value details, pagination behavior, or any error conditions. An agent would need additional inferences 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 coverage is 100%, with the parameter 'domain' already described. The description adds 'enriched company data' but does not enhance understanding of the domain parameter's format or constraints beyond the schema. Baseline of 3 is appropriate.
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 verb 'gather' and the resource 'enriched company data' with source 'Breeze Intelligence'. However, it does not differentiate from many sibling tools focused on company research (e.g., company_research_v2_get_report, get_hubspot_company_object), so it lacks distinctiveness.
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, nor any prerequisites or exclusions. The description is purely functional without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description implies read-only retrieval but does not explicitly state side effects, authentication requirements, or rate limits. The default query behavior is partially hidden in the schema parameter description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with key information. No extraneous text.
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 simplicity (2 parameters, no output schema, no nested objects), the description covers the basic purpose. However, it does not address error handling, pagination, or response format, which could be relevant.
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 coverage is 100%, and each parameter has a description. The tool description adds some context about defaults for query, but this is already present in the schema. So it meets the baseline for high coverage.
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 it retrieves data for any supported HubSpot object type or the most recent object. It differentiates from siblings like get_hubspot_company_object by being generic, but does not explicitly call out the 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?
No guidance on when to use this tool versus the more specific sibling tools (e.g., get_hubspot_company_object, get_hubspot_contact_object). No alternative mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry full burden. It fails to disclose behavioral traits such as authentication requirements, rate limits, whether the account must be public, or what 'top' means (e.g., by engagement or follower count).
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?
Single sentence is concise and front-loaded, no fluff. However, it lacks necessary context for a fully useful description.
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?
Description is too brief given no output schema. It fails to explain what 'top followers' means, what data is returned per follower, or any additional context needed for effective 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% as both parameters have descriptions. The tool description adds no additional meaning beyond the schema, so baseline score of 3 applies.
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?
Description clearly states verb 'Get' and resource 'top followers for an Instagram account'. It distinguishes from sibling 'get_instagram_profile' which retrieves account profile, not followers.
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 on when to use this tool vs alternatives. Sibling tools like 'get_instagram_profile' exist but no comparison or context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description does not disclose behavioral traits like authentication, rate limits, or whether data is mutated. As a fetch operation, it implies read-only, but this is not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Concise single sentence that front-loads the verb and resource. The phrase 'for social media analysis' adds context but is not essential.
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?
No output schema exists, and the description does not explain the return format or data structure. For a tool fetching posts, the agent needs to know what fields and format to expect.
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 coverage is 100%, so baseline is 3. The description adds no extra meaning beyond the parameter descriptions already in the schema.
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 verb (Fetch), resource (recent LinkedIn posts), and context (social media analysis). It distinguishes from siblings like get_linkedin_company_posts by focusing on 'specified profiles', but does not explicitly differentiate from get_linkedin_posts.
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 such as get_linkedin_company_posts or get_linkedin_posts. The context is implied but not clearly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description must bear full burden. It implies read-only but omits details like pagination, rate limits, authentication needs, or what constitutes 'recent'.
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 a single short sentence, which is efficient. However, it lacks structure and detail, but is not verbose or wasteful.
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?
No output schema is provided, and the description does not hint at the return format or fields. For a retrieval tool, this is insufficient, especially given similar sibling tools.
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 coverage is 100% with the parameter description already clear. The tool description adds no further meaning to the sole parameter, so baseline 3 applies.
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 ('retrieve') and the resource ('recent posts and content from a LinkedIn company page'). It distinguishes from siblings like get_linkedin_posts (likely for individual profiles) and get_linkedin_activity (broader activity), though not explicitly.
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 on when to use this tool versus alternatives like search_linkedin_posts_by_keyword or get_linkedin_posts. No exclusions or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, and the description does not disclose behavioral traits like rate limits, data freshness, or whether the tool can access private profiles. The only information is that it retrieves 'detailed information,' which is vague.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that conveys the core purpose concisely. However, it lacks structure or additional details that could be included without significant bloat, such as common use cases.
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 only one parameter, the description is sparse. It fails to mention expected return format, field names, or limitations. For a data retrieval tool, more context is needed to set appropriate expectations.
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% coverage, so the description does not need to add much. It specifies 'profile_handle' and states it is required, but does not provide examples or clarify format (e.g., username vs. full URL). The description adds minimal value beyond the schema.
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 retrieves detailed LinkedIn profile information for professional insights. However, it does not distinguish itself from sibling tools like find_linkedin_profile or search_linkedin_people, which may also retrieve profile data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. There is no mention of prerequisites, such as requiring a public profile or specific authentication, nor any exclusions for private or restricted profiles.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states 'search and retrieve' without disclosing behavior like rate limits, authentication requirements, or result format. This is insufficient for transparent usage.
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 (12 words) and efficiently communicates the tool's purpose. However, it could benefit from a slight structure, such as separating the action from the context.
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?
For a simple 2-parameter tool, the description covers the basic purpose, but it omits important contextual details like return behavior, error handling, and when to use alternatives. This leaves gaps for an agent to fully understand the tool's capabilities.
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 coverage is 100%, with clear descriptions for both parameters. The description adds no additional meaning beyond what the schema provides, so a baseline of 3 is appropriate.
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?
Clearly states the action (search and retrieve), resource (Twitter user profiles), and context (for social media analysis). However, it does not explicitly differentiate from similar sibling tools like get_recent_tweets or search, which have distinct focuses.
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 on when to use this tool versus alternatives. It lacks explicit context for appropriate usage, such as when to choose this over search or get_recent_tweets.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It describes the tool as producing output ('Produces an...'), implying a read-only or computational action, but does not confirm whether it modifies state, requires authentication, or has side effects. The absence of safety disclaimers is a significant gap.
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 a single, well-structured sentence (20 words) that immediately conveys the core deliverable. Every word adds value, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 (7 parameters, 4 required, no output schema), the description is too sparse. It does not explain how parameters like 'fit_context' or 'seller_website' influence the qualification, nor does it describe the return structure (e.g., how the score, timing, and priority are formatted). For a qualification tool, users would benefit from examples or edge-case behavior.
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 coverage is 71%, and the description adds no parameter-level information beyond what the schema already provides. The description mentions 'ICP-grounded' but does not elaborate on how specific parameters like 'fit_context' or 'seller_website' contribute. Baseline 3 is appropriate since schema descriptions do most of the work.
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 produces an 'ICP-grounded qualification' with specific outputs (fit score, timing assessment, priority recommendation). It distinguishes from sibling 'lead_qualifier_render_qualification_html' by implying this tool generates the raw data, not the rendered report. However, it could be more explicit about the resource being qualified (e.g., a lead or company).
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. It implies use for ICP-based lead qualification but does not state when not to use it, nor does it reference sibling tools like 'prospect_finder_find_and_rank_prospects' or 'prospect_research_research_prospect' that might be more appropriate for earlier stages.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It mentions enriching with details but does not disclose whether the operation is read-only or mutates the event, nor does it mention required permissions or side effects like writing to storage.
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 a single sentence that is front-loaded with the purpose. While concise, it could be slightly expanded to cover key behavioral aspects without becoming verbose.
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 6 parameters and no output schema, the description is incomplete. It omits the fact that results are stored in a variable (output_variable_name), does not explain dependencies (e.g., event must have occurred), and lacks guidance on typical usage flow.
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 coverage is 100%, so baseline is 3. The description adds no extra meaning beyond the schema, which already documents each parameter clearly. No additional context or constraints are provided.
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 verb 'enriches' and the resource 'past calendar event', and lists what is added (transcript, AI insights, attendees). However, it does not explicitly distinguish from the sibling tool 'enrich_calendar_event', leaving ambiguity about uniqueness.
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 implies use with past events but provides no guidance on when to prefer this tool over alternatives like 'enrich_calendar_event' or other meeting follow-up tools. No when-not-to-use or prerequisite information is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits but only vaguely implies reading. It does not state whether the tool is read-only, has side effects, or requires specific permissions. The lack of clarity on mutation versus query is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, making it very concise. It front-loads the key action and resource. However, it may be too brief, sacrificing detail for 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 the tool (4 parameters, no output schema, many sibling tools), the description is too sparse. It does not explain the return value, storage behavior (despite 'output_variable_name' parameter), or how this tool fits into the meeting prep pipeline. This leaves the agent with insufficient context for correct invocation.
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 coverage is 100% and parameter descriptions are adequate. The description adds little beyond summarizing the schema fields (user_data, user_email, meeting_type, output_variable_name). Since the schema already documents each parameter, the description provides marginal added semantic value.
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 it loads user profile data, voice preferences, and meeting goals for personalization, making the primary action and resource clear. However, it does not explicitly differentiate from sibling tools like meeting_prep_v3_load_user_context, leaving some ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, such as the v3 variant or other meeting prep tools. There is no mention of prerequisites or context that would help an agent decide to invoke this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states it 'generates a summary.' It does not disclose whether the tool is read-only or destructive, nor does it mention that it may use an LLM (see use_llm parameter) or that it processes existing data without side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is direct and free of unnecessary words. It efficiently conveys the core function.
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?
The tool has 7 parameters (4 required) and no output schema. The description does not explain the return value format, the role of each parameter, or how the summary is constructed. For a tool in a complex pipeline, this is 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?
Schema description coverage is 100%, so baseline is 3. The description adds limited value beyond schema: it mentions 'internal team members' and 'organizer identification,' which align with parameters like classified_attendees and processed_gcal_event, but does not elaborate on optional parameters like contact_research_results or use_llm.
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 generates a summary of internal team members and identifies the organizer. However, it could be more specific about the summary content, e.g., roles, responsibilities. It distinguishes from sibling tools like meeting_prep_classify_meeting or meeting_prep_process_calendar_event.
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 meeting_prep_analyze_meeting_relationships. The description omits prerequisites, such as requiring classified_attendees from a previous step, and fails to indicate that it is part of a larger pipeline.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must cover behavioral traits. It mentions 'validation and completeness scoring' but does not explain what validation entails, how scoring works, side effects, authentication needs, or rate limits. Key behaviors are unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no redundancy. It is efficient but could be expanded slightly for completeness without losing conciseness.
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 6 parameters, no output schema, and no annotations, the description is insufficient. It omits return values, error conditions, and the purpose of output_variable_name beyond 'store.' Missing critical context for correct invocation.
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 coverage is 100% for all 6 parameters, so baseline is 3. The description adds no additional meaning beyond the schema; it does not explain how parameters relate to validation or scoring. No improvement over schema.
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 it loads user profile, preferences, and seller profile with validation and completeness scoring. It specifies the resource (user context) and what it does (load), distinguishing it from other meeting prep tools by including 'V3' and mentioning scoring.
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 on when to use this tool versus alternatives like the V2 version or other meeting prep load tools. No exclusions or context provided, leaving the agent to guess when this 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?
With no annotations, the description must convey behaviors. It only mentions generating personalized sections but omits side effects, authentication needs, data processing flow, or output format. The agent cannot infer whether this pipeline is read-only or modifies state.
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 a single, front-loaded sentence that efficiently conveys the core purpose without unnecessary words. It earns its place.
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 (11 parameters, no output schema, no annotations), the description is insufficient. It lacks explanation of what the pipeline outputs, how to use the result, and any constraints or dependencies.
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 coverage is 100%, so the schema already describes all 11 parameters. The description adds no extra meaning beyond that, making it baseline 3.
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 identifies the tool as a V3 meeting prep pipeline with seller profile integration, generating personalized sections. This distinguishes it from similar tools (e.g., v2 pipeline and sub-tools) by highlighting the version and seller profile feature.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 pipeline vs. other meeting prep tools (e.g., v2 or individual v3 sub-tools). The agent has no information about prerequisites or 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, so the description must disclose behavioral traits. It only says 'Format and display results' but does not state side effects, idempotency, or whether it requires user interaction. The description is too vague.
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 a single sentence of 13 words, concise and front-loaded. It efficiently conveys the core purpose without fluff, though could include a tiny bit more context without harming conciseness.
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?
For a simple display tool with well-documented parameters and no output schema, the description is adequate but not thorough. It lacks details on what happens after formatting (e.g., user presentation vs. return value) and does not leverage sibling 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?
All three parameters have descriptions in the schema (100% coverage), so the description adds minimal value beyond listing example formats. The baseline is 3, and the description does not significantly enhance understanding.
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 formats and displays results in HTML, JSON, tables, or other formats, which matches the input schema's format enum. It distinguishes itself from more specific sibling render tools by being generic, though it could explicitly mention that.
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 specific render tools (e.g., render_html). No usage context or exclusion criteria are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as whether it is read-only, side effects, required permissions, or output format. The tool name and description imply it generates HTML, but details are missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is concise and front-loaded. However, it lacks necessary detail, making it under-specified for a complete tool definition.
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 two parameters with no descriptions, no output schema, and no annotations, the description is incomplete. It does not clarify the output behavior, parameter roles, or how to integrate the tool into a workflow.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description adds minimal meaning beyond parameter names. It does not explain that prospect_finder_result likely contains the data to render or what output_variable_name does. The defaults hint at templating but are not described.
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 it renders a prospect discovery report as professional HTML with specific components like prospect cards, ICP match badges, and next-step buttons. This distinguishes it from sibling render tools that focus on other types of reports.
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 description does not mention prerequisites, typical workflow (e.g., calling after prospect_finder_find_and_rank_prospects), or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as authentication requirements, rate limits, or the nature of the search results (e.g., single vs multiple profiles).
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 a single, concise sentence that immediately conveys the action and scope. No redundant information is present.
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 simplicity, the description is minimal and lacks information about output format, pagination, or error handling. For a search tool, the absence of output schema details and behavioral context makes it 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 already fully describes both parameters with clear descriptions. The description adds no additional semantic value beyond what the schema provides. Baseline score of 3 is appropriate for 100% schema coverage.
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 searches for LinkedIn profiles using first and last names, making the purpose clear. However, it does not differentiate from the sibling tool 'find_linkedin_profile', which may have a similar function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 over alternatives like 'get_linkedin_profile' or 'search_linkedin_jobs'. There is no context about prerequisites or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only says 'Send a message,' which implies a write operation, but it does not disclose any behavioral traits such as side effects, authentication requirements, rate limits, or whether the message is actually sent (e.g., confirmation). This is insufficient for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 13 words, which is appropriately concise and front-loaded. It communicates the essential purpose without unnecessary detail. However, it could potentially include a bit more context without becoming verbose.
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 5 parameters and no output schema or annotations, the description is too minimal. It does not explain what happens after sending (e.g., return status, error handling), nor does it provide formatting expectations for the message content. A tool of this complexity requires more detail to be fully complete.
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% coverage with descriptions for all 5 parameters. The description does not add any extra meaning beyond what is already in the schema. Per guidelines, with high schema coverage, the baseline is 3, and the description meets this baseline without adding value.
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 verb ('Send') and resource ('message'), and gives a specific example ('email with formatted content'). However, it might be interpreted as supporting multiple message types, while the schema only allows 'email'. Sibling tools include social media tools like 'post_to_bluesky', but no other email tool, so it is distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage 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. No explicit when-to-use, when-not-to-use, or alternative tools are mentioned. Given the lack of context, the agent would have to infer usage from the tool name and schema alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully carries the burden of transparency. It only lists high-level outputs without disclosing side effects, data dependencies, or limitations. Does not state that the tool is read-only or that it may modify state.
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?
Single sentence, front-loaded with the core purpose. No redundancy. Could be slightly more structured but is effective for a high-level overview.
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 (7 parameters, no output schema), the description is insufficient. It does not explain the 6 dimensions, how results are returned, or how to interpret output. The presence of a render tool is not mentioned.
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 coverage is 71%, so baseline is 3. The description adds no additional meaning to parameters; it only describes outputs (e.g., '6 dimensions', 'benchmarks') that are not reflected in the schema.
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?
Description clearly states the tool analyzes LinkedIn posting performance with specific deliverables (benchmarks, performers, action plan). However, it does not differentiate from sibling tools like social_performance_analyzer_render_analysis_report, which likely renders the output.
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 on when to use this tool vs alternatives. Does not mention prerequisites, context, or cases where it should not be used.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description fails to disclose behavioral traits like idempotence, required permissions, or side effects. Only states basic action without addressing safety or state changes.
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?
Single sentence is concise but overly brief. Lacks structured detail; could include parameter info or usage context without sacrificing conciseness.
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?
With 2 parameters, no output schema, and no annotations, the description is incomplete. Does not specify input format or return value structure, leaving agent guessing about integration.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, and description does not explain parameters. 'report_data' default is a template variable but not defined; 'output_variable_name' purpose is unclear. Agent cannot infer how to populate or use these.
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?
Description clearly states the verb 'renders', resource 'weekly social content plan', and output 'HTML report with post idea cards'. Distinguishes from sibling tools like social_planner_generate_plan_action which creates the plan, and social_post_creator_render_post_report which renders individual posts.
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 on when to use this tool vs alternatives. Does not mention prerequisites (e.g., needs a pre-generated plan) or situations to avoid. Sibling tools exist but no comparative context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits. It only states what the tool does (renders HTML) but does not mention side effects (none), output handling (e.g., stored in a variable), or that it is a read-only operation. The behavioral description is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise but overly minimal. It lacks necessary information like usage context and parameter roles, so it is not adequately informative given the tool's complexity.
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, no output schema, and two parameters, the description is incomplete. It does not explain that this tool is part of a pipeline (e.g., after generating ideas), nor does it describe the return format or how the output variable is used. The default parameter hints at a chain, but the description should be explicit.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50%, but the tool description adds no parameter details. It does not explain that 'report_data' comes from the generate ideas action or that 'output_variable_name' stores the result. The description fails to compensate for the lack of schema details.
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 renders YouTube video ideas as a formatted HTML report with idea cards and trending context. The verb 'Renders' and resource 'YouTube video ideas' are specific, distinguishing it from the generation tool 'youtube_idea_research_generate_youtube_ideas_action'.
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 on when to use this tool versus alternatives. The description does not indicate that it should be used after generating ideas, though the default parameter suggests a chain. No explicit when/not or comparison to sibling render tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It mentions the output format but does not state whether the tool is read-only, if it modifies data, or any limitations. The description provides minimal behavioral context beyond the output content.
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 a single sentence of 13 words, which is concise. However, it fails to include necessary parameter details, making it incomplete. It earns points for brevity but loses for missing essential 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 the tool has no annotations, no output schema, and 0% schema description coverage, the description is incomplete. It does not cover parameter usage, behavioral traits, or differentiate from similar render tools among siblings. It provides basic purpose but lacks depth for an agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain parameters. It does not mention report_data (the script content) or output_variable_name (where to store the result). The default values are not explained, leaving the agent without crucial information for correct invocation.
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 renders a YouTube script as an HTML report with timed sections and production cues. It uses a specific verb ('renders'), identifies the resource ('YouTube script'), and describes the output format, distinguishing it from generation tools like youtube_script_writer_generate_youtube_script_action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool should be used after a script is generated, but it does not explicitly state when or when not to use it, nor does it compare with other render tools. Usage context is implied but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It implies a mutation but fails to specify side effects (e.g., what happens if the company is already tracked, whether it overrides existing data, or auth requirements). No mention of rate limits or error scenarios.
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 a single concise sentence, which is front-loaded. However, it is too brief and could include more useful information without sacrificing conciseness.
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 (5 parameters, no output schema, no annotations), the description is incomplete. It does not explain the return value (despite the 'output_variable_name' parameter), error handling, or persistence behavior. A tracking tool should clarify these aspects.
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 coverage is 100%, so the input schema already describes each parameter. The description adds no additional meaning beyond the schema; for example, it doesn't clarify how to choose between 'domain' and 'company_id' or the expected format of 'tags'. Baseline 3 is appropriate.
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 action ('Add a company'), the resource ('to the user's tracked list'), and the purpose ('for monitoring'). It effectively distinguishes from the sibling tool 'company_research_v2_list_tracked' which lists tracked companies.
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 (e.g., list_tracked for viewing, a hypothetical remove tool). It does not mention prerequisites, such as whether the company must already exist in the system, or conditions like duplicate handling.
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 reveals the tool transforms an outreach package into HTML, but does not explicitly state it is a pure render without side effects. No annotations are provided, so the description must carry this burden; it provides moderate context but lacks details on permissions, rate limits, or data handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise. It front-loads the main purpose. However, it lacks any structural elements like bullet points or separate sections that could improve 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 absence of annotations and output schema, the description should provide more context about the output format, prerequisites, or potential side effects. It only mentions the content of the HTML but not how to use the output or what the output variable represents.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, requiring the description to compensate for parameter meanings. However, the description does not elaborate on the two parameters (outreach_package, output_variable_name) at all, leaving the agent to infer their purpose from names alone.
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 function: rendering an outreach package into professional HTML. It mentions specific outputs (email variants, LinkedIn messages, personalization audit) which distinguishes it from sibling tools like outreach_drafter_draft_outreach or outreach_sequence_generate_outreach_sequence.
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 on when to use this tool versus alternatives. It does not specify prerequisites (like needing to draft an outreach package first) or contexts in which this tool is appropriate. No exclusions or alternatives mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits. It only states the basic purpose, omitting details like rate limits, authentication, return format, or pagination 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 a single sentence, which is concise but lacks structure and depth. It is front-loaded but too brief to add significant value.
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, the description should explain return values and behavior. It does not cover what the tool returns or how it handles edge cases, making it 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?
Schema coverage is 100%, so the schema already documents both parameters. The description adds no extra meaning beyond what the schema provides, meeting the baseline but not going further.
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 action ('Search for') and the resource ('Bluesky posts') with the criteria of matching keywords. It distinguishes this tool from siblings like 'get_bluesky_posts' (retrieval) and 'post_to_bluesky' (creation).
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 such as 'get_bluesky_posts' or general 'search'. The description does not specify context or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral disclosure. It implies a read-only operation ('Get'), but does not explicitly state it is non-destructive, requires no special permissions, or what happens if the report is incomplete. Significant gaps remain.
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 a single, clear sentence with no filler. It is appropriately front-loaded for a simple retrieval tool, though it could benefit from a second sentence to elaborate on return value or prerequisites.
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 output schema and 3 parameters, the description is too minimal. It does not explain what constitutes a 'completed' report, the response structure, or how optional HTML is generated. Sibling tools provide some context, but the description itself is 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?
Schema coverage is 100% (all 3 parameters described in the schema). The description adds only the phrase 'with all sections and optional HTML content', which loosely maps to include_html but does not provide meaning beyond the schema. Baseline 3 is appropriate.
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 uses the specific verb 'Get' and clearly identifies the resource as a 'completed research report with all sections', which distinguishes it from siblings like company_research_v2_get_section (single section) and company_research_v2_render_html (HTML only).
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. For instance, it does not mention that get_section is for a single section, or that get_status is for checking progress. The description offers no exclusion criteria or context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. However, it only states the basic action without indicating side effects (likely none), authorization needs, or read-only nature. This 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no redundant words. However, it is so concise that it omits potentially useful information, yet it remains efficient for its 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 3 parameters, an enum, and no output schema, the description is too minimal. It fails to hint at the available sections (though schema lists them), what the returned data looks like, or prerequisites (e.g., a report must be researched first).
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 coverage is 100% with descriptions for all parameters, so the baseline is 3. The description adds no additional meaning beyond the schema, such as explaining the role of output_variable_name or the purpose of each section key.
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 'Get a specific section from a research report' clearly states the action (get) and the resource (section of a report). It distinguishes itself from sibling tools like get_report (full report) and get_status (status).
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 lacks any guidance on when to use this tool versus alternatives. For example, it does not mention that for a full report, one should use get_report, or that this tool is for retrieving individual sections after a report is generated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description adds 'Extracts filters' implying parsing behavior but no details on safety, rate limits, or side effects. Adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Very short single sentence, no wasted words. Could benefit from slight expansion for clarity, but appropriately 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?
No output schema and description omits return format (e.g., company fields, pagination details). Without this, agent cannot effectively use results. Among sibling tools, lacks relational 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 coverage 100% so baseline 3. Description adds minimal extra meaning beyond schema (only mentions filter extraction for query parameter). No additional semantics for page, page_size, or output_variable_name.
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?
States 'Search for companies using natural language query' with specific verb and resource. Mentions filter extraction, differentiating from generic search tools, but doesn't explicitly distinguish from sibling company research search 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 guidance on when to use this tool vs alternatives like `company_research_v2_run_full_research` or `get_search_results`. Lacks context for tool selection among many siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must disclose behaviors. It only mentions generating a brief and returning JSON, without covering caching, data sources, auth, processing duration, or side effects. The presence of a force_refresh parameter hints at caching but is not explained in the description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise. However, given the tool has 14 parameters, the description could benefit from slightly more context without becoming verbose. It is 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?
The tool has 14 parameters, no output schema, and many sibling tools. The description does not explain what constitutes a 'full brief,' how the output JSON is structured, or how this tool differs from similar research tools. It is insufficient for an agent to fully understand its capabilities.
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. The tool description adds no extra meaning beyond stating it generates a full brief. Baseline 3 is appropriate as description does not degrade but adds minimal value.
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 generates a comprehensive competitive intelligence brief with all sections and returns full JSON output. The verb 'generate' and resource 'competitive intelligence brief' are specific, and it distinguishes from siblings like competitive_brief_render_brief_html.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. The sibling list includes many research tools, but the description offers no context about when this specific tool is preferred, such as for generating a complete brief vs. other partial research tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries burden. It mentions output format but omits behavioral details like side effects, required permissions, or input constraints. For a non-trivial render tool, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no redundant words. It delivers core purpose immediately.
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?
While the output structure is hinted, key information—parameter usage, input expectations, output details beyond the listed sections—is missing. Given no schema descriptions and no output schema, the description should compensate but does not.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description does not explain the two parameters (report_data, output_variable_name) or their expected formats. Default values offer minimal clues, but no meaningful guidance is added.
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 renders a content audit as an HTML report with specific sections (site health dashboard, findings, page inventory). It uses a specific verb ('renders') and resource ('content audit'), effectively distinguishing it from sibling tools like content_audit_generate_audit_action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context—rendering an already-generated audit—but does not explicitly state when to use this tool versus alternatives (e.g., other render reports) or exclude cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It only states the conversion action, omitting key details like whether the original file is preserved, if the operation is asynchronous, any size or format limitations, or what the output is (e.g., a URL).
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 a single, clear sentence with no filler. It efficiently conveys the core purpose.
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?
For a simple two-parameter tool with no output schema, the description covers the basic purpose but lacks context about output handling, error scenarios, or supported formats beyond the examples. It is minimally adequate.
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 coverage is 100%, so the baseline is 3. The description adds no additional meaning beyond what the input schema already provides for the two parameters (input_file and convert_to_extension).
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 states the tool converts uploaded files to different formats like PDF, TXT, or PNG, which clearly communicates the verb (convert) and resource (files). However, it does not differentiate from similar sibling tools like file_converter_convert_action or convert_file_options, which likely perform the same function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, such as convert_file_options or other file_converter tools. There are no prerequisites, exclusions, or contextual cues to help an agent decide.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must fully disclose behavior. It only states it 'gets' options, without mentioning network calls, caching, data source, or result structure.
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?
Single sentence, front-loaded with action verb. Very concise with no wasted words, though could slightly elaborate on output without harming conciseness.
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?
With no output schema and no annotations, the description should at least hint at return format or scope. It omits what the 'options' look like, leaving the agent underinformed.
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 coverage is 100% with description 'File extension' for the parameter. The tool description adds no further semantics like format examples or case sensitivity, staying at baseline for high coverage.
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?
Description uses specific verb 'Gets' and resource 'full set of options that a file extension can be converted to', clearly distinguishing it from convert_file and other file conversion tools that actually perform actions.
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 on when to use this tool versus alternatives. It does not indicate that this should be called before conversion or describe any prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It lists operations but fails to disclose side effects, security implications, or behavior beyond the obvious. For example, it does not mention that the tool is non-destructive or that it stores output to a variable.
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 a single, front-loaded sentence that uses concise language to list core operations. Every word serves a purpose, with no redundancy or filler.
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 simplicity (4 parameters, no output schema), the description adequately covers the high-level purpose but omits details like the output storage mechanism and delimiter usage. It is minimally complete.
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 description does not need to add parameter details. The description adds no additional meaning beyond the schema, providing a baseline score of 3.
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 'Change casing, remove characters, split text, remove HTML, or truncate text' clearly lists several text transformation operations, making it clear this is a general text formatting tool. However, it does not mention all format types in the enum (e.g., join_text, convert_to_json), and it lacks specificity that would distinguish it from unrelated 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 guidance on when to use this tool versus alternatives, nor any conditions or prerequisites. It simply lists capabilities without contextual cues for agent selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral traits, yet it omits details such as rendering time, image format, error handling, or caching behavior (despite a ttl parameter), making it insufficient for an agent to predict side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words, though it could incorporate more useful information without sacrificing 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 absence of an output schema, the description fails to specify what the tool returns (e.g., image data, URL), and lacks details on limitations or prerequisites, making it incomplete for a fetch tool.
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 coverage is 100%, so baseline is 3. The description adds no extra meaning beyond the schema; for instance, it doesn't clarify the purpose of the ttl_for_screenshot parameter or how the URL should be formatted.
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 action ('Capture a visual screenshot') and the target resource ('specified web page'), effectively distinguishing it from sibling tools like grab_web_text which captures text content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 (e.g., grab_web_text), no context on prerequisites or exclusions, leaving the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the tool sends an email with specific content, but lacks behavioral details such as whether it requires permissions, is idempotent, handles failures, or modifies state. The basic function is clear, but deeper traits are missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence (146 characters) that front-loads the verb 'Sends' and efficiently conveys the tool's action and content. No wasted words.
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 no annotations, the description should compensate. It explains the email content but omits behavioral context (e.g., failure modes, usage, output variable purpose). For a 3-parameter tool with one required, more completeness is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not add meaning beyond the input schema. The schema already describes report_id and email adequately; the description's mention of email content is about the output, not parameters. The required output_variable_name parameter is undocumented in both schema and description.
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 sends an industry research report as a formatted email, mentioning specific sections (Market Overview, Key Players, personalized implications teaser). It distinguishes from the sibling tool industry_research_generate_research_action, which likely generates the report.
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 implies usage after generating a report via the report_id default value, but does not state prerequisites, when not to use, or alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It doesn't disclose whether the call is synchronous, what side effects occur, or how results are retrieved. Vague on behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, concise. However, could be improved with structure like examples or bullet points.
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?
No output schema and lack of return value explanation. Description does not specify how to retrieve agent results or handle errors, leaving gaps for a 2-param tool.
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 coverage is 100%, baseline 3. Description adds no extra parameter info beyond schema, and schema descriptions are adequate but not detailed.
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 action ('trigger') and resource ('another agent'), distinguishing it from sibling agent tools like 'describe_agent' or 'query_agent_kb'.
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 on when to use this tool versus alternatives like 'invoke_llm' or 'openclaw_tools_invoke'. Missing context on prerequisites or preferred use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavior. It does not state that this is a read-only operation, nor does it mention pagination, ordering, or what happens with no results. The description is minimal and leaves the agent to infer safety from the 'list' verb.
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 a single, front-loaded sentence that efficiently communicates the core purpose. No wasted words, but could be slightly expanded to include the agent override possibility. Still concise enough to be effective.
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 an output schema, the description should explain the return format. It mentions 'topics, keywords, and previews' but does not clarify structure, pagination, or the effect of the include_full_content parameter. The description is incomplete for an agent to fully understand the tool's output.
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?
All 6 parameters have schema descriptions (100% coverage), so the schema already provides meaning. The description adds only a redundant mention of the keyword filter. It does not add new semantic value beyond what the schema offers, meeting the baseline for high coverage.
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 verb 'list' and resource 'memories', with specific details about contents (topics, keywords, previews) and an optional filter. It distinguishes from siblings since no other tool lists memories, though it omits the agent_id_override capability.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions the optional keyword filter, giving a basic usage hint. However, it provides no guidance on when to use this tool versus alternatives (e.g., query_agent_kb) or exclusions. The usage context is implied but not explicit.
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 mentions using Jinja2 templates and not requiring an LLM, which is a positive behavioral trait. However, with no annotations provided, the description lacks details on idempotency, side effects, or authentication needs. The given info is somewhat helpful but insufficient.
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 a single, concise sentence that conveys the core function and a key distinguishing feature. It is front-loaded and efficient, though could be slightly expanded for completeness.
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 7 parameters and no output schema, the description is too brief. It does not explain the relationship to sibling tools or provide context on how inputs are used. The schema helps, but the description should offer a more comprehensive overview, such as the typical pipeline 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%, so the input schema already documents all parameters. The tool description adds no extra parameter meaning beyond the schema, so baseline score of 3 is appropriate.
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 it renders a meeting followup document as a professional HTML email, using Jinja2 templates. The purpose is specific and distinguishable from sibling render tools, though it does not explicitly differentiate from other 'render' 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 guidance on when to use this tool versus alternatives, such as other render tools or when to skip LLM usage. The 'No LLM required' note is a capability hint but not usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, description carries full burden. Only states 'Extracts' with no mention of side effects, permissions, idempotency, or data storage. Minimal behavioral disclosure.
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?
Single sentence, front-loaded, no redundant words. Efficiently conveys core information.
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?
Despite high schema coverage, no output schema and no annotations. Description is minimal, missing details on return value format or constraints like existence of event ID. Adequate but not comprehensive.
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 coverage is 100% with detailed parameter descriptions. The tool description adds no additional meaning beyond what the schema already provides, meeting the baseline for high coverage.
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?
Description clearly states verb 'Extracts' and resource 'selected meeting details from a list of Google Calendar events based on meeting ID'. It is specific but does not explicitly differentiate among many meeting_prep sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. No preconditions, exclusions, or context provided. Agent must infer from 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It states 'generates' but does not mention side effects (e.g., storing a variable), permissions, or limits. The description is too brief to be transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence. It is efficient but lacks any structural elements (e.g., bullet points or sections) that could improve readability. Slightly deducting for minimal structure.
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 3 parameters and no output schema, the description should explain how parameters interact (e.g., meeting_title vs selected_meeting) and the expected output format. It provides none of this, leaving the agent underinformed.
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 coverage is 100% (all parameters described). The description adds no extra meaning beyond the schema; it simply restates the tool's purpose. Baseline 3 is appropriate since the schema does the work.
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 uses a specific verb ('generates') and resource ('email subject line for the meeting prep document'), making the tool's function clear. It distinguishes from sibling tools (e.g., meeting_prep_analyze_meeting_relationships) by focusing on a single sub-task.
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 on when to use this tool versus alternatives (e.g., meeting_prep_generate_meeting_sections). The description omits context such as prerequisites or scenarios where this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It vaguely mentions 'data retrieval or updates' but omits critical details like authentication requirements, rate limits, side effects, error handling, or response format. This leaves significant ambiguity for an agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at one sentence (13 words) and front-loaded. It earns its place by being succinct, though it sacrifices informational depth.
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 4 parameters and no output schema or annotations, the description is insufficient. It fails to explain response behavior, error handling, or security implications, leaving an agent with inadequate context to use it 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 coverage is 100%, so the input schema already describes each parameter. The description adds no extra meaning beyond 'RESTful API call' and does not clarify parameter semantics such as expected formats for headers/body or the effect of the method parameter.
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 makes a RESTful API call for data retrieval or updates, specifying the verb and resource. Among many sibling tools specialized in specific domains, 'rest_call' stands out as a generic HTTP client, making its purpose distinct.
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 (e.g., other data-fetching tools like 'search' or 'get_calendar_events_list'). There are no when-not-to-use conditions or prerequisites mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It mentions return fields but lacks details on rate limits, authentication, or the role of Fiber.ai. Behavior is partially disclosed but insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence that front-loads purpose and return value. No redundant information.
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?
With no output schema, description partially explains return fields but omits pagination, limits, or Fiber.ai specifics. Adequate but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameter details are already in schema. Description does not add extra meaning beyond stating 'keywords' and return fields; baseline score of 3 is appropriate.
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 verb 'Search' and resource 'LinkedIn posts' with 'keywords', and lists return fields. However, it does not differentiate from sibling tool 'get_linkedin_posts', which may have similar functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 siblings like 'search_linkedin_jobs' or 'search_linkedin_people'. No context on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Lacks details on overwriting behavior, data retention, or side effects. Merely states 'store and track' without deeper behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no redundancy. Front-loaded with purpose. Every sentence adds value.
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 one parameter, no output schema, and no annotations, the description is minimally adequate. Could mention timestamp-based history or retrieval semantics, but acceptable.
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 coverage is 100% with a single parameter 'variable'. Description adds context about storage and tracking, but does not elaborate on parameter format or valid values. Adequate but not exceptional.
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?
Description clearly states the tool stores and tracks a variable and implies future retrieval, distinguishing it from sibling get_variable_from_database. However, it does not explicitly name the sibling.
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 like save_to_agent_kb. Does not mention context or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must fully disclose behavior. It mentions 'cached data' but the parameter 'use_live_data' (default true) suggests live web search is included, creating ambiguity. No disclosure of side effects, permissions, or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, efficiently communicating the core purpose without extraneous words. It is appropriately front-loaded and 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?
Despite having 4 parameters and no output schema, the description fails to explain key aspects like output format, interaction between cached and live data, or prerequisites. The agent lacks sufficient context for correct invocation.
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 each parameter having a basic description. The tool description adds minimal extra meaning (e.g., 'cached data'), but the default behavior of use_live_data contradicts this. Overall, the schema already provides adequate semantic information.
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: answering custom research questions about a company using cached data and LLM. It effectively distinguishes from siblings like get_section or get_report by focusing on custom questions.
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 on when to use this tool versus alternatives like ask_domain_question or get_section. The description does not mention exclusions or preferred contexts, leaving the agent without decision criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the output components (SEO metadata, linking suggestions, etc.) but does not mention behavioral traits like requirements, side effects, or limitations. It is somewhat transparent but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is concise and front-loaded with the primary action. It lists key output components without waste. However, it could be slightly more structured with separate clauses.
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 (8 parameters, no output schema, no annotations), the description is too brief. It does not cover important details like output format, enum meanings, or how parameters affect output. Incomplete for agent decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 25%, and the description does not explain any parameters beyond the overall purpose. It fails to compensate for low schema coverage, providing no additional meaning for parameters like topic, target_keyword, content_type, etc.
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 generates a complete, publish-ready article with specific components (SEO metadata, linking suggestions, image prompt, checklist). The verb 'generates' and resource 'article' are specific, and it distinguishes from siblings like content_planner and social_post_creator.
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 on when to use this tool versus alternatives. The description does not mention prerequisites, context, or when not to use it. It simply describes the output without any usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as authentication needs, rate limits, or the extent of data retrieved. It only implies a read operation without specifics.
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 a single, front-loaded sentence with 9 words. It is very concise, but could include more context without sacrificing conciseness.
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 simplicity of the tool (1 param, no output schema, no annotations), the description is adequate but lacks details about the output format or types of details returned. It is minimally complete.
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 coverage is 100% (the parameter 'domain' is described in the schema). The description adds no additional meaning beyond what the schema already provides, so the baseline of 3 is appropriate.
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 verb 'Gather' and the resource 'domain', specifying it retrieves registrar details. This distinguishes it from sibling tools that focus on company research or social media profiles.
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 on when to use this tool vs alternatives. There are sibling tools like 'company_research_v2_ask_domain_question' that could also provide domain info, but the description does not clarify when to choose this one.
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 it uses CloudConvert and supports many formats, but fails to disclose critical behavioral traits such as whether conversion is synchronous or asynchronous, file size limits, authentication requirements, or what happens to the original file. This is insufficient for safe and correct invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but lacks structure. Given the complexity of the tool (4 parameters, conversion process), it could benefit from brief bullet points or a more detailed breakdown. The length is appropriate but the flat structure limits 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?
The description does not explain the return value or output format, and there is no output schema. The agent does not know what the result of the conversion will be (e.g., a URL or file path). Additionally, siblings like file_converter_render_conversion_report suggest that output handling may be separate, which is not clarified. The description is incomplete for reliable 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 each parameter having a clear description in the input schema. The tool description adds no additional meaning beyond what the schema provides, so baseline 3 is appropriate.
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 verb 'convert' and the resource 'file from one format to another', and specifies the scope using CloudConvert with 200+ formats. It distinguishes from siblings like file_converter_encrypt_action, file_converter_merge_action, etc. by focusing solely on format conversion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool should be used when converting file formats, but does not provide explicit guidance on when to use this tool versus alternatives among the many file_converter siblings (e.g., merge, split, encrypt). No exclusions or when-not-to-use conditions are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It only states 'create images' without explaining output format, error handling, rate limits, or any side effects. This is insufficient for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 12 words, front-loaded with the action, and contains no redundant 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 4 required parameters with enums and no output schema, the description is too brief. It lacks information about the return value (e.g., image URL) and any prerequisites or post-conditions.
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 baseline is 3. The description adds minimal value, only echoing that options exist for style and aspect ratio. It does not correct the misleading schema description for 'model' (which says 'text generation').
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 verb 'create' and the resource 'images using AI models', with specific options for style and aspect ratio. It effectively differentiates from sibling tools focused on research or text generation.
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 'social_post_creator_generate_social_image_action' or 'youtube_thumbnail_generate_packaging_action'. There is no mention of when-not-to-use or alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states the action without disclosing read-only nature, performance implications, rate limits, auth requirements, or side effects. For a tool with no annotations, this is insufficient 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 a single, well-structured sentence that is front-loaded with the action. Every word adds value, with no 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 7 parameters and no output schema, the description is too brief. It does not mention return format, ordering, pagination, error handling, or how the multiple filters interact. A more comprehensive description is needed for this complexity.
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 baseline is 3. The description adds minimal value beyond what the schema already provides for each parameter. It does not explain parameter interactions or provide additional context.
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 verb (Build) and resource (list of calendar events), and specifies the supported providers (Google Calendar, Outlook, or all). This distinguishes it from sibling tools like enrich_calendar_event or meeting_prep tools that focus on single events or meeting preparation.
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 vs alternatives. There is no mention of prerequisites, context, or when not to use it. Among siblings, many meeting-related tools exist, but no direct comparison or exclusion criteria are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It only states 'fetch', implying read-only, but does not confirm no side effects, auth requirements, or rate limits. Minimal behavioral insight beyond basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words. Front-loaded with the core action and benefit. Efficient and to the point.
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?
No output schema exists, but the description does not explain return values, result format, pagination, or error handling. Parameters like max_documents_count hint at limits but are not elaborated. The description leaves an agent uncertain about what to expect from the results.
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 coverage is 100%, with parameter descriptions explaining each field. The description adds little extra meaning beyond 'filtering criteria'. 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it fetches semantic search results from a builder's knowledge base. The verb 'fetch' and resource 'builder's knowledge base' are specific. However, it does not distinguish from sibling tools like 'query_agent_kb' or 'get_data_from_user_uploaded_files', leaving ambiguity about what 'builder' refers to.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions 'for data analysis', giving a hint about when to use, but no explicit guidance on when not to use or alternative tools. The context is implied, not explicit.
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 given, so the description must convey behavior. It only says 'Get Instagram profile info', implying a read operation but without explicit guarantees, rate limits, or authentication requirements. The description is too vague.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no unnecessary words. It adequately conveys the core purpose without fluff.
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?
The description fails to inform about what specific data is returned (e.g., bio, follower count). Without an output schema, the agent is left guessing, especially given the many sibling tools.
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 username parameter having a clear description ('without @'). Baseline is 3; the tool description adds no extra meaning beyond what the schema provides.
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 action ('Get') and the resource ('Instagram profile info'). It distinguishes from sibling tool 'get_instagram_followers', which covers a different aspect.
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 get_instagram_followers or other social media profile tools. The agent lacks context for appropriate 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 present, so the description carries full burden. It only states 'generate text based on input instructions', omitting any behavioral traits such as system prompt, context, personality, cost implications, or rate limits. This is insufficient for an LLM invocation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 15 words, front-loaded with the verb and resource. Every word contributes to the core purpose, and there is no redundant 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?
Despite only 2 parameters and no output schema, the description lacks details on return format, error behavior, or model-specific constraints. It does not mention what happens with the generated text (e.g., streaming, token limits). The completeness is insufficient for an agent to use this tool reliably.
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 coverage is 100%, so baseline is 3. The description adds minimal value: it reiterates that input instructions are used for generation but does not elaborate on the parameters beyond what the schema already provides (e.g., not explaining the 'auto' default or model selection strategy).
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 verb 'invoke' and the resource 'language model', with the action 'generate text based on input instructions'. It distinguishes itself from many sibling tools that are domain-specific (e.g., company research, file conversion) by indicating it is a generic LLM invocation tool.
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 other LLM-related tools like openclaw_chat_completion or invoke_agent. There is no mention of context, prerequisites, or situations where one alternative should be preferred over another.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description should disclose behavioral traits. Only states extraction of structured data, no mention of side effects, authentication needs, or whether it modifies state.
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?
Single sentence is appropriately concise. Front-loaded with verb and purpose. Could mention output variable usage more explicitly but overall good.
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?
No output schema, but description covers high-level purpose. Lacks details on return format, error scenarios, or dependencies on followup_context from other tools.
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 coverage is 100%, so baseline is 3. Description adds no additional parameter-specific meaning beyond what schema already provides.
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?
Description clearly states the verb 'extracts', resource 'meeting transcripts', and specific outputs (key moments, action items, signals, performance analysis). Differentiates from sibling meeting tools by focusing on transcript analysis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 like meeting_followup_generate_all_artifacts or meeting_followup_load_followup_context. Lacks context about prerequisites or sequence.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It fails to mention that this is likely a generative call consuming tokens, does not indicate side effects, or specify whether it is safe to call repeatedly.
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?
Single sentence with no fluff. Front-loads the core purpose immediately.
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?
Without an output schema, the description should explain the return value format or structure. It does not. Also lacks mention of required prior steps (Analyze Transcript, Load Followup Context) that are referenced in parameter defaults.
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 coverage is 100% with descriptions for all 5 parameters. Description adds generic terms like 'strengths, improvements' but does not provide semantic meaning beyond the schema's own descriptions.
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?
Clearly states the verb 'generates' and resource 'personalized coaching insights', listing included content (strengths, improvements, recommendations). It distinguishes from siblings like meeting_followup_analyze_transcript by focusing on coaching generation.
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 on when to use this tool versus alternatives like meeting_followup_generate_all_artifacts or meeting_followup_generate_followup_artifacts. Missing context on prerequisites or workflow order.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions determining first meeting, relationship stage, and recommendations, but does not disclose side effects, permissions needed, or whether it modifies data. The description suggests a read-only analysis, but this is not explicitly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that covers the main purpose. However, it could be more structured by breaking into use cases or behavior. Still, it is efficient and front-loaded with key information.
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 absence of an output schema, the description does not explain the return format (e.g., structure of recommendations). It provides a high-level overview but lacks details on what the analysis output contains. With 4 well-described parameters, it is partially complete but could be more thorough.
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 coverage is 100% and all parameters have descriptions. The tool description does not add any new meaning beyond what the schema already provides. Baseline score of 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool analyzes relationship history and patterns for meeting attendees, determines if it's a first meeting, relationship stage, and provides recommendations. It distinguishes itself from sibling meeting_prep tools by focusing specifically on relationships, though it does not explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage 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 required parameters (processed_event and meeting_classification) imply it should be used after event processing and classification, but there is no mention of when not to use it or what alternative tools exist for similar purposes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does not disclose whether the tool is read-only or has side effects, nor does it mention required permissions, potential LLM calls (e.g., via the use_llm_for_company_name parameter), or the nature of formatting.
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—two sentences that front-load the core purpose. Every word adds value, and there is no redundancy or filler.
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?
The tool is part of a multi-step meeting prep workflow, but the description does not explain prerequisites, expected outputs, or how it fits with other steps. Without output schema or behavioral details, an AI agent may lack sufficient context to use it 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?
The input schema already defines each parameter with descriptions, achieving 100% coverage. The description adds no further meaning beyond the schema, so a baseline score of 3 is appropriate.
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 function: it identifies the target company and primary contact, and formats contacts for research. The reference to combining Steps 21-22 from the original workflow distinguishes it from sibling tools that handle other parts of the meeting prep pipeline.
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 does not provide explicit guidance on when to use this tool versus its many meeting_prep siblings. It mentions combining specific workflow steps, but that assumes prior knowledge and does not give an AI agent clear selection criteria or 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, so the description bears full responsibility for behavioral disclosure. It mentions the processing actions but fails to disclose side effects, permissions required, idempotency, or that it likely stores results in a variable (given the output_variable_name parameter). The description lacks clarity on whether the tool modifies state or is safe to call multiple times.
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 a single sentence that efficiently conveys the tool's purpose. It is front-loaded with the main verb and resources, with no unnecessary words or repetition.
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 is part of a meeting prep pipeline with numerous siblings and no output schema, the description should explain its role in the pipeline and that it stores output to a variable. It omits that the output is likely saved via 'output_variable_name', and doesn't specify that it should be used after contact_research and before assembly. The description is insufficient for an agent to fully understand its integration.
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%, and each parameter has a basic description (e.g., 'The results from the Contact Research action.'). The tool description itself does not add extra meaning beyond the schema. Baseline of 3 is appropriate because schema already documents parameters, though descriptions are minimal.
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 function with specific verbs (processes, identify, build, calculate) and resources (contact research results, primary contact, profiles, quality scores). It distinguishes from sibling tools like 'contact_research' which likely gathers raw data, while this tool processes that data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 its many siblings, such as whether it should be called after contact_research or before assembling a meeting document. No explicit context or alternative recommendations are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'tiered models' and 'conditional prompt injection' but does not explain what these entail, nor does it disclose side effects, authentication needs, rate limits, or the mutation behavior of generating sections. The behavioral traits are vague.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, comprising two sentences that capture the core functionality. It is front-loaded with the key action ('Generates 7 meeting prep sections') and avoids unnecessary 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 complexity (14 parameters, no output schema, no annotations) and many sibling tools, the description lacks completeness. It does not explain the return value format, the integration with seller profile beyond mention, or how this tool fits into the larger pipeline. Critical context for an agent is missing.
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 every parameter has a description. The tool description adds some context by listing V3 vs V2 sections and mentioning model tiers, but this is already hinted in the parameter descriptions. The description does not significantly enrich understanding beyond the schema.
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 generates 7 meeting prep sections in parallel with seller profile integration. It uses specific verbs ('Generates') and distinguishes itself as 'V3', contrasting with V2 in the parameter schema. This sets it apart from sibling tools like meeting_prep_generate_meeting_sections.
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 mentions 'V3' but does not explain the criteria for choosing V3 over V2 or other meeting prep tools. There are no recommendations, exclusions, or context hints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavioral traits. It only states basic send/receive behavior, omitting side effects, streaming implications, or auth specifics beyond parameter description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with front-loaded purpose. No unnecessary words. Efficient and clear.
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?
Despite 10 parameters (3 required), no output schema, and no annotations, the description is too brief. Lacks guidance on session key, streaming, timeout, or output variable usage for a complex tool.
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 coverage is 100% via context signals, so baseline is 3. Description adds minimal value beyond schema (e.g., return text). No additional semantic enrichment.
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?
Description clearly states the verb 'Send', resource 'chat completion request to OpenClaw instance', and return 'assistant's response text'. This distinguishes it from sibling tools like 'rest_call' or 'invoke_llm'.
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 (e.g., 'invoke_llm' or 'rest_call'). Missing context for preferred scenarios or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility for behavioral disclosure. It fails to mention that the tool calls external APIs (Fiber.ai and Perplexity) and may incur costs or have rate limits. It also does not mention that the result is stored in a variable (output_variable_name) or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-formed sentence that efficiently conveys the core functionality. No unnecessary words or redundant information. It is front-loaded with the primary action (searches) and secondary action (scores/ranks).
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 (7 parameters, no output schema, no annotations), the description is too minimal. It does not explain the output format (list of ranked prospects stored in output_variable_name), nor does it mention that the tool can exclude prospects (exclusion_slugs). The lack of behavioral context (e.g., external API calls) makes it incomplete for an agent to reliably invoke without additional knowledge.
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 71%, which is moderate. The description adds no parameter-level details beyond what the schema already provides. For instance, 'seller_product' and 'seller_icp' are present in schema with descriptions, but the description does not explain their role in the scoring process. Score at baseline 3 as schema covers most but description does not enhance.
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: searching prospects via natural language (Fiber.ai) and scoring/ranking them against an ICP (Perplexity). It distinguishes from sibling prospect tools like 'prospect_research_find_prospects' by specifying the two-step process of search then scoring.
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 such as 'prospect_research_find_prospects' or 'prospect_research_research_prospect'. It does not mention any prerequisites, limitations, or exclusion criteria. The description assumes the agent will infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for disclosing behavioral traits. It states the output count (5-7) and mentions 'trending context,' implying external data fetching. However, it does not explain side effects (e.g., whether data is stored), permissions needed, or any cost/rate implications. This minimal disclosure leaves significant behavioral gaps.
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 a single, efficient sentence (12 words) that conveys the core action. It is front-loaded with the verb. However, it is so brief that it sacrifices necessary detail, bordering on under-specification. Still, it earns a 4 for avoiding fluff.
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?
The tool has 4 parameters (2 required, 2 with enums) and no output schema. The description only covers the topic and output count, omitting how parameters shape results, the structure of 'idea cards,' or how 'trending context' is determined. For an agent to use it effectively, more context is needed about expected output and parameter semantics.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 25% (only output_variable_name has a description). The tool description adds no meaning for the parameters: it does not explain how 'topic' should be formatted, what 'content_style' or 'content_goal' values mean, or how they influence the output. With low coverage, the description fails to compensate, leaving the agent to rely on parameter names and enums alone.
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 identifies the tool's function: 'Generates 5-7 YouTube video idea cards with trending context for a given topic.' It specifies the verb (generates), resource (YouTube video idea cards), and key feature (trending context). This distinguishes it from sibling render tools like 'youtube_idea_research_render_ideas_report'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool should be used when a user needs YouTube video ideas with trending context. However, it provides no explicit guidance on when not to use it, nor does it mention alternatives among sibling tools (e.g., other content generation tools). The context is clear but lacks exclusions or comparative direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must disclose behavior. It mentions caching per user/domain, which is helpful. However, it does not describe authentication needs, rate limits, data staleness, or the effect of parameters like use_live_search on behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences. The first sentence states the core purpose, and the second adds a key behavioral detail (caching). No redundant or unnecessary words.
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 lack of output schema, the description does not explain the format or structure of the answer. It also omits details on caching behavior implications (e.g., how to force refresh). While it covers basic usage, it leaves gaps for a complete 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, so the description adds no additional parameter meaning. It does not explain the difference between use_report_context and use_live_search, nor the role of output_variable_name beyond the schema. Baseline 3 applies.
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 ('Ask a custom research question') and the resource ('about a company domain'). It adds a distinguishing feature (caching per user/domain). However, it does not explicitly differentiate from the very similar sibling tool 'company_research_v2_answer_question', which could cause confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, no prerequisites, and no context on its appropriate use cases. It only states what it does, not when or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Says 'get' implying read-only but does not explicitly state no side effects, pagination behavior, or data source 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?
Single sentence, no redundant words, front-loaded with key action. Every word earns its place.
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?
Description tells purpose but lacks details on return structure, ordering, or limitations (e.g., only returns questions asked via the tool). Adequate for a simple retrieval tool but could be improved.
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 parameter descriptions. Tool description adds no additional semantic value beyond the schema, so baseline score applies.
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?
Description clearly states verb (get), resource (Q&A for a domain), and scope (user's history). Distinguishes from sibling tools like 'ask_domain_question' and 'answer_question' which perform actions rather than retrieval.
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 (e.g., ask a new question vs. view history). Agent must infer usage context from the description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions using specific search engines and generating conversation intelligence, but does not disclose limitations (e.g., contact not found), rate limits, or whether the tool modifies data. The description implies a read-only research operation but lacks explicit safety cues.
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?
Three sentences, front-loaded with primary purpose, then details on methods and outputs. Every sentence adds value without redundancy. Very efficient.
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 5 parameters and no output schema, the description covers the tool's purpose and outputs adequately. However, it lacks information on error handling, success criteria, and limitations (e.g., required email format for enrichment). For a research tool generating conversation intelligence, more details on output structure or reliability could improve completeness.
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 coverage is 100%, so baseline is 3. The description does not add significant meaning beyond schema for each parameter, but the overall context of researching and enriching contacts helps understand parameter usage. No additional parameter details are provided in the description.
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 researches contacts using Perplexity Sonar Pro and deep web search, with specific outputs like profile enrichment and conversation intelligence. It distinguishes from sibling tools like enrich_person (basic enrichment) and get_person_object (simple retrieval) through its multi-source triangulation and conversation prep focus.
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 like enrich_person, prospect_research, or meeting_prep_* tools. The description implies use for deep research and conversation prep, but doesn't specify exclusions or 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, so the description must carry the full burden. It mentions generating a plan but does not disclose if the tool writes to a database, requires authentication, has rate limits, or any side effects. For a generation tool, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded with the key output (content calendar) and qualifiers (SEO/AEO, schedule, rationale). No unnecessary words.
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?
With 7 parameters, no output schema, and no annotations, the description is too brief. It does not explain how the plan is returned (despite output_variable_name), what the plan includes beyond a calendar, or how parameters interact. The agent lacks sufficient context to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 43%, leaving many parameters without explanations. The description adds minimal value: it hints that 'optimization_focus' relates to SEO/AEO but does not clarify other parameters like planning_period, publishing_capacity, or brand_voice. It fails to compensate for the low coverage.
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 generates a content calendar with article ideas mapped to SEO/AEO opportunities, a publishing schedule, and strategic rationale. This distinguishes it from siblings like content_creator_generate_article_action (single article) and content_audit_generate_audit_action (audit) by specifying the output is a calendar and plan.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used for planning a content calendar, but it does not explicitly state when to choose it over alternatives such as content_audit or content_creator. No when-to-use or when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only states the basic action without disclosing behavioral traits such as file size limits, the fact that it stores the file URL in a variable (output_variable_name), or any side effects. Since no annotations are provided, the description carries full responsibility for transparency, and the minimal text fails to convey important behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. It is appropriately concise for a simple tool, though additional context (e.g., what happens after saving) could improve usefulness without sacrificing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (3 required params, no complex output), the description is largely complete: it identifies the action and result. However, it does not explain the role of 'output_variable_name' (storing the file URL) or mention that the file is downloadable, which is partially covered by the schema descriptions.
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 baseline is 3. The description does not add any meaning beyond what the input schema already provides; it merely restates the core purpose without elaborating on how parameters like 'output_variable_name' function in the tool's operation.
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 uses a specific verb ('Save') and resource ('text content as a downloadable file'), clearly indicating the tool creates a file from text. This distinguishes it from siblings like 'convert_file' (which converts existing files) and 'format_text' (which does not produce a download).
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 (e.g., 'convert_file' for converting existing files or 'get_variable_from_database' for retrieving stored data). The description implies usage for saving text as a file but does not provide exclusions or context for when other tools would be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description burdens full behavioral disclosure. It only states the core function without revealing side effects, such as file overwriting, permission needs, or result storage. This minimal disclosure is insufficient for safe autonomous use.
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 a single sentence that is direct and free of redundancy. Every word contributes to conveying the tool's purpose, making it highly concise.
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?
For a simple utility tool with full schema coverage and no output schema, the description adequately covers the core action. However, it lacks details on limitations (e.g., text size, font, positioning) and result handling, which would improve completeness given the complex sibling 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 coverage is 100%, so baseline 3 applies. The description adds no extra parameter context beyond the schema's already clear descriptions. It neither enhances nor detracts from the schema's clarity.
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 action: 'Add a text watermark' to 'a PDF or image file', specifying the resource and examples like CONFIDENTIAL, DRAFT. This distinguishes it from sibling tools such as file_converter_convert_action or file_converter_encrypt_action.
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. Among many sibling tools (e.g., file_converter_convert_action, file_converter_merge_action), there is no mention of conditions or exclusions, leaving the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does not disclose behavior like authentication needs, rate limits, or what exactly is returned (e.g., profile slug, URL, or full profile data). The schema mentions returning a 'profile slug,' but the tool description omits this, leaving the agent uncertain about the output.
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 a single sentence of 13 words, instantly conveying purpose. It is front-loaded with the action verb 'Find' and the resource, with no extraneous information.
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?
For a simple one-parameter tool, the description is minimally complete. However, it lacks details about the output format or error handling. Without an output schema, the agent cannot fully anticipate the tool's response, making the description somewhat 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 only parameter 'query' has a description in the schema that explains it finds the LinkedIn profile slug. The tool description adds no additional meaning beyond what the schema provides. With 100% schema coverage, a baseline of 3 is appropriate.
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 action: 'Find someone's LinkedIn profile from a query of their name or other details.' It specifies the verb 'find' and the resource 'LinkedIn profile,' and differentiates from sibling tools like 'get_linkedin_profile' (which likely works with an existing identifier) and 'search_linkedin_people' (which searches with specific criteria).
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 does not mention when not to use it, prerequisites, or mention sibling tools. An agent would need to infer usage 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?
No annotations provided; description only states 'Fetch recent posts' without disclosing behavior for invalid handles, rate limits, pagination, or response format. Agent lacks critical context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loads key information. No extraneous content.
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?
Tool is simple, but missing output schema and usage guidance relative to siblings reduces completeness. Agent doesn't know return structure or when to prefer this over search_bluesky_posts.
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 coverage is 100% and already describes both parameters. Description adds no additional meaning beyond schema, meeting baseline expectation for high coverage.
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?
Description clearly states verb 'Fetch', resource 'recent posts', and source 'specified Bluesky user handle'. Differentiates from siblings like post_to_bluesky (posting) and search_bluesky_posts (keyword search).
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 on when to use this tool versus alternatives such as search_bluesky_posts. Agent must infer, increasing risk of incorrect 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, so the description must carry full behavioral disclosure. It fails to mention that the query parameter defaults to '_most_recent_contact' for missing or short queries (though present in schema). It also omits details on return format, error handling, or read-only nature.
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, using one sentence that is front-loaded. However, it could benefit from slightly more structure to separate the two retrieval modes clearly.
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, the description should clarify what 'contact data' entails. It does not specify return fields, pagination, or error behavior, leaving the agent underinformed for a tool with a required parameter.
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 covers the parameter fully at 100% coverage. The tool description adds little beyond restating the purpose, so baseline 3 is appropriate.
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 it retrieves contact data from HubSpot and distinguishes between query-based retrieval and fetching the most recent contact. This makes the purpose specific and distinct from sibling tools like get_hubspot_company_object.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage contexts (query or most recent contact) but provides no explicit guidance on when to use this tool versus alternatives like get_person_object or contact_research. No when-not details are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It fails to mention error handling, rate limits, or what happens if the company URL is invalid. The description only states a simple retrieval, which is insufficient for a tool with no other metadata.
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 a single, front-loaded sentence with no extraneous words. It efficiently communicates the tool's purpose.
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?
The tool has only one parameter and no output schema. The description lists three sample output fields but is vague about others. For a simple retrieval tool, it is adequate but could be more complete by listing key fields or mentioning edge cases.
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 explains the parameter. The tool description does not add additional meaning for the parameter beyond referencing output fields, which is marginal. Baseline 3 is appropriate.
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 verb 'Retrieve' and the resource 'LinkedIn company page', and lists specific fields (size, industry, specialties). This differentiates it from sibling tools like get_linkedin_company_posts and get_linkedin_profile.
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, no prerequisites, and no context about required authentication or URL format. It only describes what the tool does, not when to choose it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral disclosure. It only states the tool 'retrieves' information but gives no details on error handling, authentication, rate limits, or what 'detailed information' includes.
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 a single concise sentence that is front-loaded and contains no superfluous words.
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 simplicity (one parameter, no output schema, no annotations), the description is minimal. It fails to specify what details are returned or how it differs from similar LinkedIn profile tools, leaving room for ambiguity.
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 coverage is 100% and the single parameter is well-described in the schema. The description adds no additional meaning beyond the schema, so baseline score of 3 is appropriate.
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 verb 'Retrieve' and the resource 'detailed information about a specific LinkedIn job posting', distinguishing it from sibling tool 'search_linkedin_jobs' which searches for job listings.
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 'search_linkedin_jobs', nor any prerequisites or context for invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only states 'Retrieve' (read operation), but omits details like authentication requirements, rate limits, input validation, or return format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence (10 words) that front-loads the essential information. No extraneous text.
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 simplicity (one parameter, no output schema, no annotations), the description provides minimal but adequate context. It does not explain return values or error conditions, but for a basic retrieval tool it suffices.
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 covers the parameter fully (100% coverage). The description adds no extra meaning beyond what the schema already provides for 'post_urls'. Baseline score of 3 is appropriate.
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 action (Retrieve), the resource (LinkedIn posts or articles), and the method (by direct URLs). It effectively distinguishes from sibling tools like search_linkedin_posts_by_keyword and get_linkedin_company_posts.
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 does not mention prerequisites, exclusions, or scenarios where other tools would be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility. It conveys the basic action (capture and split) but omits details on the interactive nature (presumably involves displaying a textarea to the user), output format, or potential side effects. The description is adequate but shallow.
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 a single sentence that efficiently captures the core functionality. No superfluous information is present.
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?
For a tool with 4 parameters and no output schema, the description is minimal. It does not explain what the tool returns or how parameters interact, though the schema fills some gaps. The description is adequate for a simple input capture but lacks completeness for an agent to fully understand the tool's behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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. The description adds no extra meaning or context for the parameters beyond what the schema provides.
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 captures a list from a textarea and splits it by delimiter or newline. It distinguishes its purpose from siblings by focusing on textarea input processing, though it does not explicitly differentiate from potentially similar tools like 'get_data_from_user_uploaded_files'.
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. Among many sibling tools, there is no mention of context or exclusions, leaving the agent without clear decision criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility for disclosing behavioral traits. It mentions 'retrieve' (implying read-only) but fails to specify any other characteristics like authentication requirements, rate limits, or the exact nature of the returned data (e.g., subscriber count, channel metadata).
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 a single, front-loaded sentence that efficiently conveys the tool's purpose without extraneous words. Every element (verb, resource, scope) earns its place.
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?
For a simple tool with one parameter and no output schema, the description gives a reasonable idea of the return content ('videos and statistics'), but lacks specific details about the output fields (e.g., channel name, subscriber count) or behavioral context. It meets a minimum viable standard but is not comprehensive.
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% for the single parameter 'url', which is already described as 'URL of the YouTube channel.' The tool description does not add any additional meaning or constraints beyond what the schema provides, so the baseline score of 3 applies.
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 uses a specific verb 'Retrieve' and resource 'a YouTube channel', and clearly states the scope includes 'its videos and statistics', effectively distinguishing it from sibling tools like 'get_youtube_transcript' (transcript retrieval) and 'run_youtube_search' (search).
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 such as 'run_youtube_search' for finding channels or 'get_youtube_transcript' for video transcripts. The agent must infer context solely from the name and sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description does not disclose behavioral traits such as whether transcripts require captions, language support, error handling, or rate limits. The description carries the full burden but provides minimal information beyond basic purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single concise sentence with no redundant content. Efficiently communicates the tool's purpose without unnecessary words.
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?
For a simple tool with one parameter and no output schema, the description is minimally adequate. However, it could be improved by noting return format, prerequisite conditions (e.g., video must have captions), or typical use cases. Given the lack of annotations, some completeness is missing.
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 covers the single parameter 'url' with a description, achieving 100% coverage. The description adds no new semantic information about the parameter beyond what the schema already provides, meeting the baseline expectation.
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 verb 'Fetch' and the resource 'transcript of a specified YouTube video'. It distinguishes from sibling tools like run_youtube_search (search videos) or get_youtube_channel (channel info). However, it lacks explicit mention that the transcript is text, which is implicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for obtaining video transcripts but does not provide guidance on when to use this tool versus alternatives (e.g., run_youtube_search for finding videos). No when-not-to-use conditions or context for selection are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description should disclose behavioral traits. It does not mention whether the operation is read-only, what happens if the meeting ID is not found, or any side effects beyond storing output. The description is minimal and lacks 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 a single sentence of 15 words, front-loading the action. Every word is necessary and it avoids fluff or repetition. It is appropriately sized for the tool's simplicity.
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 simplicity, the description is minimally complete: it states the purpose and relies on the schema for parameters. However, it lacks details about the output format (e.g., what details are stored in the variable) and error handling. The absence of an output schema increases the need for description, which is not met.
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 describes all parameters clearly. The description adds only the phrase 'based on the meeting ID', which is redundant with the parameter description. It does not provide additional meaning beyond the schema.
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 'Extracts the selected meeting from a list of past calendar events based on the meeting ID' uses a specific verb ('Extracts') and resource ('selected meeting from a list of past calendar events'), clearly distinguishing it from sibling tools like meeting_followup_analyze_transcript or meeting_prep_extract_selected_meeting.
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 vs alternatives such as meeting_prep_extract_selected_meeting, nor does it mention prerequisites like first calling get_calendar_events_list. Usage context is implied but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It describes a non-destructive assembly operation, but lacks details on permissions, idempotency, error conditions, or what happens to the input data. Only mentions output readiness for rendering.
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 a single concise sentence (13 words), front-loading the core action and output. No redundancy, but could benefit from additional context without becoming verbose.
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 8 parameters, no output schema, and no annotations, the description is insufficient. It does not explain the structure of the assembled document, how sections are combined, or what 'ready for HTML rendering' entails. Users lack guidance on the output format.
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 for all 8 parameters, each with clear default references. The description adds no extra meaning beyond what the schema already provides, so baseline 3 is appropriate.
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 action ('Combines all generated sections') and its output ('unified meeting prep document structure ready for HTML rendering'). It implicitly differentiates from sibling tools like generate_meeting_sections (which produces the sections) and render_meeting_prep_html (which renders HTML).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool should be used after sections are generated, but does not explicitly state when to use it versus alternatives (e.g., directly rendering without assembly) or provide exclusions. No guidance on prerequisites or order of operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavior. It reveals that the generation is parallel, uses tiered models (fast for simple sections, quality for complex), and outputs structured JSON. However, it does not describe the output structure, side effects, or required permissions, leaving some behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loading the main purpose and method. Every sentence provides useful information without redundancy. It is efficient and well-structured.
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 complexity (11 parameters, no output schema, no annotations), the description covers the core behavior and model tiering but omits the specific sections generated and the output JSON structure. The agent may need additional context to fully understand inputs and expected results.
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 baseline is 3. The description adds minimal parameter-specific value beyond the schema, as it only mentions 'all 5 meeting prep sections' and 'tiered models' without detailing individual parameters. The schema descriptions are already clear, so the description does not significantly enhance understanding.
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 it generates all 5 meeting prep sections using parallel LLM calls with structured JSON output. The verb 'generates' and resource 'meeting prep sections' are specific. However, it does not explicitly differentiate from the sibling tool 'meeting_prep_v3_generate_meeting_sections', which may have similar functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'meeting_prep_v3_generate_meeting_sections' or other meeting prep tools. It mentions 'tiered models for speed/quality balance' which implies a context for use, but lacks clear when-to-use or when-not-to-use instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose behavioral traits such as authentication mechanics, rate limits, or potential side effects beyond stating 'using your account credentials'.
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?
Single concise sentence with no extraneous information. Straightforward and efficient.
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?
While basic, the tool is simple; however, lacking output schema and any description of return values or process (e.g., handling errors) leaves it incomplete for a 4-parameter required tool.
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 coverage is 100% with good parameter descriptions in the schema itself. The tool description adds no additional parameter meaning beyond what schema already provides, meeting baseline expectations.
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 action ('Create a new post') and the resource ('Bluesky') with authentication context, distinguishing it from sibling tools like 'get_bluesky_posts' and 'search_bluesky_posts'.
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 on when to use this tool versus alternatives, no prerequisites or contexts provided. The description assumes the agent knows to use it for posting but lacks decision-making support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It mentions the output structure (3-7 post ideas, mapping to pillars, format, hooks, timing) but does not disclose any side effects, API calls, or limitations. For a content generation tool, this is minimally adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the main purpose and key output details. No redundant 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 7 parameters, no output schema, and no annotations, the description is too minimal. It does not explain the expected input format for performance_context, the output structure in detail, or how this tool relates to its sibling tools like social_planner_render_plan_report.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 57% (4 of 7 parameters have descriptions). The description adds context about LinkedIn-specific outputs but does not explain parameters like planning_period, num_posts, brand_voice, or performance_context beyond the schema. It does not compensate for the missing parameter descriptions.
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 generates a weekly LinkedIn posting plan with 3-7 post ideas, each mapped to a content pillar with format recommendations, hooks, and timing. This distinguishes it from sibling tools like content_planner_generate_content_plan_action, which is more general.
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 on when to use this tool vs alternatives (e.g., social_post_creator_generate_post_action for individual posts, or content_planner_generate_content_plan_action for general content planning). The description does not provide any context on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It states the tool outputs 'professional, mobile-friendly HTML' and includes links and sections, which gives some insight into the output. However, it does not disclose behavior regarding parameter conflicts, performance, error handling, or how the HTML is returned (e.g., stored in variable). Basic transparency is present but lacks detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences: the first states the core purpose, the second adds key features. It is front-loaded and avoids fluff. However, it could be slightly more informative without becoming verbose, hence a 4 rather than 5.
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?
For a render tool with 3 parameters, no output schema, and no nested objects, the description provides basic purpose and features. However, it lacks guidance on parameter interaction (e.g., what happens if both `report_data` and `report_id` are provided) and does not explicitly state that the output is the HTML string stored in the variable. Slightly incomplete for full contextual 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 baseline is 3. The description does not add meaning beyond the schema; it only mentions features of the report output, not parameter usage. The parameter descriptions in the schema already explain purpose, so the description provides no additional semantic value.
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 renders a complete company research report as HTML, uses a specific verb ('Render') and resource ('company research report'), and adds detail about including links to article sources and all research sections. Among sibling tools, it is distinct from other render tools by its focus on company research and mention of sources and sections.
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 `company_research_v2_get_report` or other render tools. It does not specify prerequisites (e.g., having run full research first) or when not to use it. The parameter description for `report_data` hints at a prerequisite, but the tool-level description lacks such context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It fails to explain whether the research is synchronous/asynchronous, cache behavior (despite a 'force_refresh' parameter), error conditions, or side effects (e.g., overwriting previous reports).
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 at 13 words across two sentences, immediately stating the action and key output. Every word earns its place with no fluff or 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?
Despite its conciseness, the description lacks completeness given the tool's role in a multi-step research workflow. It does not explain the research process, how to use the report_id, or confirm the polling pattern implied by 'for polling status,' leaving gaps for an AI agent unfamiliar with the sibling tools.
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?
All parameters are fully described in the input schema (100% coverage), so the description adds no additional meaning beyond the schema. The baseline of 3 applies as the description does not enhance understanding of the parameters.
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 action: 'Start researching a company by domain' and specifies the key return value 'Returns report_id for polling status,' which distinguishes it from related tools like 'get_report' or 'get_status' that handle completed results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (to initiate research) and hints at a follow-up polling pattern via 'report_id for polling status,' but it does not explicitly state when not to use this tool or mention alternatives among the many similar research 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?
No annotations are provided, so the description must bear the burden. It correctly indicates the tool performs a crawl (implying external network access) and generates a structured audit. However, it does not disclose potential side effects (e.g., rate limits, site impact), required authentication, or time cost. The description is moderately transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence front-loaded with the verb 'crawls'. It lists key outputs without redundancy. Every element adds value, and no unnecessary words exist.
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?
With no output schema, the description outlines expected deliverables (scores, action plan, gap analysis, etc.), giving the agent a good idea of the result. However, it lacks details on parameter usage, process duration, or return format, leaving gaps in completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50% (2 of 4 parameters have descriptions in schema). The tool description does not describe individual parameters (e.g., audit_scope, optimization_focus) beyond listing output components. It adds no meaning beyond the schema, so the score is below baseline 3.
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 action ('Crawls a website') and specifies the outputs ('structured content audit with SEO/AEO scores, prioritized action plan, content gap analysis, keyword cannibalization detection, page-level inventory'). This distinguishes it from sibling tools like content_audit_render_audit_report, which handles rendering rather than generation.
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 does not explicitly state when to use this tool versus alternatives (e.g., content_audit_render_audit_report for rendering or other content tools). It lacks 'when-to-use' or 'when-not-to-use' guidance, leaving the agent to infer usage from the purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must fully disclose behavior. It only states basic functionality without revealing important traits like output format, pagination, rate limits, or authentication needs.
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 a single, front-loaded sentence with no unnecessary words, efficiently conveying the tool's 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 no output schema and no annotations, the description lacks details about return values, source (Google News), language, or limitations, making it incomplete for 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 full description coverage (100%), so baseline is 3. The description adds no extra meaning beyond what the schema provides, merely mentioning queries and date ranges.
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 uses the specific verb 'Fetch news articles' and identifies resources (queries, date ranges) and purpose (monitoring topics/trends), clearly distinguishing it from general search tools like get_search_results.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for news monitoring but does not provide explicit guidance on when to use this tool versus alternatives such as get_search_results or search, nor does it mention when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully convey behavioral traits. It does not mention any side effects, authorization needs, rate limits, or return format beyond the basic functionality. The default behavior is partially explained via the schema but not in the description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the core purpose without unnecessary words. It is well front-loaded and earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with one parameter and no output schema, the description provides adequate context: it retrieves company data and outlines the two usage modes. However, it could be slightly improved by noting the typical return fields or expected behavior.
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 provides 100% coverage for the single 'query' parameter, describing its default and search purpose. The description adds no further parameter semantics beyond what the schema already gives, meeting the baseline for high schema coverage.
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 retrieves company data from HubSpot, specifying two modes: by query or most recent company. This distinguishes it from other HubSpot tools like get_hubspot_contact_object or get_hubspot_object.
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 such as get_hubspot_object or other company-related tools. The description does not mention when-not-to-use or contrast with siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description only indicates read operation (text extraction) and crawl capability, but misses details like limitations, authentication needs, or behavior on dynamic content.
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?
Single sentence, front-loaded, no wasted words. Efficiently conveys core functionality.
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?
Lacks description of return value format (plain text? structured data?). With no output schema, missing info on what the agent receives after invocation.
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 covers 100% of parameters with clear descriptions; tool description adds no extra semantics beyond schema.
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?
Clearly states 'extract text' from web pages, with two modes (single page or crawl). Distinguishes from sibling 'grab_web_screenshot' which captures images.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies use cases via mode parameter but does not explicitly compare to alternative tools or provide when/when-not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It mentions real-time web research but does not disclose that the result is stored via output_variable_name, nor any side effects or required permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with four sentences, front-loads the purpose, and includes necessary details without redundancy. Every sentence adds value.
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 7 parameters and no output schema or annotations, the description lacks details on output delivery, return format, and prerequisites. It is not fully adequate for correct invocation.
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 57% (low). The description adds context by listing sections and mentioning personalized implications tied to seller_product/seller_icp, but does not cover seller_website or seller_competitors.
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 it generates a structured 8-section market landscape brief using specific tools and lists the sections. It distinguishes from sibling tools like competitive brief or company research by focusing on 'market landscape'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for broad market research but does not explicitly state when to use or not use this tool versus alternatives. No exclusions or alternative references are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It only mentions parallel generation and lists output types, but omits details on side effects, rate limits, error handling, or dependencies on other tool outputs. Critical for a complex follow-up tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with verb and core action. Every word is relevant. No redundancy or filler.
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?
Tool has 9 parameters, 4 required, and no output schema. Description only gives high-level output list, but fails to explain workflow, input dependencies (e.g., transcript_analysis likely from another tool), or structure of returned artifacts. Incomplete for effective invocation.
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 coverage is 100%, so baseline is 3. The description does not add meaning beyond parameter descriptions in the schema. It briefly mentions outputs but not how parameters influence behavior.
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 primary action (generates) and lists specific deliverables (email draft, CRM notes, task list, team update) performed in parallel. It distinguishes from sibling tools like meeting_followup_analyze_transcript that focus on individual steps.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when or when-not guidance is provided. The description implies this is a final aggregation step, but does not mention prerequisites like having transcript analysis or coaching insights, nor does it compare to alternatives like generate_coaching or analyze_transcript.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose all behavioral traits. It states processing actions but does not mention side effects, permissions, or whether the tool is read-only or destructive. This is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the core action and lists subsequent steps concisely. No extraneous 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?
The tool has 4 parameters, no output schema, and no behavioral annotations. The description fails to explain the output format or structure of the processed event data. Given its role in a pipeline, the agent needs to know what the tool returns, which is missing.
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 baseline is 3. The description adds context about what is extracted (attendee classification, duration, etc.), but this is already implied by the tool name and purpose. It does not significantly enhance parameter meaning beyond schema descriptions.
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 processes raw calendar event data and lists specific actions: classifies attendees, extracts duration, conference links, and organizer info. It distinguishes itself from sibling tools by focusing on data processing rather than analysis or rendering.
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 does not provide any guidance on when to use this tool compared to alternatives like meeting_prep_analyze_meeting_relationships or meeting_prep_classify_meeting. It lacks context on prerequisites or post-conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It only states it runs a pipeline but does not reveal side effects, data mutations, error behavior, or performance characteristics.
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 two sentences with clear action and usage guidance, no wasted words. It is appropriately sized and front-loaded.
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 complex pipeline with 10 parameters and no output schema or annotations, the description is too minimal. It omits details on output, pipeline stages, and how parameters affect behavior.
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% parameter description coverage, so the baseline is 3. The description adds no extra meaning beyond the schema for the parameters.
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 it runs the complete optimized meeting prep pipeline (Phases 2-7) in a single action, using specific verb-resource combination. It distinguishes from sibling tools that are individual phases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says it is 'great for testing or simple deployments,' implying when to use it, but does not explicitly state when not to use or mention alternatives like individual phase tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states the action (rendering) without clarifying safety (e.g., read-only, no side effects) or requirements like authentication. The description adds minimal transparency beyond the action name.
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 a single sentence that is concise and front-loaded with the version and action. Every word is informative with no wasted 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?
For a simple rendering tool with two parameters and no output schema, the description omits key details: it does not explain that the output is stored in output_variable_name, nor does it describe the output format or any constraints on meeting_sections. This leaves gaps for the 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 coverage is 100% with both parameters described. The description does not add additional meaning beyond the schema; it only provides context about V3 cards which indirectly relates to the meeting_sections parameter. Baseline 3 is appropriate.
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 specifies the tool's action ('Renders meeting prep HTML'), the specific V3 cards (Situation, Segues, Questions, Next Step), and mentions V2 backwards compatibility, distinguishing it from sibling tools like meeting_prep_render_meeting_prep_html.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies that the tool handles both V2 and V3 meeting documents but does not explicitly state when to use this version versus the V2 sibling. There is no guidance on prerequisites or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It explains it validates and filters, but doesn't mention side effects, state changes, or what happens with invalid data. Adequate but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, ~20 words, front-loaded with action and key filtering rules. No redundant 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?
No output schema, and description doesn't explain output format or how it fits into a workflow. Missing details about what the validated output contains, limiting completeness for an 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 detailed parameter descriptions. The tool description adds a high-level overview but no new parameter-specific info. Baseline score of 3 is appropriate.
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 it validates calendar event trigger data and applies specific filtering rules (exclusion keywords, domains, external-only, time window). This differentiates it from siblings like meeting_prep_process_calendar_event.
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 on when to use this tool vs alternatives, prerequisites, or conditions. The description only states functionality without context for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only states that the tool invokes an API and returns results, omitting details about authentication requirements, error handling, latency, or side effects. The description does not contradict annotations since none exist.
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 a single, front-loaded sentence that efficiently communicates the tool's core function. It wastes no words, though it could benefit from slightly more structure (e.g., a second sentence on usage context).
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?
Despite having 11 parameters and no output schema, the description is minimal. The schema covers parameter details well, and the output_variable_name parameter explains how to access results. However, the description itself provides no guidance on constructing the invocation or interpreting results, which is a gap for a complex tool.
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 baseline is 3. The description adds no additional meaning beyond the schema, simply summarizing the tool's purpose. Each parameter has a detailed description in the schema, so no further elaboration is needed.
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 action ('Invoke a single tool'), the resource ('on an OpenClaw instance'), and the return ('Returns the tool's result'). It effectively distinguishes itself from sibling tools, which are specialized actions for specific services or domains.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives. While the context of sibling tools (specific actions) implies this is for generic tool invocation, no guidance on when not to use it or when other tools are preferable is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries burden. It describes what the tool generates (touchpoints, content) but does not disclose behavioral traits like output format constraints, rate limits, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence with a semicolon, concise and front-loaded with key info. No fluff, but could benefit from listing parameters briefly.
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?
With 13 parameters and no output schema, the description is insufficient. It does not explain required parameters or provide enough context for an AI agent to correctly invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is only 8% (only sequence_length has description). The description adds minimal meaning to the 13 parameters, failing to explain key inputs like company_website, outreach_goal, or seller_product.
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 it generates a multi-channel outreach sequence with 3-8 touchpoints across email and LinkedIn, and lists specific output elements. This distinguishes it from siblings like outreach_drafter_draft_outreach and outreach_strategist_generate_outreach_strategy.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
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 implies it's for generating a full sequence, but does not provide exclusion criteria or compare with siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It states 'persistent memory' but fails to cover important traits like overwrite behavior, size limits, or access scope. Critical details for an agent to use this tool safely are missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently conveys the core purpose. Every word earns its place with no superfluous content.
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 4 parameters, no output schema, and no annotations, the description should provide more context about return behavior (e.g., saving result in output variable), limitations, and how it relates to sibling tools. It lacks completeness for a write 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% (all parameters have descriptions). The description adds minimal value beyond the schema, simply restating the general purpose. Baseline 3 is appropriate.
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 verb 'Save' and the resource 'agent's persistent memory', making the purpose unambiguous. It distinguishes this write tool from sibling read tools like 'query_agent_kb' and 'list_agent_memories'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for storing information for future recall, but lacks explicit guidance on when to use this versus alternatives like 'store_variable_to_database'. No when-not-to-use or prerequisite information is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It does not mention whether the tool is read-only, requires authentication, or has rate limits. Only states the search action, leaving safety and behavior unclear.
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 a single sentence of 12 words, front-loaded with verb and resource. No redundant information, every word earns its place.
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?
The tool has 7 parameters with enums but no output schema. The description does not explain return format, pagination, error handling, or result limits. For a search tool, this is insufficiently complete.
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. The description adds no extra meaning beyond listing keyword, location, and filters. Baseline 3 is appropriate.
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 verb 'Search', the resource 'job postings on LinkedIn', and the scope 'by keyword, location, and filters'. This distinguishes it from siblings like search_linkedin_people or get_linkedin_job_posting.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for searching jobs but does not provide when-to-use guidance, exclusions, or alternatives. It is adequate for a simple search tool but lacks explicit context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description partially discloses behavior (creates post, optional image) but does not clarify whether it actually posts to LinkedIn or just generates content, nor does it mention permissions, rate limits, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One concise sentence that lists key components with no wasted words. It is front-loaded and efficient.
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?
Despite having 13 parameters and no output schema, the description is too brief. It does not explain return values, whether the post is published, image generation details, or prerequisites like brand assets.
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 coverage is 77% (high), so the description's summary of components adds some value but does not explain parameter details beyond the schema descriptions.
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 it creates a LinkedIn post with specific elements (hook, body, CTA, hashtags, optional AI-generated image) and distinguishes it from related sibling tools like social_planner and social_performance_analyzer.
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 such as social_post_creator_generate_social_image_action or content_creator_generate_article_action. The context of usage is implied but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It mentions generating research and lists included aspects, but does not disclose side effects, auth requirements, or output structure. Adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence that is front-loaded with the purpose and includes a list of outputs. No wasted words.
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 5 parameters, low schema coverage, no output schema, and no annotations, the description lacks guidance on parameter usage, output format, and when to use sibling tools. Insufficient for a complex research tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 20% (output_variable_name has a description). The description does not explain any parameters beyond the topic, leaving research_depth, website_url, and optimization_focus unexplained. Fails to compensate for low schema coverage.
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?
Description clearly states it generates comprehensive AEO & SEO research for a topic, listing inclusions like keyword opportunities and competitor landscape. It distinguishes from siblings like industry_research_generate_research_action by specifying AEO & SEO focus.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage for AEO & SEO research tasks, but no explicit when-to-use or when-not-to-use guidance. No alternatives are mentioned despite sibling tools with similar names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description must carry full burden. It lists what data is fetched (attendees, transcript, AI insights) but does not disclose permissions needed, rate limits, or how data is processed. Parameter booleans imply optional inclusion, but overall behavioral details are minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence that front-loads purpose. It is clear and efficient, though could be slightly more concise. No unnecessary words.
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?
With 9 parameters and no output schema, the description should explain return structure or how to use output_variable_name. It lacks guidance on what the enriched data looks like or how to utilize it, making it incomplete for a complex tool.
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 covers 100% of parameters with descriptions. The tool description repeats the parameter list but does not add new meaning beyond schema. Baseline 3 is appropriate; no significant improvement over schema.
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?
Description clearly states the tool enriches a calendar event with comprehensive details (attendees, notes, transcript, AI insights) and specifies supported providers (Google/Outlook). This distinguishes it from sibling tools like get_calendar_events_list which only lists events.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
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 vs alternatives (e.g., meeting_followup_analyze_transcript). Usage context is only implied by the mention of 'comprehensive details', but no when-not-to-use or alternative recommendations are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It mentions 'search' and 'extract' but does not disclose authentication needs, rate limits, or that the tool may require Gmail/Outlook access. The AI analysis aspect is only partially covered.
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 a single, concise sentence with no unnecessary words. It front-loads the main action.
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?
Despite having 7 parameters and no output schema, the description fails to mention that results are stored in a variable (via output_variable_name). It does not describe the output format or provide enough context for a complex tool.
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 baseline is 3. The main description adds no additional meaning beyond the schema; the parameter descriptions in the schema are already detailed.
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 action ('Search a contact's email history') and resource ('email history'), with additional objectives like extracting patterns and generating insights. It distinguishes itself from sibling tools, which are not email-specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for finding relevant emails from a contact based on meeting details, but lacks explicit guidance on when to use this over alternatives or when not to use it. No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It states the action (password-protect) but does not explain side effects (e.g., whether the original file is modified or a new copy created), auth requirements, or how the result is returned.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, front-loaded with the action verb, and contains no redundant or extraneous information.
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?
The description covers the basic purpose but lacks details about the output format, constraints (e.g., file size limits), and how the result is stored (only implied by output_variable_name). For a simple mutation tool, more behavioral context would be 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 coverage is 100%, and the description adds no additional meaning beyond what the schema already provides for each parameter. It does not compensate with extra context.
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 uses a specific verb 'password-protect' and identifies the resource as a PDF file, clearly distinguishing it from sibling file_converter_ actions like convert, watermark, or merge.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide explicit guidance on when to use this tool versus alternatives or when not to use it. Usage is implied by the tool's name and simple purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden for behavioral disclosure. It does not mention any side effects, rate limits, authentication requirements, or how results are structured (e.g., pagination, included fields). The description is too minimal to adequately inform an agent about the tool's behavior beyond its basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that effectively communicates the tool's purpose without unnecessary words. It is front-loaded and each phrase earns its place.
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 and the absence of an output schema, the description is adequate for basic understanding but lacks details on the return format, error handling, or limitations. An agent would benefit from knowing what the fetched results contain (e.g., titles, URLs, snippets) and any restrictions on query length or frequency.
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 already provides clear descriptions for all three parameters (100% coverage). The description adds little beyond the schema, listing the engine options and mentioning 'specified queries' without elaborating on format. According to the guidelines, with high schema coverage, the baseline is 3, and the description does not provide significant additional meaning.
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 action ('Fetch search results'), the resources ('Google, YouTube, or YouTube channels'), and the input ('specified queries'). It distinguishes itself from sibling tools like 'search' or 'run_youtube_search' by explicitly listing the supported search engines.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide explicit guidance on when to use this tool versus alternatives such as 'search', 'run_youtube_search', or 'get_google_news'. It lists the three search engines but does not explain the differences or provide scenarios for choosing one over the other.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It states it 'assembles' a document, but does not explain side effects (e.g., whether it writes to a database), authorization needs, rate limits, or what happens to inputs. The behavioral profile is largely implicit.
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: two sentences with no unnecessary words. The key action and scope are front-loaded ('V3: Assembles all sections...'). Every phrase earns its place.
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?
The tool has 12 parameters, no output schema, and no annotations. The description explains the overall purpose and lists handled sections, but it does not describe the output format, how the document is stored (output_variable_name suggests variable storage, but not clarified), or any processing details. It is adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed descriptions for each parameter. The tool description adds minimal extra meaning beyond grouping sections into V3 and V2 categories. Given high schema coverage, a baseline of 3 is appropriate; the description does not significantly enhance parameter understanding beyond the schema.
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 it assembles all sections (V3 and V2) into a unified document, specifying exactly which sections are handled (situation, segues, questions, next_step alongside legacy strategy/goals). This distinguishes it from the non-v3 sibling tool meeting_prep_assemble_meeting_document and clearly defines its scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this tool is used after generating meeting sections (likely via V3 and V2 generators), but it does not explicitly state prerequisites, when to use vs. alternatives, or when not to use it. Sibling tools like meeting_prep_assemble_meeting_document exist, but no guidance is provided on choosing between them.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavior. It mentions using Perplexity Sonar Pro and output sections, but lacks information on data sources, limitations, or side effects, leaving gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single well-structured sentence contains essential action and output summary with no redundant words, achieving high 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?
No output schema or annotations; description outlines output sections but lacks format details. For a tool with 9 parameters and structured output, it is adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline 3. The description adds context by listing output sections (e.g., ICP Fit), which clarifies the purpose of seller_icp and seller_product parameters, but doesn't enrich parameter semantics beyond schema.
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 that the tool researches a prospect and produces a structured intelligence brief with 8 specific sections, making its purpose distinct from sibling tools like prospect_research_find_prospects or contact_research.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
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 like contact_research or comprehensive_contact_intelligence; the context of use is implied but not contrasted.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits like authentication needs, rate limits, or side effects (e.g., that it sends an email). The description only explains what the email contains, not the action's implications.
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 two sentences, front-loaded with the core action, and each sentence adds specific value (action detail and content structure). No extraneous information.
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 annotations and no output schema, the description is minimal. It does not cover prerequisites, error conditions, or return behavior. For a simple email action, it is adequate but leaves gaps in behavioral 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 67%. The description adds no parameter information beyond what the schema provides. The schema already covers digest_id and email adequately, but output_variable_name lacks a description. The description does not compensate for this gap.
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 sends a trends research digest as a formatted email, specifies its content components (Top Trends, Industry Signals, etc.), and references the design system. This distinguishes it from sibling tools like trends_research_generate_trends_action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
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, such as industry_research_send_research_email_action. The usage is implied by the tool name and context, but no when-not or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It only describes the rendering action without disclosing side effects, permissions, or limitations. As a pure rendering operation, it is likely non-destructive, but this is not stated. The description lacks sufficient transparency for an agent to infer safety 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 two sentences, front-loaded with the primary purpose. Every word adds value, with no extraneous information. It is concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (two parameters, no output schema), the description adequately covers purpose and input. It lacks details on the output format or error handling, but for a rendering tool of moderate complexity, it is largely complete.
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 detailed parameter descriptions (e.g., brief_data instructs to use {{competitive_brief}}). The tool description adds little beyond reinforcing the input source, so it meets the baseline but does not enhance understanding.
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 renders a competitive brief as HTML, specifying the input from 'CBFull Run Full Competitive Brief'. It effectively communicates the core purpose but doesn't explicitly differentiate it from other render tools in the sibling list, though its specific input requirement provides implicit distinction.
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 explicitly states the prerequisite input ('output from [CBFull] Run Full Competitive Brief'), guiding the agent to use this tool after running that specific action. However, it does not provide when-not-to-use guidance or mention alternatives, which are not critical given the clear dependency.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It states 'renders' which implies a non-destructive output generation, but it doesn't clarify side effects, required inputs (like prior plan generation), or how the report is structured. Basic transparency but insufficient for full understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that efficiently conveys the core purpose without extraneous words. It is front-loaded with the verb and resource, making it easy to scan.
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 has 2 parameters (with 0% schema description) and no output schema or annotations, the description is minimal. It explains the basic purpose but lacks details on data format, prerequisites, expected output structure, and error behavior. An agent would need additional context to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the schema provides no parameter descriptions. The description does not explain the parameters 'report_data' or 'output_variable_name' beyond what the schema (name and type) already shows. It adds no semantic meaning, so it fails to compensate for the schema gap.
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 renders a content calendar as an HTML report with week-by-week content briefs. It uses specific verb 'renders' and resource 'content calendar HTML report', and the detail 'week-by-week' distinguishes it from sibling tools like content_planner_generate_content_plan_action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
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 vs. alternatives. The description implies it is for rendering after generation, but it doesn't state prerequisites or when not to use it. Sibling names provide some context, but the description itself lacks usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the transparency burden. It states the output is a validated render-spec and mentions model fidelity/cost trade-offs, providing moderate behavioral insight. However, it does not disclose safety, reversibility, or error handling behaviors.
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 a single efficient sentence that front-loads purpose and covers key points (generate, select model/theme, write prompt, get spec). Every clause is meaningful with no 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?
Despite no output schema, the description does not detail the render-spec structure or validation process. It omits how the output integrates with the runner. Given the tool's 5-parameter complexity and missing annotations, more context on output and workflow integration is needed.
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 coverage is 100%, so the baseline is 3. The description summarizes model and theme selection and mentions 'write the prompt', but does not add extra meaning beyond the schema's descriptions (e.g., instruction format or variable referencing). No new context is provided.
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 generates interactive UI as a workflow step, specifying concrete outputs like dashboards, forms, and multi-section reports. It distinguishes from siblings like 'generate_image' or 'shared_render_tabbed_report' by focusing on validated render-specs for the runner.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage as a workflow step but offers no explicit guidance on when to prefer this tool over alternatives (e.g., 'output_formatter' for formatting or 'invoke_agent' for general generation). No when-not-to-use or prerequisite conditions 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?
No annotations are provided, so the description carries full burden. It discloses the key behavioral trait of LLM inference, but lacks details on side effects, permissions, or data handling. Given the tool's safety profile, this is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no waste, front-loaded with the primary purpose. All information is relevant and efficiently presented.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and good parameter descriptions, the description adequately explains the tool's function and inference capability. It could mention the output variable usage, but is sufficient for the tool's complexity.
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 coverage is 100% with parameter descriptions already covering inference logic. The description adds minimal new meaning beyond what the schema provides, so baseline score of 3 is appropriate.
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 loads user context including role and goals, and mentions inference via LLM. However, it does not distinguish from sibling tools like meeting_prep_load_user_context or meeting_prep_v3_load_user_context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context on when to use (loading user context) and inference behavior, but does not specify when not to use or suggest alternatives from 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?
No annotations are provided, so the description carries the full burden. It lists classification outputs but does not disclose behavioral traits such as whether the tool is read-only, if it modifies any state, or any requirements. The description is functional but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the main actions. It is front-loaded with key verbs. Minor improvement could be a bulleted list for clarity, but it is effective as is.
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?
No output schema exists, so the description should hint at the return format. It mentions outputs (meeting type, topic signals, etc.) but does not describe structure or how these are returned. Among many sibling tools, this is adequate but not fully complete.
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 coverage is 100%, so the parameters are already documented. The description adds context about the outputs but does not enhance parameter semantics beyond what the schema provides.
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 verb (classifies, extracts, determines) and specific resources (meeting type, topic signals, buyer stage, urgency). It distinguishes from siblings like meeting_prep_process_calendar_event which processes raw events, and meeting_prep_analyze_meeting_relationships which analyzes relationships.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this tool is part of a meeting prep pipeline, but it does not explicitly state when to use it versus alternatives like meeting_prep_process_calendar_event or meeting_prep_extract_selected_meeting. No exclusions or alternative suggestions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so description must carry full burden. It only says 'poll' (implying non-destructive read) and mentions checking 'is_complete', but does not disclose behavior on invalid report_id, rate limits, or potential errors.
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?
Two sentences: first states purpose, second gives usage. No unnecessary words, well front-loaded.
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?
No output schema exists. Description hints at is_complete boolean in response, but does not mention other potential fields like progress percentage or error states. Adequate but not complete.
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 descriptions cover both parameters with 100% coverage. Description adds context about using in a loop and checking is_complete, but does not add significant meaning beyond schema.
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 'Poll for research report progress' clearly states the verb (poll) and resource (research report progress). It distinguishes from siblings like start_research (initiates) and get_report (retrieves final report).
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 explicitly says 'Use in a loop until is_complete is true', providing clear usage pattern. It implies polling context but does not mention alternatives or when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must communicate behavioral traits. It implies a read-only operation ('Get'), but does not disclose output format, data freshness, or any side effects. It is adequate but minimal for a read tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, 14 words, front-loaded with the core action. No filler or 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?
The tool has no output schema, so the description should clarify what 'detailed metadata' includes. It does not elaborate on return structure (e.g., 'name, description, parameters'). It is minimally complete for a simple getter but lacks specificity.
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%, and the parameter description already mentions ID or slug. The tool description adds no new semantic meaning beyond confirming that both ID and slug are accepted. Baseline 3 applies.
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 verb 'Get' and the resource 'detailed metadata, input fields, and output fields for a specific agent'. It specifies the identifier method ('by its ID or slug') and the scope ('specific agent'). This clearly distinguishes it from sibling tools like 'invoke_agent' or 'list_agent_memories'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage (when you need agent details), but does not mention when not to use it or alternatives (e.g., 'openclaw_get_details' for a different system). No explicit guidance on prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool 'Adds a searchable text layer' which implies transformation but not destruction. However, it does not disclose whether the original file is modified, output format, file size limits, or required accessibility of the URL.
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?
Two sentences, front-loaded with the core action. No unnecessary words. Efficient and clear.
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 lack of output schema and multiple sibling file converter tools, the description could be more complete. It does not explain the output (likely a PDF with text layer), file size limits, or how it differs from image_to_text. It covers the core but leaves 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 67% (2 of 3 parameters have descriptions). The description does not add any parameter information beyond what the schema provides. Since the schema already explains the parameters adequately, the description adds no extra value for parameter semantics.
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: 'Add a searchable text layer to scanned PDF files using OCR.' It uses a specific verb ('Add') and resource ('searchable text layer to scanned PDF files'). This distinguishes it from sibling tools like file_converter_image_to_text_action, which likely handle non-PDF images.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use or not use this tool versus alternatives. It implies usage for scanned PDFs, but does not mention alternatives like file_converter_image_to_text_action for non-PDF images or other conversion tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full burden. It states the tool reduces file size while maintaining quality, but does not specify whether compression is lossy or lossless, nor disclose any limitations or side effects. The core behavior is clear, but additional detail could improve transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with action, no redundant information. Every word serves a purpose. Highly efficient.
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?
The description explains what the tool does but does not address output format, error scenarios, or return value semantics. Given the absence of an output schema and annotations, more detail would be helpful for an agent to fully utilize the tool.
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 75% (3 of 4 parameters documented). The missing 'profile' parameter has enum but no description. The tool description adds no additional meaning to parameters beyond the schema. Baseline 3 is appropriate given coverage level.
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 verb (compress/optimize), the resource (PDF, PNG, JPG files), and the scope (without changing format). It effectively distinguishes the tool from siblings like file_converter_convert_action (which changes format) and file_converter_encrypt_action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for compression needs where format must be preserved, but it does not explicitly state when to use this versus alternatives like convert or merge. 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?
Without annotations, the description carries full burden. It mentions scraping, voiceover creation, API submission, and returning a video_id for polling. However, it omits authentication needs, rate limits, potential costs, and error scenarios.
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?
Three sentences, no redundancy, front-loads purpose. Every sentence adds value and fits within a concise structure.
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?
Covers key functionality and output, but lacks details on error handling, prerequisites, and full output structure. Given the complexity (10 params, no output schema, no annotations), it is adequate but not fully complete.
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 coverage is 70% with good descriptions. The tool description adds little beyond restating the two source_type modes and the output video_id. Baseline 3 applies as the schema does most of the work.
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?
Clearly states it generates a talking-photo avatar video via HeyGen, with two sourcing methods (blog URL or topic/script). Distinguishes from siblings like heygen_photo_avatar_create_avatar_action which creates avatars rather than videos.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage for generating avatar videos but does not explicitly compare with sibling tools like heygen_avatar_get_video_status (for polling) or other HeyGen tools. No when-not-to-use guidance provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses processing time estimates and content moderation but omits details on error handling, quota limits, or output format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with the primary action, no extraneous text. Efficiently lists key features 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?
Covers inputs and moderation but lacks output schema or detailed behavior (e.g., how custom_prompt interacts, what moderation failure entails). Adequate for basic use but incomplete for nuanced scenarios.
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 coverage is 56%. The description adds value by explaining time estimates for quality and hinting at output variable usage, but many parameters (e.g., style, background) rely solely on enums without further context.
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 verb 'generates' and the resource 'AI professional headshots' using a specific model. It lists key configurable options, making it easy to distinguish from the sibling tool 'instant_headshot_render_headshot_report'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for generating headshots but lacks explicit guidance on when to choose this tool over alternatives (e.g., the render report tool) or prerequisites like reference photo requirements.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry all behavioral context. It mentions AI-powered semantic search and citations, but does not explain that results are stored in a variable (as per output_variable_name parameter), nor any limitations or cost considerations. Adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that front-loads the purpose and core functionality. Every word contributes meaning, with no fluff or repetition.
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?
With 5 parameters, no output schema, and no annotations, the description is brief but covers the main purpose. However, it lacks details on how the output variable works (output_variable_name) and how metadata filtering is used. More context would improve completeness.
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%, meeting the baseline. The description adds general context (AI search, citations) but does not elaborate on any specific parameter beyond what the schema already provides. No added semantic value for parameters.
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 action (search/recall), the resource (agent's memories), and the method (AI-powered semantic search). It mentions output includes citations, which helps distinguish it from related tools like list_agent_memories or save_to_agent_kb.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used for recalling past context via semantic search, but it does not explicitly differentiate from siblings like list_agent_memories. No when-not or alternative usage is provided, leaving the decision partially to the agent's inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the processing chain and outputs but omits limitations, error handling, supported formats explicitly, or response characteristics.
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?
Two sentences efficiently convey purpose, process, and outputs. No extraneous text; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description explains return values (searchable PDF and .txt). However, it could mention how to retrieve results via output_variable_name, supported image formats, or file size constraints.
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 coverage is 67% (input_file_url and output_variable_name have descriptions; language has enum but no description). The tool description adds no extra parameter meaning beyond the schema, so baseline score is appropriate.
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 'Extract text from an image using OCR' and details the chain of operations (image → PDF → OCR → plain text) and outputs (searchable PDF and .txt), distinguishing it from sibling file_converter tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
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 like file_converter_ocr_action. The description implies usage for OCR on images but does not specify exclusions or provide when-not criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It discloses automatic conversion to PDF but lacks details on file size limits, supported formats, or output storage behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no extraneous words. Every part contributes to understanding the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the core function and auto-conversion. Given no output schema and 2 simple parameters, it is mostly complete, though it could mention output variable behavior.
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 coverage is 100%, so baseline 3. The description adds no additional meaning beyond the schema; it does not elaborate on URL format or output variable.
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 combines multiple files into a single PDF and automatically converts non-PDF files. This distinguishes it from sibling tools like split or convert.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for merging files into a PDF but does not explicitly state when to use or avoid this tool, nor does it compare to alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must bear this burden. It discloses the output format (array of URLs) but does not mention behaviors such as whether the original PDF is modified, storage duration of URLs, file size limits, or required access permissions. This leaves some uncertainty about the tool's side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at two sentences, with no redundant or filler content. Each sentence serves a purpose: stating the action and specifying the return value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two required parameters and no output schema, the description is mostly complete. It covers the core operation and output. Minor gaps remain: the nature of the returned URLs (temporary? accessible?) and any prerequisites are not mentioned, but the overall context is sufficient for an agent to understand the tool's role.
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 coverage is 100%, so parameters are already documented. The description adds no additional meaning beyond the schema; it does not explain the parameters further or provide usage context for input_file_url or output_variable_name.
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 specifies the action (Split a PDF into one file per page) and the output (array of individual page PDF URLs), distinguishing this tool from other file_converter actions like merge, convert, or optimize.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for splitting PDFs into separate pages but provides no explicit guidance on when to use this tool over alternatives like file_converter_merge_action or file_converter_ocr_action. No when-not-to-use or precondition details are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must cover behavioral traits. It mentions Jinja2 templates and no LLM need, but lacks details on side effects, prerequisites, or output format beyond HTML email.
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 a single, concise sentence that immediately conveys the purpose and key details, with no extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple renderer with two parameters and no output schema, the description covers the essential purpose and process. It could mention input format expectations, but the parameter description fills that gap.
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-defined. The description adds minimal extra meaning beyond the schema, meeting the baseline for high coverage.
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 verb 'renders' and the resource 'assembled meeting prep document', specifying it produces a 'beautiful HTML email using Jinja2 templates' and uniquely notes 'No LLM required', which distinguishes it from other tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage after assembly but provides no explicit when-to-use, when-not-to-use, or alternative tools like meeting_prep_v3_render_meeting_prep_html.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions that providing a LinkedIn URL enriches output with warm-up suggestions, which is useful. However, it does not disclose whether the tool is read-only, requires authentication, has rate limits, or modifies any data. The behavioral disclosure is partial.
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 two sentences, front-loaded with the primary action and output. Every word adds value, no repetition or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 11 parameters, no output schema, and many siblings, the description adequately explains the output components and positions the tool. It could be more complete by specifying the output structure (e.g., text, JSON), but it is sufficient for an agent to understand the tool's role.
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 high (91%), so the baseline is 3. The description adds marginal value by noting the LinkedIn URL enriches output, but otherwise does not elaborate on parameter meanings beyond what the schema provides.
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 that the tool analyzes a prospect's context and produces a structured Outreach Strategy Brief, listing specific components (messaging angle, channel priority, CTA approach, timing assessment, risk factors). It also positions itself as the 'entry point to the Sales Outreach Team workflow', distinguishing it from sibling tools like outreach_drafter_draft_outreach.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage as the first step in the outreach workflow, but does not explicitly state when to use it versus alternatives, nor does it provide exclusions or prerequisites. The guidance is clear but not comprehensive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry the burden. It discloses deterministic rendering and no LLM use, but does not cover error handling, input validation, or side effects like whether it modifies state. This is adequate but not exhaustive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence that is front-loaded with the main action and key attributes (email-compatible HTML, Jinja2, no LLM). Every word adds value; no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two parameters and no output schema, the description adequately covers the render function, output format, and efficiency. Could mention expected input format (JSON from Research Prospect) but is otherwise complete.
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 both parameters (prospect_research and output_variable_name). The description adds minimal extra meaning beyond what the schema provides, meeting the baseline.
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 uses a specific verb ('Renders') and resource ('Prospect Intelligence Brief as professional email-compatible HTML'), clearly distinguishing it from other render tools by specifying the output format and technology (Jinja2 templates).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides context ('No LLM required — fast deterministic rendering') but lacks explicit guidance on when to use this tool versus similar rendering tools among siblings, such as competitive_brief_render_brief_html or company_research_v2_render_html.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the 30-day caching behavior, which is useful. However, it does not mention whether the operation is read-only, any rate limits, or output format beyond listing fields. Some behavioral context is provided, but gaps remain.
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?
Two sentences front-load the key information: what data is returned, caching policy, and integration context. Every sentence adds value with no fluff. Excellent conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with only two simple parameters and no output schema, the description adequately covers purpose, output contents, caching, and downstream usage. It could mention whether the output is structured (e.g., JSON) but overall it's sufficient.
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 coverage is 100%, so the schema already documents both parameters. The description adds no new meaning beyond what the schema provides: it repeats 'company name or domain' for query and lacks detail for output_variable_name. Baseline of 3 is appropriate.
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 returns 'rich company intelligence' and lists specific data types (funding, investors, etc.). It uses a specific verb-resource combination ('search company intel') and distinguishes from sibling tools by focusing on a quick, cached snapshot rather than deep research.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
While the description mentions it 'feeds directly into Research Prospect,' it does not explicitly state when to use this tool versus alternatives like company_research_v2_start_research or other company research tools. No usage exclusions or context for when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It mentions using Perplexity Sonar Pro and GPT-5 Mini, and lists the six sections. However, it does not disclose potential side effects (e.g., API rate limits, cost implications) or behavior on invalid inputs (e.g., missing required fields). The transparency is adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the main action and lists all sections. It is reasonably concise, though slightly long due to enumerating all six sections. Every piece of information is useful, but the sentence could be broken for better readability.
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 7 parameters, no output schema, and no annotations, the description explains the digest structure (6 sections) and mentions the tools used. However, it does not specify the output format (e.g., JSON, text), typical response time, or any error handling, leaving some gaps for complex research tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 86%, so baseline is 3. The description adds value by explaining that optional parameters (seller_product, seller_icp, seller_website, seller_competitors) enable personalized sections (e.g., 'What This Means for You'), which goes beyond the schema's field descriptions.
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 generates a structured 6-section trends research digest for any industry, specifying the verb ('Generates') and resource ('trends research digest'). It lists all six sections (Top Trends, Industry Signals, etc.), which distinguishes it from sibling tools like industry_research_generate_research_action that may produce different outputs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for generating industry trend research but does not explicitly state when to use this tool versus alternatives like aeo_seo_research_generate_research_action or industry_research_generate_research_action. No exclusions or when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description indicates a read operation ('retrieve') but does not disclose behavioral traits like authentication requirements, rate limits, or pagination. For a simple retrieval tool, this is minimally adequate but leaves gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence clearly stating the tool's purpose with no unnecessary words. It is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema, no nested objects), the description fully clarifies what the tool returns and requires. No additional context is needed for an agent to use it 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% (the only parameter has a description). The tool description adds no extra meaning beyond restating the parameter's purpose; hence it meets the baseline of 3 without adding value.
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 uses a specific verb ('retrieve') and resource ('all owners (users) from a HubSpot portal'), clearly distinguishing it from sibling tools like get_hubspot_company_object which target different HubSpot objects.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing HubSpot owners, but it lacks explicit guidance on when to use this tool versus alternatives such as get_hubspot_contact_object. No when-not-to-use or prerequisite info is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Discloses no credit consumption but omits details like read-only nature, supported file types beyond examples, and error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two efficient sentences with front-loaded purpose and a critical behavioral note. No superfluous content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple 2-param tool with no output schema. Could mention output format (e.g., JSON object) but current description is sufficient.
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 coverage is 100% with both parameters described. Description adds no extra meaning beyond schema; baseline 3 appropriate.
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?
Clearly states 'Extract metadata from any file' with specific examples (EXIF, PDF properties, video resolution/duration). Distinct from sibling file converter tools like file_converter_convert_action by explicitly noting no conversion credits consumed.
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?
Implicit guidance via 'Does not consume conversion credits' suggests using when only metadata needed, saving credits. However, lacks explicit when-not-to-use or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It mentions polling behavior and return values, but lacks details on rate limits, error handling, or call frequency. Adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with approximately 20 words, front-loading the verb and resource. Every word adds value, no repetition, and it is efficiently structured for an AI agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a polling tool with no output schema, the description covers the essential return values (status, video_url, thumbnail_url). It does not detail error states or timeout behavior, but the sibling context (generation tool) provides enough completeness for typical 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 coverage is 100% with descriptions for both parameters. The description does not add new information about parameter usage beyond the schema's template values ({{heygen_result.video_id}}). Since schema already defines parameters, the description adds minimal semantic value.
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 polls for video generation progress, listing specific statuses and return fields (video_url, thumbnail_url). It distinguishes from the sibling tool heygen_avatar_generate_video, making purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage after generating a video to check progress, but does not explicitly state when not to use it or name alternatives. Context suggests it pairs with heygen_avatar_generate_video, but more explicit guidance would improve score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description well discloses it uses Jinja2 templates for deterministic rendering, and lists included report components. Adds context beyond schema about performance and content.
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?
One concise sentence that effectively conveys the tool's action and key attributes without unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, description adequately explains what the report contains. Could mention return format (string of HTML) but is sufficient for a rendering tool.
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 coverage is 100%, so baseline is 3. Description does not elaborate on parameters beyond what schema already provides.
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?
Description clearly states it renders an HTML sentiment report from LinkedIn post data, and lists specific components (sentiment badges, engagement stats, author cards). This distinguishes it from sibling render tools that specialize in other domains.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage from description (for LinkedIn post reports, no LLM needed), but no explicit guidance on when to use this vs other render tools or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description carries full burden. It discloses the composite nature, parallel execution, and performance improvement, but does not cover potential side effects, error handling, or output format beyond what parameter descriptions imply. Adds moderate behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences front-loaded with 'OPTIMIZED' and key benefits. Every word earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 9 parameters (3 required) and no output schema, description covers high-level purpose, sibling replacement, and performance. Lacks detail on output structure, but parameter descriptions in schema fill gaps. Overall sufficient for an AI agent to understand when and why to call.
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 baseline is 3. The description itself adds no extra meaning to parameters; the optimization and combination benefit are the only additions. The output_variable_name parameter description lists set variables but is not part of the tool description.
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?
Description clearly states the tool combines coaching (F5) and artifacts (F6) into a single optimized action with 5 parallel LLM calls, reducing time by ~50%. It directly distinguishes from sibling tools (the separate F5 and F6 actions) by naming them and specifying that this replaces them.
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?
Explicitly advises 'Use this instead of separate F5 and F6 actions,' providing clear context for when to use this tool over alternatives. Does not mention when to avoid using it, but the directive is strong enough for basic guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explains auto-conversion of recurring event IDs, the difference between 'list' and 'query' modes (LLM invocation), and output structure. No annotations present, so description carries full burden. It provides good behavioral context without contradictions.
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?
Two sentences that front-load the main purpose and key features. No redundant information. Efficient and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description explains return structure for both modes (memories array, llm_response). Covers behavior for 7 parameters and 5 required. Missing details on error handling or limits, but generally complete given complexity.
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 coverage is 100%, so baseline 3. Description adds value for event_id (wildcard auto-conversion) and mode (list vs query). Other parameters like kb_scope, sort_order, context_limit are adequately described in schema; description adds little extra.
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 queries meeting knowledge bases with metadata filtering, date sorting, and optional LLM Q&A. It distinguishes from siblings by focusing on querying stored memories, not generating prep docs or analyzing transcripts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving meeting memories but does not explicitly state when to use this tool versus other meeting prep tools (e.g., analyze_transcript, assemble_meeting_document). No when-not or alternatives are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It discloses caching duration and return fields, but does not mention authentication requirements, what happens on invalid/not-found emails, or any rate limits. Adequate but leaves gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with all critical info upfront: action, source, returns, caching. No filler words; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description adequately describes return fields and caching. However, it lacks error handling details or mention of data freshness beyond caching. For a simple lookup tool, this is mostly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds value by explaining cache behavior and the nature of returned data (career history, skills). This goes beyond the schema descriptions, which are minimal.
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 resolves an email to a LinkedIn profile via Fiber.ai, listing specific return data (name, title, etc.). This distinguishes it from siblings like 'search_linkedin_people' or 'get_linkedin_profile', which do not emphasize email resolution.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for email-based lookups and mentions caching (30 days), but lacks explicit guidance on when to prefer this tool over alternatives (e.g., 'search_linkedin_people', 'enrich_person'). No contraindications or context for when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description mentions Gemini AI and LinkedIn optimization but does not disclose behavioral details like return format (URL vs binary), rate limits, or whether it is destructive. With no annotations, the description carries the full burden and is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two efficient sentences. First sentence covers features, second covers usage context. No fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequately covers the action for a simple image generation tool given high schema coverage. However, lacks explicit mention of return format (but output_variable_name parameter implies URL). Could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 88%. Description adds value by explaining prompt/topic priority (prompt takes precedence) and that image_aspect_ratio 'takes up more feed space on mobile'. These additions justify a score above baseline 3.
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?
Clearly states it generates LinkedIn-optimized images using Gemini, lists 4 visual styles and 2 aspect ratios, and differentiates from generic image generation tools like 'generate_image'.
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?
Explicitly states it can be used as a standalone action or part of the Social Post Creator pipeline. Does not provide explicit when-not-to-use or alternatives, but the context implies it's for LinkedIn social images.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses key behaviors: sticky sidebar on desktop, horizontal tabs on mobile, scroll-to-section, active highlighting, JSON input structure. No annotations provided, so description carries burden. Missing error handling 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences, front-loaded purpose, details structured logically. Could be slightly tighter but no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers input structure and output variable storage. No output schema, so description explains how result is stored. Lacks limitations like section count or size.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage 100%, but description adds significant value for report_data parameter with example section structure and hint about using variables. Other parameters minimally enhanced.
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?
Description clearly states it renders a multi-section HTML report with sidebar/tabs, icons, badges. Specific verb 'renders' and resource 'multi-section HTML report' plus unique UI features distinguish it from sibling render tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this vs other render tools. Implied usage as a report renderer but lacks context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It indicates a read-only operation ('Fetch'), but does not disclose potential side effects, authentication requirements, or rate limits. The template variable reference adds some context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no waste. The first sentence states the action, and the second explains output usage. Information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lists key output fields (IP, auth token, status) and their usage. However, it omits details about the status value structure or possible values. Still, it is sufficient for an agent to correctly invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter. The description adds meaning beyond the schema by showing how to use the output (template variables), which helps the agent understand the parameter's role.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Fetch') and clearly states the resources: IP, auth token, and status. It distinguishes from siblings like 'openclaw_chat_completion' and 'openclaw_tools_invoke' by focusing on instance details.
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 before subsequent OpenClaw actions by mentioning template variables, but it does not explicitly state when to prefer this tool over alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It mentions data sources (Fiber AI, LLM, Perplexity), caching (30 days), and the fields returned. This gives sufficient transparency for an enrichment tool, though rate limits or error behavior are not mentioned.
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 two sentences: first states the action and data sources, second lists return fields, caching, and input requirement. No fluff, crucial information front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lists all return fields and mentions caching. No output schema exists, but the returned data is clearly enumerated. It lacks guidance on failure cases or resolution quality, but for a data enrichment tool it is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining that email is the best identifier and that name+company or LinkedIn URL are fallbacks. It also groups inputs into the required 'at least one' condition, which the schema does not convey.
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 enriches a person's professional profile using Fiber AI, LLM, and Perplexity. It lists specific return fields and distinguishes itself from sibling tools like get_linkedin_profile by combining multiple data sources and naming the enrichment action.
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 explicitly states the required inputs: 'Provide at least one of: email, name + company, or LinkedIn URL.' This guides the agent on when to use the tool. It does not compare to sibling tools or give when-not-to-use scenarios, but the input requirement is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the transparency burden. It discloses asynchronous behavior (returns group_id for polling) and mode-specific requirements. No contradictions.
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 three sentences, front-loading the main purpose, then detailing modes and return value. No redundant information, highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (11 params, no output schema), the description covers essential aspects: purpose, modes, required inputs, and async return. It could mention companion status tools or error handling, but it is largely complete for selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 55% schema description coverage, the description adds value by linking parameters to modes (e.g., upload requires photos_json, generate uses age/gender/ethnicity/style). It clarifies which parameters apply to which mode, though some parameter details are left to the schema.
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 it creates a HeyGen Photo Avatar, differentiating between upload and generate modes. It specifies required items for each mode and the return value, distinguishing it from sibling tools like heygen_avatar_generate_video.
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 provides clear context on when to use each mode (upload vs generate) based on required parameters. However, it does not explicitly state when not to use this tool or suggest alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses caching (30-day) and source (Fiber.ai linkedin search). It honestly portrays a read-only search. It could mention rate limits or usage restrictions to be more transparent, but the existing info is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences that front-load the core action and source. No redundant phrases; every part provides essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers identification methods (company name, domain, linkedin slug), optional filters, and output details. No output schema exists, so the description compensates well. Could mention if more than 10 results are possible or pagination, but not essential for a simple search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds value by specifying the output fields (name, title, LinkedIn URL, skills) beyond the schema, helping agents understand what the tool returns.
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 'discovers people at a company using Fiber.ai LinkedIn search'. It specifies the verb ('discovers'), resource ('people at a company'), and method, differentiating it from sibling tools like 'search_linkedin_people' by naming the source and exact output fields.
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 for finding multiple people at a specific company, which contrasts with sibling tools (e.g., search_linkedin_people for general search, prospect_research_research_prospect for individual research). However, it lacks explicit when-to-use/not-use guidance or alternative suggestions.
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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