competlab-mcp-server

Server Quality Checklist

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Latest release: v2.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose. Tools are organized by dimension (dashboard, history, run detail) and by action (list, get, start, check, fetch). Descriptions are detailed and differentiate similar tools. No two tools appear to do the same thing.
Naming Consistency5/5
Tool names follow a consistent verb_noun pattern with underscores, all lowercase. Groups of related tools (e.g., get_content_dashboard, get_content_history, get_content_run_detail) share a common prefix and suffix pattern. Naming is predictable and unambiguous.
Tool Count3/5
With 33 tools, the server is on the heavier side. While each tool serves a distinct purpose within the broad domain of competitive intelligence, the number exceeds the typical well-scoped range (3-15) and falls into the heavy category (25+). However, the scope is broad, so it is borderline but not extreme.
Completeness4/5
The tool surface covers the five monitoring dimensions comprehensively with dashboard, history, and run detail for each. Additional scanning and generic tools extend functionality. Minor gaps exist: there are no tools to create/update/delete projects or competitors, nor to trigger monitoring runs (only ad-hoc scans). These are workable for an agent focused on retrieval.
Average 4.3/5 across 33 of 33 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 3 commits in the last 12 weeks
- Last stable release on June 23, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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How to sync the server with GitHub?

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

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the full burden. It declares the tool is 'Read-only' and describes the return structure. However, it lacks disclosure of potential side effects, permissions, or rate limits. The prerequisite linkage adds some transparency, 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?
The description consists of four sentences, each serving a distinct purpose: purpose, comparison, usage, prerequisite, read-only note, and return type. It is front-loaded with the main purpose. The phrase 'Returns JSON object' is slightly redundant, but overall the description is concise 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 no output schema, the description references 'the same data structure as get_pricing_dashboard', which is helpful if the agent knows that structure. However, it does not detail the specific fields or any limits. For a tool with only two parameters and a defined use case, this is moderately complete but leaves some gaps for an agent unfamiliar with the dashboard 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 already covers both parameters with descriptions (100% coverage). The description adds only the context that 'runId' comes from 'get_pricing_history', which is already in the schema description. Thus, the description provides marginal 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 clearly states the tool retrieves 'full competitor-by-competitor Pricing Intelligence data for a specific historical run', specifying the verb, resource, and scope. It also distinguishes itself from the sibling 'get_pricing_dashboard' by noting it returns the same structure for a past point in time, making the 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 explicitly advises to 'use this to investigate pricing changes between runs or audit a specific monitoring cycle' and notes the prerequisite 'Requires runId from get_pricing_history.' It does not explicitly state when not to use it, but the comparison with 'get_pricing_dashboard' implies it is for historical data rather than current. This provides clear context for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It only notes 'Read-only' and 'Returns JSON object.' Lacks details on authentication, rate limits, or idempotency. 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?
Two concise sentences with front-loaded key details. No wasted words. 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 no output schema, the description adequately mentions return object contents. Could be more thorough about the exact structure, but sufficient for a simple get 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% (projectId with description). The tool description adds no new parameter information beyond what is already in the schema. Baseline 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 clearly states the action ('Get project details') and specifies the contained information (per-dimension freshness, AI monitoring prompts, status). It distinguishes itself from sibling dimension-specific tools by being the main project detail endpoint.
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 to use after list_projects and before fetching dimension data, providing clear workflow guidance. Does not explicitly mention when not to use, but the context is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark it as readOnlyHint=true and openWorldHint=true. The description confirms 'Read-only' and 'Returns JSON object' but adds limited behavioral detail beyond safety hints, such as rate limits or output complexity.
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 tool's purpose and key features. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the tool's core functionality and scope. Without an output schema, it mentions 'Returns JSON object,' which is sufficient for an agent. More detail on output structure could improve completeness, but it is not missing critical information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters. The description adds overall context (e.g., categorizes by section) but does not provide parameter-specific meaning beyond what is in 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 performs live sitemap analysis, discovering URLs and identifying content gaps and depth. It uses specific verbs and resources, distinguishing it from sibling tools like get_content_dashboard or check_ai_crawlers.
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 states it works on any public domain without project setup, providing clear context for use. It does not explicitly exclude private domains or mention alternatives, but the scope is well-defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It only states 'Read-only' and 'Returns JSON object', missing details like auth requirements, rate limits, or whether it modifies state. The note about same structure as another tool is 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with 4 sentences, front-loaded with purpose and outputs. No redundant information; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 outlines the key returned data (rankings, scores, per-provider) and references another tool's data structure for clarity. With only 2 parameters, it covers the essential context.
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%, but the description adds context beyond the schema by stating 'Uses checkId (not runId)' and re-emphasizing where to get the IDs. This adds meaning for proper 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 'Get full detail for a specific AI Visibility check' with specific outputs (rankings, rates, scores, per-provider). It distinguishes from sibling get_ai_visibility_dashboard by noting 'for a past point in time'.
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 tells where to get checkId values (from get_ai_visibility_history) and notes it uses checkId not runId. It states it is read-only. However, it does not explicitly state when to use this versus alternatives or when not to.
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?
Declares read-only status and describes pagination behavior with hasMore flag. No annotations provided, so description partially covers transparency. Missing rate limits or authentication details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three efficient sentences: action, usage motivation, and drill-down direction. 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?
With no output schema, description specifies return type (JSON array, pagination.hasMore) and references sibling. Could mention error handling but adequate for a list 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 all 3 parameters with descriptions. Description adds no extra meaning beyond schema, 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?
Clearly states verb 'Get', resource 'pagination history of Positioning monitoring runs with completion timestamps', and distinguishes from sibling tool get_positioning_run_detail.
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 mentions when to use for tracking competitor messaging and directs to get_positioning_run_detail for specific run data. No explicit when-not, but clear 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 provided, so description carries full burden. It mentions 'Read-only' and pagination with hasMore flag, but does not disclose permission requirements or rate limits, which are important for a 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with purpose, no unnecessary words or redundancy. Very concise.
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, so description compensates by mentioning paginated JSON array with hasMore flag, but lacks explicit item fields. However, references to get_pricing_run_detail fill the gap for details.
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 description adds minimal value beyond what schema already documents. It links runId to another tool but does not enhance parameter understanding.
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 a paginated history of Pricing Intelligence monitoring runs with completion timestamps, distinguishing it from sibling tools like get_pricing_dashboard and get_pricing_run_detail.
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 says to track competitor pricing changes and to use runId with get_pricing_run_detail for details, providing clear context. Does not explicitly state when not to use, but the context is sufficient.
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 the full burden of behavioral disclosure. It declares the tool is read-only and returns a JSON object, and mentions a specific possible value for security headers. However, it does not cover error scenarios, auth requirements, rate limits, or what happens on invalid inputs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with six sentences each serving a distinct purpose: core function, comparison to sibling, usage guidance, parameter origin, a behavioral detail, and final attributes. No redundant or irrelevant 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?
Given no output schema and no annotations, the description covers the main purpose, usage, parameter requirements, a behavioral quirk, and return type. Missing error handling and full output structure, but adequate for a read-only tool with simple 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% for both parameters, with descriptions in the schema indicating how to obtain each ID. The description reiterates that runId comes from get_tech_trust_history, adding no new semantic 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 clearly states the tool retrieves full competitor-by-competitor Tech & Trust data for a specific historical run, using the verb 'get' and specifying the resource. It explicitly distinguishes from the sibling tool get_tech_trust_dashboard by noting it returns the same structure but for a past point in time.
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 explains when to use the tool ('investigate what changed between runs or to audit a specific monitoring cycle') and how to obtain the required runId from get_tech_trust_history. It does not explicitly state when not to use it, but the comparison with get_tech_trust_dashboard implies the context.
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?
Declares tool as read-only and returns a JSON object, aligning with safe usage. Mentions returning the same structure as get_content_dashboard, providing behavioral insight. Without annotations, this covers essential behavioral aspects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Five sentences front-load purpose, comparison, use case, dependency, and safety—each sentence adds unique value without redundancy or 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?
For a simple tool with two parameters and no output schema, the description sufficiently covers purpose, usage, behavior, and return format, though it could optionally mention data limits or ordering.
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 already describes both parameters (runId and projectId) with sources, achieving 100% coverage. Description reinforces runId source but adds minimal new meaning beyond the schema, 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 it retrieves competitor-by-competitor Content Intelligence data for a past historical run, distinguishing it from get_content_dashboard (current data) and other siblings.
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 recommends use to investigate content strategy changes between runs and specifies prerequisite of runId from get_content_history. Implicitly contrasts with get_content_dashboard for current data, guiding selection.
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 'Read-only', 'Returns paginated JSON array with pagination.hasMore flag', and mentions completion timestamps. This provides sufficient behavioral transparency for a read-only history 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 three sentences, front-loading the main purpose, then usage context, then additional details. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the pagination and sibling context, the description covers key aspects: pagination flag, drill-down capability, and what each run contains. It could mention ordering but overall 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 baseline is 3. The tool description does not add extra parameter-specific meaning beyond what the schema already provides (defaults, max, source).
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 'Get paginated history of Tech & Trust monitoring runs' with specific verbs and resources. It distinguishes from sibling tools by mentioning the domain (Tech & Trust) and the full snapshot nature, and references a related detail tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use: 'compare changes over time' and directs to get_tech_trust_run_detail for specific run data. It does not explicitly state when not to use, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It clearly states 'Read-only' and describes return structure (enabled/disabled, interval, timestamps). This is adequate for a read operation with no destructive 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?
The description is concise with five sentences, each adding value. It could be slightly more structured, but it is efficient and front-loaded with the primary purpose.
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 low complexity, single parameter, and no output schema, the description fully covers purpose, return structure, naming conventions, use cases, and safety. No gaps remain.
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 (projectId) has 100% schema coverage with a clear description. The tool description adds no additional parameter meaning, meeting the baseline expectation.
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 lists monitoring schedules for all 5 dimensions, specifying the returned fields. It distinguishes itself from sibling tools like get_tech_trust_dashboard which likely return per-dimension 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 provides explicit use cases: 'check when the next monitoring run is due or verify scheduling configuration.' It implies usage over per-dimension tools but lacks explicit when-not or 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?
Description aligns with readOnlyHint and openWorldHint annotations, adding details about specific crawlers checked and the methods (robots.txt, meta tags). It also explicitly says 'Read-only' and returns JSON, providing behavior beyond 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?
Extremely concise at two sentences, front-loaded with key action and covered crawlers. Every sentence adds value with no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 (2 params, no output schema), the description fully covers purpose, behavior, and output format. It mentions specific crawlers and that it's read-only, providing sufficient context for correct 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 clear descriptions for domain and industry parameters. The description adds little extra beyond stating it works on any public domain, so 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?
Description clearly states it does a live check of AI crawler access via robots.txt and meta tags, covering multiple specific crawlers and returning per-crawler verdict. This distinguishes it from siblings like check_sitemap.
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?
States it works on any public domain with no setup, implying ease of use. It doesn't explicitly list when not to use or alternatives, but the purpose is clear enough for the agent to decide.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnlyHint, openWorldHint), the description details behavioral traits: returns status during execution, partial detection under behavioral protection, recommended polling interval, and explicitly states read-only. This adds significant context for the agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (5 sentences) and front-loaded with the main purpose. Every sentence contributes valuable information: return types, edge cases, polling guidance, and safety. No superfluous content.
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 complexity of a tech-stack scan (status, results, partial detection), the description covers all relevant return scenarios, edge cases, and usage recommendations. Despite lacking an output schema, the description sufficiently explains what the tool returns and when.
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 the single parameter 'scanId', which is already described in the schema. The description does not add additional semantic information or constraints beyond what the schema provides, so it meets the baseline but does not exceed.
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 'status or full results of a tech-stack scan'. It specifies the key input (scanId) and differentiates from sibling tools by focusing on tech-stack scans. It also describes both running and completed states, and the partial detection scenario, leaving no ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving tech-stack scan results, but does not explicitly contrast with alternatives like other scanning tools. It provides a recommended poll interval, which is helpful, but lacks when-not-to-use guidance or explicit sibling differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses the tool is read-only, returns a paginated JSON array with a hasMore flag, and that alerts include change diffs and action hints. This provides solid behavioral context beyond the schema. It could mention error handling or caching, but overall it is transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is four sentences, front-loaded with the purpose, then filters, then response details, then usage hint. Every sentence adds value 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.
Completeness5/5
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 explains the return type (JSON array with pagination.hasMore) and contents (change diffs, action hints). It covers purpose, filters, usage guidance, and read-only nature. With 6 parameters and rich sibling context, the description is 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 baseline is 3. The description adds minimal extra meaning beyond the schema, such as noting that projectId comes from list_projects and competitorId from list_competitors. It repeats the enum options for dimension and severity. No deep parameter semantics are added, but the existing schema is already descriptive.
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 starts with a specific verb-resource combination: 'Get paginated competitive alerts'. It clearly states the scope ('detected changes across all monitored dimensions') and lists filter options by dimension, severity, and competitorId. The phrase 'before diving into specific dimension dashboards' distinguishes this tool from the per-dimension siblings.
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 tells the agent when to use this tool: 'Use this to find recent competitive changes before diving into specific dimension dashboards.' It also clarifies it is read-only and returns paginated results with a hasMore flag. It does not explicitly state when not to use it or list alternatives, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool is read-only and returns a JSON array, and includes behavioral details like the inclusion of the user's own domain with an isOwn marker. This adds value beyond the schema, though it could mention any potential rate limits or permission requirements.
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 and front-loaded, with no wasted words. It states the main action, key details, and usage context in a few well-structured sentences. Every sentence adds value.
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 there is no output schema, the description adequately explains the output format (JSON array with domain, name, status, and isOwn flag). It also provides usage context and links to other tools. For a simple list tool, this is 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 description coverage is 100% because the sole parameter (projectId) has a clear description in the schema: 'Project ID (from list_projects)'. The tool description does not add additional semantic 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 lists all competitors for a project, including the user's own domain, and specifies the returned fields (domain, name, status). It distinguishes itself by indicating the output is a JSON array and mentions its use for getting competitorId values, differentiating from sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states that this tool is used to get competitorId values needed by several other tools (list_alerts, get_competitor, get_content_changelog). It also notes that the tool is read-only. However, it does not explicitly say when not to use it or mention alternatives, but the sibling context provides additional differentiation.
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 adds async behavior, polling mechanism, and scan record creation beyond annotations (readOnlyHint=false). It covers state change and typical duration, 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?
Concise at ~50 words, front-loaded with action, logically structured with detection categories, return info, timing, and side effect. No fluff.
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?
Complete for a 1-param async tool: explains purpose, detection scope, return value, polling method, and typical duration. No missing 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% with domain parameter already described adequately. Description adds no new parameter meaning but reinforces the domain scanning purpose.
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 starts an async tech-stack detection on any domain, listing specific detection categories (hosting, frameworks, CMS, etc.) and distinguishes from sibling tools like get_tech_stack_scan and other start_* scans.
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 advises using this tool for tech-stack detection, explains it returns a scanId for polling, and mentions typical completion time, though it 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description states it is 'Read-only' and describes the return format as a 'paginated JSON array with pagination.hasMore flag.' It also highlights the unique data model. With no annotations provided, the description carries the full burden and adequately covers key behavioral aspects, though it could mention authentication or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only three sentences, each adding distinct value: purpose, data model note, usage guidance, and return format. No redundancy 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 paginated browsing tool with no output schema, the description adequately describes the return format (paginated JSON array with hasMore flag) and mentions completion timestamps. It could include more detail on each item’s structure, but the sibling tool get_ai_visibility_check_detail handles full detail, so this 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%, so the schema already documents all three parameters (page, limit, projectId) with constraints. The description does not add significant semantic detail beyond reinforcing pagination. Baseline 3 is appropriate as per guidelines.
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 explicitly states 'Get paginated history of AI Visibility checks with completion timestamps,' providing a specific verb and resource. It also clarifies the unique data model (each check is a 3-prompt x 3-LLM cycle) and distinguishes from siblings like get_ai_visibility_check_detail and get_ai_visibility_trend.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool ('browse past checks') and when to use alternatives ('retrieve full detail with get_ai_visibility_check_detail, or use get_ai_visibility_trend for aggregate time-series'). It also warns about the checkId vs runId distinction, providing clear 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 discloses that the tool is 'Read-only' and 'Returns paginated JSON array with pagination.hasMore flag.' This provides essential behavioral information beyond the schema, especially given no annotations are provided. 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 concise with four well-structured sentences. Each sentence serves a distinct purpose: stating the function, outlining filters, providing usage guidance, and noting read-only and return format. 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 the tool has 5 parameters and no output schema, the description covers purpose, usage, filtering, return type (paginated JSON array with hasMore flag), and safety. It is nearly complete, though a bit more detail on the output structure could be beneficial.
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 baseline is 3. The description adds value by giving examples of category values (e.g., blog, docs) and mentioning the pagination flag, which provides context beyond the schema's 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's purpose: 'Get detected content changes over time — new URLs, removed URLs, moved URLs.' It uses a specific verb ('Get') and resource ('content changelog'), and differentiates it from sibling tools like get_content_dashboard by noting that it shows changes rather than current state.
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 says 'Use this instead of comparing full runs when you only need to know what changed' and 'Complements get_content_dashboard which shows the current state.' This provides clear context on when to use the tool, though it doesn't explicitly state 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?
The description declares 'Read-only' which is a key behavioral trait, and mentions the response format (paginated JSON with hasMore flag). Since no annotations are provided, this self-disclosure is valuable, though it lacks details on potential side effects or prerequisites beyond projectId.
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 three sentences that are front-loaded with the main purpose, followed by usage guidance and behavioral notes. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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 covers the return format and pagination details. It mentions the need for projectId and the relationship to get_content_run_detail. While not exhaustive, it provides sufficient context for a list 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 the baseline is 3. The description does not add additional meaning beyond what is already in the schema for each parameter; it only provides overall context. Thus, no extra credit beyond 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 tool retrieves paginated history of Content Intelligence monitoring runs with completion timestamps. It distinguishes itself from siblings like get_content_run_detail by specifying the retrieval of a list versus a single run.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use this tool ('to compare content snapshots over time') and provides an alternative for retrieving specific run data using get_content_run_detail, fulfilling the need for usage 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?
Since no annotations are provided, the description carries the full burden. It declares the tool is read-only and returns a JSON object. This is sufficient for a simple read operation, though it could mention data freshness or caching. Still, it communicates the key behavioral trait of non-destructiveness.
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 long, with the first providing purpose and the second listing returned fields. It is efficient and front-loaded, though the list of fields is lengthy but necessary for clarity. No wasted words.
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?
Despite lacking an output schema, the description enumerates all returned fields comprehensively. It covers usage context (latest snapshot vs history) and the single required parameter is well-documented in the schema. The tool's behavior and output are fully described for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the schema already providing a clear description of projectId. The tool description adds no additional semantic detail beyond what the schema offers, thus the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it gets the latest Positioning analysis for all competitors, listing over a dozen specific fields returned. It distinguishes itself from the sibling tool get_positioning_history, which is for past runs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly instructs to use this for the current snapshot and mentions the alternative get_positioning_history for past runs, providing clear guidance on when to use each.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses read-only behavior and return type (JSON object). Could mention data freshness, but adequate for a read-only snapshot 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?
Three concise sentences, front-loaded with purpose, then details, usage alternative, and read-only note. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Describes return components (plans, stats, gap analysis, AI analysis) but lacks exact response fields. Without output schema, slightly more detail could help, but sufficient given tool's complexity and 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% with one parameter (projectId) described in schema. Description adds no additional meaning beyond the schema's description. 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 it 'Get the latest Pricing Intelligence for all competitors,' specifying the verb and resource. It differentiates from the sibling tool 'get_pricing_history' by noting use for current snapshot vs. past runs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use this for the current snapshot; use get_pricing_history for past runs,' providing clear when-to-use and alternative guidance. Also marks tool as read-only.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds significant behavioral context beyond annotations: explains behavior while running, when complete, and the special case where signalsAvailable is false, including placeholder values. Annotations already declare readOnlyHint and openWorldHint, and description reinforces 'Read-only.' with no contradiction.
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?
Description is front-loaded with main purpose and efficiently uses sentences to convey critical details. Slightly lengthy due to special case explanation, but every sentence adds value. Could be more streamlined.
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 no output schema, description thoroughly explains output format (status, verdicts, signalsAvailable case, placeholder values) and provides polling guidance. Combined with annotations, it is fully informative for a one-parameter read-only 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 has 100% coverage with description for scanId stating 'Scan ID (from start_trust_signals_scan).' The tool description mentions scanId but does not add new semantic detail beyond the schema, so baseline 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 'Retrieve status or full results of a trust-signals scan by scanId.' It specifies the resource (trust-signals scan) and action (retrieve), and distinguishes from siblings by detailing output like per-signal verdicts and tier verdict, plus a special case for behavioral protection.
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?
Provides explicit guidance: 'always check signalsAvailable first' and recommends a poll interval of 5-10 seconds. Implies usage after starting a scan, but does not explicitly mention when not to use or list alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses async behavior, immediate return of scanId, typical completion time (30-90 seconds), and that it creates a scan record. This adds significant context beyond the annotations (readOnlyHint=false, openWorldHint=true), which already indicate mutation and open input.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences long, front-loads the core purpose, and each sentence provides essential information about the action, return value, and typical behavior. No wasted words.
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 single-parameter async start tool, the description covers what it does, how to retrieve results, and expected timing. It lacks mention of error conditions or limits, but overall it is sufficiently complete for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter (domain) with 100% description coverage via the example. The tool description adds context about the analysis but does not further clarify the parameter meaning or format, making it adequate but not outstanding.
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 starts an async trust-signals analysis on any domain, listing specific signal categories. It distinguishes itself from sibling tools like get_trust_signals_scan (polling) and other start_* tools by focusing on trust signals.
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 explains that it returns a scan ID immediately and advises polling with get_trust_signals_scan, giving clear context on the async flow. However, it does not explicitly state when not to use this tool or compare it to alternative start_* tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It declares the tool is 'Read-only' and explains the return value details (scores, mention rate, per-provider breakdowns, etc.) and the number of AI queries per check. It could mention caching or rate limits but is otherwise 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 concise paragraph that front-loads the main action and then efficiently lists details. Every sentence adds value and there is no redundancy.
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 has one required parameter and no output schema, the description thoroughly explains the return content (score, mention rate, per-provider, rankings, analysis) and contextualizes the cost (9 queries per check). It also differentiates from related tools in the sibling set.
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% (one parameter, projectId). The schema's description already says 'Project ID (from list_projects).' The description adds no further semantics about the parameter, but since coverage is high, 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 purpose: 'Get the latest AI Visibility scores for all competitors.' It identifies the unique dimension of CompetLab and distinguishes from sibling tools by explicitly naming get_ai_visibility_history and get_ai_visibility_trend.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool ('Use this for the current snapshot') and when to use alternatives ('use get_ai_visibility_history for past checks or get_ai_visibility_trend for time-series data'). It also notes that each check uses 9 AI queries.
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 states 'Read-only' and 'Returns JSON object,' which are key traits. However, it does not mention data freshness, latency, or any potential limits. For a read-only dashboard, the disclosure is mostly adequate but could be more thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at 4 sentences, front-loaded with purpose, followed by detailed contents and usage guidance. No unnecessary words.
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 simplicity (1 parameter, no output schema), the description thoroughly covers what the tool does, its return content (extensive list), and relationship to siblings. Agents have sufficient context to use this 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 coverage is 100% (1 parameter, projectId, described in schema). The description adds no additional meaning about the parameter beyond what the schema provides. Baseline is 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 starts with a clear verb and resource: 'Get the latest Content Intelligence for all competitors.' It lists specific return data and distinguishes from siblings by mentioning get_content_history and get_content_changelog, establishing a unique purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly directs agents: 'Use this for the current snapshot; use get_content_history for past runs or get_content_changelog for URL-level changes.' This provides clear when-to-use and when-not-to-use guidance with named 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?
Since no annotations are provided, the description carries full burden. It states 'Read-only' and 'Returns JSON object', indicating a safe, non-destructive operation. It also mentions the return structure is the same as 'get_positioning_dashboard', providing helpful context. Could mention authorization or rate limits but is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, very efficient. First sentence defines the action and output. Second sentence provides use case and prerequisites. No wasted words.
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?
With no output schema, the description explains the return structure (same as dashboard). Both parameters are explained with sources. Use case and prerequisites are covered. Complete for a read-only retrieval 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% with descriptions for both parameters. The description adds extra context by specifying that 'runId' comes from 'get_positioning_history' and 'projectId' from 'list_projects', which is helpful beyond the schema's type/pattern info.
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 'full competitor-by-competitor Positioning data for a specific historical run' using the verb 'Get' and the resource 'Positioning data for a historical run'. It distinguishes from siblings like 'get_positioning_dashboard' by specifying 'for a past point in time'.
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 says 'Use this to investigate how competitor messaging evolved between runs' and notes the prerequisite 'Requires runId from get_positioning_history'. While it implies the alternative 'get_positioning_dashboard' for current data, it does not explicitly state 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It explicitly states 'Read-only. Returns JSON array of projects,' disclosing the read-only nature and return type. Does not mention potential side effects or pagination, but for a zero-parameter list operation this 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?
Three sentences: first states purpose and outputs, second provides usage guidance, third adds behavioral info. No unnecessary words, all content earns its place.
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?
For a zero-parameter list tool with no output schema, the description covers purpose, return fields, usage context, and read-only nature. No gaps given the tool's simplicity.
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?
No parameters; schema coverage is 100% (empty). Description confirms no inputs needed, adding no extra semantics but meeting baseline for zero 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 verb (List), resource (projects), scope (all in your organization), and specifies returned fields (status, competitor count, last monitored timestamp). It also distinguishes from siblings by explicitly saying 'Start here' and indicating that this tool provides projectId values needed by others.
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 says 'Start here — call this first to discover available projectId values required by all other tools,' providing clear when-to-use guidance. Does not mention when not to use or alternatives, but the context is well-established.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, openWorldHint), the description discloses that advanced fingerprinting may block header retrieval and flags it via headersAvailable. It also explains cleanHtml as a token-cost win for LLM. No contradictions with 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?
Two sentences, front-loaded with purpose, then critical behavioral detail. Every sentence earns its place; 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?
No output schema, but description adequately covers return fields (body, headers, cleanStats). It mentions failure mode. Lacks explicit error handling details but sufficient for a fetch 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%, so baseline is 3. The description adds value by explaining cleanHtml's purpose (token-cost win) and headersAvailable flag, exceeding schema info.
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 fetches URLs with automatic JS-rendering and bot-protection handling. It distinguishes itself from siblings (e.g., check_ai_crawlers, get_tech_stack_scan) by being a generic fetcher, not domain-specific.
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 general URL fetching with JS rendering, but does not explicitly state when not to use or compare to alternatives. However, siblings are all different domains, so context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description compensates by explicitly stating 'Read-only' (no side effects) and 'Returns JSON object' (output type). This provides sufficient behavioral transparency for an agent to understand the tool's safety profile and 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?
The description is two sentences, immediately front-loading the purpose and key details. Every sentence adds value: first defines function, second gives usage context and behavioral notes. No extraneous words.
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 states 'Returns JSON object', which is minimal but acceptable for a retrieval tool. It covers required parameters (projectId, competitorId) and output contents (monitored pages, configuration). Could mention potential errors or size, but for a single-object getter, it's adequate.
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?
Input schema has 100% coverage with descriptions for both parameters. The description adds context beyond the schema by explaining that competitorId is obtained from list_competitors and that returned details include 'monitored pages' (homepage and pricing page URLs) and configuration, giving semantic meaning to the output fields.
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 'Get competitor details' and specifies included fields (monitored pages with homepage/pricing URLs, configuration). Distinguishes from sibling list_competitors by noting it provides metadata beyond what list_competitors offers, with an example (finding tracked URLs).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use ('when you need specific competitor metadata beyond what list_competitors provides') and provides a prerequisite ('Requires competitorId from list_competitors'). This gives clear guidance on context and alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully covers behavioral traits: it explains null values for securityGrade/securityScore and the 'unscannable' case with behavioral protection, and declares read-only and JSON output.
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 moderately long but well-structured, front-loading the main purpose and then detailing returned data. Every sentence adds value, though it could be slightly more concise without losing information.
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 no output schema, the description thoroughly explains the comprehensive return data (various signals, categories) and edge cases. It provides enough context for an AI 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?
The single parameter (projectId) has full schema description coverage (100%), so the description does not need to add much. It mentions 'Project ID (from list_projects)' in the schema, which is sufficient. The description does not elaborate further, but given the simple parameter, this is adequate.
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 the latest Tech & Trust Profile for all competitors, listing specific data categories (security headers, trust signals, tech stack, etc.). It distinguishes from the sibling 'get_tech_trust_history' by specifying 'current snapshot vs. past runs'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use this for the current snapshot; use get_tech_trust_history for past runs,' providing clear when-to-use guidance and a direct alternative. It also states 'Read-only,' indicating safe usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses important behavioral traits beyond annotations: special handling for bot-protected targets, neutral scoring, and a counter rename from n8nCalls. No contradiction with readOnlyHint and openWorldHint 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 concise with five sentences, each serving a distinct purpose: purpose, runtime behavior, exception details, counter rename, and polling recommendation. It is front-loaded with the most critical information.
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 complexity (multiple states, exception handling, counter rename), the description covers all necessary context without an output schema. It explains what the tool returns and how to use it effectively.
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?
The input schema fully describes scanId (pattern, description). The description adds useful context that scanId comes from start_agent_adoption_scan, linking the tools and clarifying origin. With 100% schema coverage, this additional context elevates the score above 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 tool retrieves status or full results of an Agent-Adoption Check by scanId. It uses a specific verb ('retrieve') and identifies the resource, differentiating from sibling tools like get_ai_visibility_check_detail or start_agent_adoption_scan.
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 explicit context for usage: it returns status while running and complete results when finished, and recommends a polling interval of 5-10 seconds. It implies when to use (after starting a scan) but does not explicitly exclude other scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate non-read and open-world behavior. Description adds async nature, immediate scanId return, record creation, and typical timing, providing rich 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, front-loaded with key information, no redundancy.
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?
For an async scan tool with one parameter and no output schema, the description provides all necessary context: what it does, how to retrieve results, and expected timing.
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?
Only one parameter 'domain' with schema description 'Domain to scan, e.g. example.com'. Schema coverage is 100%, and description adds context about any domain and scope of checks, adding value 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 it starts an async Agent-Adoption Check on any domain, specifying 25 checks across discoverability, access control, content readability, and agent endpoints. Differentiates from siblings like get_agent_adoption_scan and check_ai_crawlers.
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 mentions to poll with get_agent_adoption_scan, and gives typical completion time. Lacks explicit 'when not to use' but provides clear context for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but description covers key traits: read-only, returns up to 200 data points, JSON array, ISO-8601 dates, and explains aggregate vs per-provider computation. 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?
Four sentences, front-loaded with main purpose, each sentence adds necessary information without redundancy.
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 no output schema, description covers return type, format, limits, and behavior for all parameter states, making it fully informative.
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 100% schema coverage, baseline is 3. Description adds value by explaining the effect of provider filter on computation (aggregate vs raw) 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 fetches trend data for AI visibility over time, tracking LLM brand perception. It distinguishes from siblings by specifying alternate tools for snapshot and check detail.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states 'Use this for time-series analysis' and names alternatives: get_ai_visibility_dashboard for latest snapshot, get_ai_visibility_check_detail for specific check. Also explains behavior with/without provider filter.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses key behaviors beyond annotations: it is read-only (consistent with readOnlyHint), explains the availability states (ready, ready-refreshing, preparing, none), mentions regeneration every 30 days, describes the envelope structure, and notes 404 behavior for missing projects. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is lengthy but well-structured, front-loading the core purpose and then detailing usage guidance and behavioral notes. Every sentence adds value, though some parts could be slightly more concise. Overall it is efficiently organized for its complexity.
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 absence of an output schema, the description thoroughly explains return values (meta, coverage, dimensionHealth, item) and the JSON envelope. It covers the lifecycle, availability, and caveats (e.g., coverage methodology, dimensionHealth absent). Completeness is high.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds significant meaning for all parameters. For 'sections', it explains the default ['hub'], the hub→deep flow, and when to add other sections. For 'includeCharts', it clarifies default false and when to set true. For 'projectId', it references list_projects. This goes 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 the tool's purpose: retrieving the synthesized Strategic Briefing. It specifically contrasts with raw monitoring tools and the competitor roster tool, distinguishing it from siblings. The verb 'Get' plus resource 'project's Strategic Briefing' is specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use and when-not-to-use guidance, including alternatives like get_<dimension>_dashboard and list_competitors. It explains the hub→deep drill-down flow, recommends defaulting to 'hub' and adding sections only as needed, and advises branching on meta.availability. This is comprehensive.
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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