mcp-seo-audit

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v2.0.0
Disambiguation3/5
Most tools have distinct purposes, but there is notable overlap between audit tools (audit_live_site, crawl_site_seo, site_audit) and between analytics tools (get_search_analytics, get_advanced_search_analytics, compare_search_periods). Descriptions help differentiate, but agents may struggle to choose the right one for similar tasks.
Naming Consistency4/5
Tools follow a consistent verb_noun pattern (e.g., add_site, analyze_page_seo, get_sitemaps) with only minor deviations like list_properties (verb_noun but missing underscore) and reauthenticate (single word). The naming is mostly predictable and readable.
Tool Count2/5
With 30 tools, the set feels heavy and potentially overwhelming for an SEO audit domain. While the domain is broad, many tools could be consolidated (e.g., multiple audit and analytics tools), leading to redundancy and complexity.
Completeness5/5
The tool set provides comprehensive coverage for SEO auditing, including site management, page analysis, sitemap handling, indexing, performance metrics, and search analytics. There are no obvious gaps, and it supports full CRUD/lifecycle operations for the domain.
Average 3.5/5 across 30 of 30 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 4 commits in the last 12 weeks
- Last stable release on May 26, 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.
Add related servers to improve discoverability.

How to sync the server with GitHub?

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

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

How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('Check') but doesn't explain what 'indexing notification status' entails, such as whether it's a read-only operation, what the response format is, or any rate limits or permissions required. This leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences that directly state the purpose and parameter, with no wasted words. It could be slightly improved by front-loading more context, but it's efficiently structured overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which handles return values) and a simple input schema with one parameter, the description is minimally complete. However, without annotations and with unclear differentiation from siblings, it lacks depth for effective agent use, making it just adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal semantics by specifying that 'url' is 'The URL to check', which clarifies its role. However, with 0% schema description coverage and only one parameter, this is adequate but not exceptional, aligning with the baseline expectation for such a simple schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Check') and resource ('latest indexing notification status for a URL'), making the purpose understandable. However, it doesn't differentiate from siblings like 'inspect_url' or 'batch_inspect_urls', which might have overlapping functionality, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings like 'inspect_url' and 'batch_inspect_urls' available, there's no indication of specific contexts, prerequisites, or exclusions for this tool's use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions crawling and aggregating SEO issues, but fails to disclose critical traits: whether this is a read-only or mutative operation, potential rate limits, authentication needs, or what the output entails (e.g., report format). For a tool that likely involves web crawling and data processing, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the core purpose, followed by a brief parameter list. There's no wasted text, and the structure is clear. However, it could be slightly more polished (e.g., by integrating parameter details more seamlessly), but it's efficient overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (crawling and SEO analysis), no annotations, and an output schema (which likely covers return values), the description is minimally complete. It explains what the tool does and the parameters, but lacks behavioral context and usage guidelines. With the output schema handling return values, the description doesn't need to detail outputs, but it should address other gaps like operational constraints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds basic meaning for both parameters: 'start_url' as the 'First URL to crawl' and 'max_pages' as the 'Maximum number of same-origin HTML pages to crawl'. This clarifies the intent beyond the schema's bare titles, but it doesn't provide details like URL format constraints or default behavior for 'max_pages' (though the schema shows a default of 10). The compensation is minimal but adequate for a baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Crawl a site from a start URL and aggregate common technical/on-page SEO issues.' It specifies the verb ('crawl'), resource ('site'), and outcome ('aggregate SEO issues'), making it distinct from siblings like 'analyze_page_seo' or 'site_audit' which focus on different aspects. However, it doesn't explicitly differentiate from 'audit_live_site', which might be similar, so it's not a perfect 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, such as needing the site to be added first (via 'add_site'), or compare it to siblings like 'audit_live_site' or 'site_audit' that might offer overlapping functionality. This lack of context leaves the agent guessing about appropriate use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions 'detailed info' but doesn't disclose behavioral traits like whether this is a read-only operation, requires authentication, has rate limits, or what the output format entails. This leaves significant gaps for a tool that likely interacts with external services.
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 appropriately sized and front-loaded, with the main purpose stated first and parameter details following. There's no wasted text, but the structure could be slightly improved by integrating the parameter note more seamlessly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema, the description doesn't need to explain return values. However, with no annotations, low parameter schema coverage, and complexity from interacting with GSC, the description is incomplete—it lacks context on authentication, error handling, or operational limits, which are crucial for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal semantics beyond the input schema: it specifies that 'site_url' is an 'Exact GSC property URL', which clarifies the parameter's purpose. However, with 0% schema description coverage and only 1 parameter, this provides some value but doesn't fully compensate for the lack of schema details, such as format examples or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List all sitemaps') and resource ('for a property with detailed info'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'analyze_sitemap' or 'submit_sitemap', which would require mentioning scope or purpose distinctions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context, or exclusions, such as whether it requires prior setup or differs from other sitemap-related tools in the sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral context. It mentions what the tool inspects (indexing status, rich results, mobile usability) but doesn't disclose critical details like rate limits, authentication requirements, response format, or whether it's a read-only operation. For a tool with no annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with two sentences: one stating the purpose and another listing parameters with brief explanations. It's front-loaded with the core function. The parameter section could be slightly more structured, but overall it's efficient with minimal waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which handles return values) and only 2 parameters, the description is moderately complete. However, with no annotations and 0% schema description coverage, it should provide more behavioral context (e.g., rate limits, authentication) and clearer parameter guidance to be fully adequate for agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds value by explaining that 'site_url' requires an 'Exact GSC property URL' with an example format, and 'page_url' is 'The specific URL to inspect'. However, it doesn't fully document both parameters' semantics (e.g., what constitutes a valid GSC property URL beyond the example). Baseline would be lower without this partial compensation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Inspect a URL for indexing status, rich results, and mobile usability.' This specifies the verb ('inspect') and resource ('URL') with concrete inspection targets. However, it doesn't explicitly differentiate from sibling tools like 'batch_inspect_urls' or 'analyze_page_seo', which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'batch_inspect_urls' for multiple URLs or 'analyze_page_seo' for broader SEO analysis. There's no context about prerequisites or when-not-to-use scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the action ('Add a site') but doesn't clarify whether this requires specific permissions, what happens on success/failure, if the site becomes immediately available for analysis, or any rate limits. This is a significant gap for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear purpose statement followed by parameter details in a labeled 'Args' section. It avoids unnecessary fluff, though the two-sentence format is slightly more verbose than a single integrated sentence might be.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (a mutation with one parameter) and the presence of an output schema (which handles return values), the description is minimally adequate. However, it lacks behavioral context and usage guidelines, which are important for an agent to invoke this correctly in practice.
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 description adds meaningful context for the single parameter 'site_url' by providing examples (e.g., 'https://example.com or sc-domain:example.com'), which clarifies format beyond the schema's basic string type. With 0% schema description coverage, this effectively compensates for the schema's lack of detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Add' and the resource 'site to your Search Console properties', making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'submit_sitemap' or 'list_properties', which could involve similar domain operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'list_properties' (for viewing existing sites) or 'delete_site'. It mentions no prerequisites, constraints, or typical scenarios for adding a site, leaving usage context entirely implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "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 mentions the API returns data but doesn't describe rate limits, authentication needs, error handling, or whether it's read-only/destructive. 'Run' implies an action but lacks details on costs, latency, or side effects, leaving significant gaps for a tool interacting with an external API.
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 appropriately sized with 3 sentences: purpose, return data, and parameter details. It's front-loaded with the main action and uses a clear 'Args:' section. No wasted words, though it could be slightly more structured with bullet points.
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 3 parameters with 0% schema coverage and an output schema (which handles return values), the description is moderately complete. It explains parameters well but lacks behavioral context (e.g., API constraints) and usage guidelines. For a tool with external API calls and no annotations, more detail on limitations would improve completeness.
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 0%, so the description must compensate. It adds meaningful semantics: 'url' as 'Full page URL', 'strategy' as 'mobile or desktop', and 'categories' as 'Comma-separated Lighthouse categories', clarifying format and options beyond the bare schema. This adequately covers the 3 parameters, though it could specify default values or examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Run Google's PageSpeed Insights API for a URL' with specific verb ('Run') and resource ('PageSpeed Insights API'), and distinguishes it from siblings like 'run_lighthouse_audit' by mentioning it returns 'Lighthouse lab data plus available Chrome UX Report field data'. However, it doesn't explicitly differentiate from all SEO/performance siblings, keeping it at 4.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'run_lighthouse_audit', 'get_core_web_vitals', or 'audit_live_site'. It mentions what the tool does but offers no context about use cases, prerequisites, or exclusions, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'fetch a page and analyze' but does not specify details like whether it requires authentication, rate limits, what happens if the URL is invalid, or the format of the analysis results. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with a clear purpose statement followed by a concise 'Args' section. Every sentence earns its place, providing essential information without waste, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (SEO analysis with one parameter) and the presence of an output schema (which likely covers return values), the description is minimally adequate. It explains what the tool does but lacks details on behavioral aspects and usage context. With no annotations and incomplete parameter guidance, it meets the baseline but has clear gaps.
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 description adds meaning beyond the input schema by specifying that the 'url' parameter should be a 'Full page URL'. The schema has 0% description coverage (only a title 'Url'), so this clarification is valuable. However, it does not elaborate on URL format requirements or constraints, keeping it from a perfect score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Fetch a page and analyze on-page SEO signals, structured data, and indexability hints.' It uses specific verbs ('fetch', 'analyze') and resources ('page', 'SEO signals'), making the function evident. However, it does not explicitly differentiate from siblings like 'inspect_url' or 'run_lighthouse_audit', which might have overlapping functionality, so it falls short of a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention any context, prerequisites, or exclusions, such as comparing it to 'inspect_url' for basic checks or 'run_lighthouse_audit' for performance analysis. Without such information, the agent lacks clear direction on tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 mentions 'validate with GET requests' for sampled URLs, hinting at network activity, but doesn't cover critical aspects like rate limits, authentication needs, error handling, or what 'analyze' entails (e.g., parsing, reporting). This is a significant gap for a tool that performs external requests.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise and well-structured: a clear purpose statement followed by bullet-point parameter explanations. Every sentence earns its place with no wasted words, making it easy to scan and understand quickly.
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 2 parameters with 0% schema coverage and an output schema present, the description does an adequate job explaining inputs but lacks behavioral context (e.g., network effects, analysis scope). The output schema likely covers return values, reducing the burden, but for a tool that fetches and analyzes external resources, more guidance on usage and limitations would 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 0%, so the description must compensate. It adds meaningful context for both parameters: 'sitemap_url' is clarified as a 'Full sitemap URL', and 'sample_urls' is explained as 'Number of sitemap URLs to validate with GET requests'. This goes beyond the bare schema, though it could detail validation outcomes or URL format expectations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('fetch and analyze') and resource ('XML sitemap or sitemap index'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_sitemaps' or 'crawl_site_seo', which could have overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_sitemaps' (which might list sitemaps) or 'crawl_site_seo' (which might perform broader analysis). There's no mention of prerequisites, typical use cases, or exclusions, leaving the agent to guess based on tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 states the tool compares analytics but doesn't describe what metrics are compared, the output format, whether it's a read-only operation, authentication requirements, rate limits, or potential side effects. For a tool with 7 parameters and no annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear purpose statement followed by a well-organized parameter list. Every sentence earns its place: the first sentence establishes the core function, and the Args section provides essential parameter details without redundancy. The information is front-loaded and appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 7 parameters, no annotations, but does have an output schema, the description is partially complete. The parameter semantics are well-covered, but behavioral aspects are lacking. The output schema existence means the description doesn't need to explain return values, but it should still address when to use this tool versus siblings and provide more context about the comparison operation itself.
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 description provides explicit parameter documentation in the Args section, listing all 7 parameters with brief explanations. Since schema description coverage is 0% (titles only, no descriptions), the description fully compensates by adding semantic meaning to each parameter. It clarifies date formats, default values for dimensions and limit, and the exact nature of site_url. This goes well beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Compare search analytics between two time periods.' This specifies the verb ('compare') and resource ('search analytics') with context about time periods. However, it doesn't explicitly differentiate from sibling tools like 'get_search_analytics' or 'get_advanced_search_analytics' which might also retrieve search analytics data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With multiple sibling tools related to search analytics (get_search_analytics, get_advanced_search_analytics, get_search_by_page_query), the agent receives no help in selecting this specific comparison tool over other analytics retrieval tools. No prerequisites, exclusions, or comparative context are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states the action ('Remove') without disclosing critical behavioral traits such as whether this is destructive, requires specific permissions, or has irreversible effects. This is inadequate for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded, with the core purpose in the first sentence and parameter details in a brief, structured format. Every sentence earns its place without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a destructive operation with no annotations) and the presence of an output schema, the description is minimally adequate but lacks crucial details like safety warnings or usage context. It meets basic needs but has clear gaps.
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 description adds meaningful context for the single parameter by specifying 'The URL of the site to remove', which clarifies the parameter's purpose beyond the schema's minimal title. With 0% schema description coverage, this compensates well, though it could detail format constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Remove') and resource ('a site from your Search Console properties'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'request_removal' or 'delete_sitemap', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'request_removal' or 'delete_sitemap', nor does it mention prerequisites or consequences. This leaves the agent without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool retrieves data ('Get'), implying a read-only operation, but doesn't disclose behavioral traits such as authentication requirements, rate limits, data freshness, or error handling. For a tool with no annotations, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: a clear purpose statement followed by parameter explanations in a bullet-like format. Every sentence adds value without redundancy, making it easy to scan and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 parameters, no annotations, but has an output schema), the description is minimally adequate. It covers the purpose and parameters but lacks usage guidelines and behavioral details. The output schema may handle return values, but the description doesn't provide enough context for effective use without additional information.
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 description adds meaningful semantics beyond the input schema. The schema has 0% description coverage, but the description explains that 'site_url' is an 'Exact GSC property URL' and 'days' is the 'Number of days to look back (default: 28),' clarifying usage and context. With only 2 parameters, this is adequate, though not exhaustive.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get a performance overview with totals and daily trend.' It specifies the verb 'Get' and resource 'performance overview' with scope 'totals and daily trend.' However, it doesn't explicitly differentiate from sibling tools like 'get_search_analytics' or 'get_advanced_search_analytics,' which might offer similar performance data, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It mentions the parameters but doesn't indicate context, prerequisites, or exclusions. Given the many sibling tools related to performance and analytics, this lack of differentiation is a significant gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the tool retrieves data ('get'), implying a read-only operation, but does not specify authentication needs, rate limits, data freshness, or what happens if inputs are invalid. For a tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the purpose clearly, followed by a bullet-point list of parameters with concise explanations. Every sentence earns its place, with no wasted words or redundancy, making it easy to scan and understand.
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 that there is an output schema (which handles return values), the description covers the purpose and parameters adequately. However, for a tool with no annotations and multiple parameters, it lacks behavioral context like error handling or performance considerations. It's minimally viable but has clear gaps in usage guidance and transparency.
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 description adds meaningful context beyond the input schema, which has 0% description coverage. It explains that 'site_url' is an 'Exact GSC property URL', 'page_url' is 'The specific page URL to analyze', and provides defaults and constraints for 'days' and 'row_limit'. This compensates well for the schema's lack of descriptions, though it doesn't detail formats or examples for URLs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get search queries driving traffic to a specific page.' It specifies the verb ('get') and resource ('search queries'), and indicates the scope ('driving traffic to a specific page'). However, it does not explicitly differentiate from sibling tools like 'get_search_analytics' or 'get_advanced_search_analytics', which may have overlapping functions, so it doesn't achieve a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It lacks context about prerequisites, such as whether the site must be added first using 'add_site', or when to choose this over other analytics tools like 'get_search_analytics'. There are no explicit when/when-not statements or named alternatives, leaving usage unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions 'Fetch and summarize' but doesn't disclose behavioral traits such as whether it's read-only, potential rate limits, authentication needs, error handling, or what 'summarize' entails (e.g., format, depth). This is a significant gap for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the core purpose stated first and parameter details in a clear 'Args:' section. Every sentence earns its place without redundancy, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (fetching and summarizing a file), no annotations, and an output schema exists, the description is partially complete. It covers the basic purpose and parameter semantics but lacks behavioral details and usage guidelines, which are needed for full context despite the output schema handling return values.
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 description adds meaning beyond the input schema by explaining the parameter 'url_or_origin' as 'Full URL, origin, or sc-domain property', which clarifies acceptable input formats. Since schema description coverage is 0%, this compensates well, though it could provide more examples or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Fetch and summarize') and resource ('the site's robots.txt file'), making it easy to understand what it does. However, it doesn't explicitly differentiate from sibling tools like 'inspect_url' or 'crawl_site_seo', which might also involve URL inspection, so it misses full sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. For example, it doesn't specify if this is for quick checks versus detailed analysis or how it compares to tools like 'inspect_url' or 'audit_live_site'. This leaves the agent without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'retrieves and returns' but lacks details on permissions, rate limits, pagination, or error handling. For a read operation with zero annotation coverage, this is insufficient to inform the agent adequately.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It is front-loaded with the core action and resource, making it efficient and easy to understand, which is ideal for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 0 parameters, 100% schema coverage, and an output schema exists, the description covers the basic purpose adequately. However, without annotations and with multiple sibling tools, it lacks context on usage scenarios and behavioral traits, making it minimally complete but with notable gaps.
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 has 0 parameters with 100% coverage, so no parameter information is needed. The description appropriately does not discuss parameters, earning a high baseline score as it avoids redundancy and focuses on the tool's purpose.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Retrieves and returns') and the resource ('user's Search Console properties'), making the purpose evident. However, it does not explicitly differentiate this tool from similar siblings like 'get_sitemaps' or 'site_audit', which might also involve property-related operations, so it falls short of a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings like 'add_site', 'delete_site', and 'get_sitemaps', it's unclear if this is for listing all properties, filtered properties, or specific use cases, leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool 'shows true organic SEO growth,' implying a read-only analytical function, but doesn't specify data sources (e.g., Google Search Console), permissions required, rate limits, or output format. For a tool with 3 parameters and no annotations, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and concise: two sentences explain the purpose and benefit, followed by a clear 'Args' section listing parameters. Every sentence earns its place, with no redundant or vague language, making it easy to scan and understand.
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 3 parameters, no annotations, and an output schema (which reduces the need to describe return values), the description is moderately complete. It covers the purpose and parameters but lacks behavioral details like data sources, error handling, or usage context. This is adequate for a basic tool but has clear gaps in transparency.
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 description includes an 'Args' section that documents all 3 parameters with brief explanations and an example for 'brand_name'. Since schema description coverage is 0%, this adds substantial value beyond the bare schema. However, it doesn't detail formats (e.g., URL structure for 'site_url') or constraints (e.g., range for 'days'), keeping it from a perfect score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Split search performance into branded vs non-branded queries' and explains the benefit: 'Shows true organic SEO growth by separating brand searches.' It specifies the verb ('split'), resource ('search performance'), and scope ('branded vs non-branded'), but doesn't explicitly differentiate from sibling tools like 'get_search_analytics' or 'compare_search_periods' that might also handle search data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_search_analytics' or 'compare_search_periods' that might overlap in functionality, nor does it specify prerequisites or exclusions. The context is implied (SEO analysis) but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but lacks behavioral details. It mentions 'submit or resubmit' but doesn't disclose whether this requires authentication, has rate limits, affects indexing status, or what happens on success/failure. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose, followed by clear parameter explanations in a structured 'Args:' section. Every sentence earns its place with no wasted words, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 2 parameters with no schema descriptions, the description adequately explains parameter semantics, and an output schema exists (so return values needn't be described). However, as a mutation tool with no annotations, it lacks behavioral context like side effects or error handling, leaving gaps in completeness.
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 0%, but the description compensates by explaining both parameters: 'site_url' as the 'Exact GSC property URL' and 'sitemap_url' as the 'Full URL of the sitemap to submit'. This adds crucial meaning beyond the bare schema, though it doesn't cover format examples or validation rules.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('submit or resubmit') and target resource ('a sitemap to Google'), making the purpose unambiguous. It distinguishes from siblings like 'get_sitemaps' (read) and 'delete_sitemap' (remove), but doesn't explicitly differentiate from 'add_site' or other submission-related tools, keeping it at 4 rather than 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'batch_request_indexing' or 'request_indexing', nor any prerequisites (e.g., site verification in Google Search Console). The description implies usage for sitemap submission but offers no context about timing, frequency, or constraints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. While it mentions the tool provides 'advanced search analytics with sorting, filtering, and pagination,' it doesn't describe important behavioral aspects like rate limits, authentication requirements, data freshness (beyond the data_state parameter), error conditions, or response format. The description is functional but lacks operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear purpose statement followed by detailed parameter documentation. While comprehensive, it's appropriately sized for a tool with 14 parameters. The parameter documentation is organized but could be more front-loaded with critical usage information before the parameter details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (14 parameters) and the presence of an output schema, the description provides good coverage of the input parameters. However, with no annotations and a complex tool, it could benefit from more behavioral context about rate limits, authentication, and error handling. The parameter documentation is excellent, but operational guidance is lacking.
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?
The description provides extensive parameter documentation with 14 parameters, including examples (e.g., 'sc-domain:example.com'), format specifications ('YYYY-MM-DD'), value ranges ('up to 25000'), and enumeration options. With 0% schema description coverage, the description fully compensates by explaining every parameter's purpose, format, and constraints, adding significant value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'Get advanced search analytics with sorting, filtering (including regex), and pagination.' This specifies the verb ('Get'), resource ('advanced search analytics'), and key capabilities. However, it doesn't explicitly differentiate from its sibling 'get_search_analytics' tool, which appears to be a simpler version.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There's no mention of when this advanced version is preferable to the simpler 'get_search_analytics' sibling, nor any prerequisites or constraints beyond the parameter documentation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the action as 'Get,' implying a read operation, but doesn't specify if it requires authentication, has rate limits, or what the output format is. It mentions default values and limits (e.g., 'max: 500'), which adds some context, but lacks details on error handling or data freshness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized, with a clear purpose statement followed by a bulleted list of parameters. Each sentence earns its place by providing essential details. It could be slightly more front-loaded with usage context, but overall, it's efficient and organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 parameters, no annotations, but with an output schema), the description is reasonably complete. It covers all parameters in detail, which is crucial since the schema lacks descriptions. The output schema likely handles return values, so the description doesn't need to explain them. However, it could improve by adding behavioral context like authentication needs.
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?
The description adds significant meaning beyond the input schema, which has 0% description coverage. It explains each parameter's purpose: 'site_url' as the 'Exact GSC property URL,' 'days' as 'Number of days to look back,' 'dimensions' with examples, 'row_limit' with default and max, and 'search_type' with options. This compensates fully for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get search analytics data for a specific property.' It specifies the verb 'Get' and resource 'search analytics data,' making it distinct from siblings like 'get_advanced_search_analytics' or 'get_performance_overview.' However, it doesn't explicitly differentiate from 'get_search_by_page_query' or 'compare_search_periods,' which may also involve search analytics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose this over 'get_advanced_search_analytics' or 'get_search_by_page_query,' nor does it specify prerequisites or exclusions. The context is implied through parameter details but lacks explicit usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions 'live SEO audit' and 'small same-origin crawl', which implies real-time analysis and limited scope, but doesn't disclose behavioral traits like execution time, rate limits, authentication needs, or what 'live' entails (e.g., real-time vs cached data). The description adds some context but leaves significant gaps for a tool with multiple components.
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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by a concise list of components, and then parameter explanations. Every sentence earns its place with no wasted words, making it easy to scan and understand.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (combining multiple SEO functions) and the presence of an output schema (which handles return values), the description is fairly complete. It covers the purpose, key components, and parameter meanings. However, without annotations and with 0% schema coverage, it could benefit from more behavioral details (e.g., execution limits, data freshness) to fully guide the agent.
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 0%, so the description must compensate. It provides clear semantics for all three parameters: 'url' as the site/page URL, 'crawl_pages' as the number of pages to crawl for specific issues, and 'include_lighthouse' as a flag for an additional audit. This adds meaningful context beyond the bare schema, though it doesn't specify ranges or constraints for 'crawl_pages'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Run a live SEO audit' with specific components listed (page analysis, robots.txt inspection, sitemap discovery, PSI data, crawl). It distinguishes from siblings by emphasizing 'without requiring Search Console access' and combining multiple functions, though it doesn't explicitly differentiate from similar tools like 'site_audit' or 'crawl_site_seo'.
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 SEO auditing when Search Console access isn't available, but doesn't explicitly state when to use this tool versus alternatives like 'site_audit' or 'run_lighthouse_audit'. It mentions combining multiple functions, which suggests a comprehensive approach, but lacks clear exclusions or specific scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It mentions 'costs 1 API call each' for URL inspection, which is valuable behavioral context about resource usage. However, it doesn't disclose other critical traits like whether this is a read-only or destructive operation, authentication requirements, rate limits, or what the comprehensive audit entails beyond listed checks.
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?
Well-structured with purpose statement followed by parameter details. Every sentence earns its place by providing essential information. Could be slightly more front-loaded with key constraints, but efficiently conveys necessary information without waste.
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 3 parameters with 0% schema coverage and an output schema exists, the description does well by thoroughly explaining parameters and audit scope. It covers the main functionality adequately, though could benefit from more behavioral context given no annotations. The existence of an output schema means return values don't need description.
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 description coverage is 0%, so the description must compensate. It provides excellent parameter semantics: explains 'site_url' requires exact GSC property URL with an example, clarifies 'sitemap_url' is optional with auto-detection behavior, and specifies 'max_inspect' default value and API cost implication. This adds substantial meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('run', 'checks', 'inspects', 'identifies', 'reports') and resources ('site audit', 'sitemap health', 'URLs', 'coverage problems', 'findings'). It distinguishes from some siblings like 'analyze_page_seo' or 'crawl_site_seo' by emphasizing comprehensive auditing, but doesn't explicitly differentiate from 'audit_live_site' which might be similar.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for comprehensive site auditing, but provides no explicit guidance on when to use this tool versus alternatives like 'audit_live_site' or 'crawl_site_seo'. The parameter descriptions hint at context (e.g., 'auto-detects from GSC'), but no when-not scenarios or clear alternatives are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the destructive action ('Delete') but doesn't mention permission requirements, rate limits, confirmation prompts, or what happens after deletion (e.g., if it's reversible). For a destructive tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly front-loaded with the core purpose in the first sentence, followed by parameter explanations in a clean Args section. Every sentence earns its place with zero wasted words, making it highly scannable and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a destructive tool with no annotations but with an output schema (which handles return values), the description adequately covers purpose and parameters. However, it lacks important contextual details about permissions, consequences, and error conditions that would be expected for a deletion operation.
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 0%, so the description must compensate. It provides clear semantic meaning for both parameters ('Exact GSC property URL' and 'Full URL of the sitemap to delete'), adding value beyond the bare schema. However, it doesn't specify format examples or validation rules, keeping it from a perfect score.
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 specific action ('Delete (unsubmit)') and resource ('a sitemap from Google Search Console'), distinguishing it from sibling tools like 'submit_sitemap' and 'get_sitemaps'. It uses precise terminology that differentiates this destructive operation from read-only alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing to remove a sitemap from GSC, but doesn't explicitly state when to use this vs. alternatives like 'delete_site' or 'request_removal', nor does it mention prerequisites or exclusions. The context is clear but lacks explicit guidance on tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the core actions (deleting token and triggering auth flow) but omits critical details like side effects (e.g., interrupting other operations), user interaction requirements (browser flow), error handling, or rate limits. It adequately conveys the mutation nature but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise and front-loaded, using only two sentences that directly explain the tool's actions without any wasted words. Each sentence adds essential information about the sequence of operations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (authentication flow with potential side effects), no annotations, and an output schema (which covers return values), the description is minimally adequate. It explains what the tool does but lacks details on prerequisites, consequences, or integration with sibling tools, leaving gaps for an agent to infer usage.
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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately avoids discussing parameters, focusing instead on the tool's behavior, which aligns with the schema's emptiness.
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 specific action ('Perform a logout and new login sequence') and the resource involved ('current OAuth token'), distinguishing it from all sibling tools which focus on SEO analysis, site management, or indexing operations. It uses precise verbs ('Deletes', 'triggers') to define the tool's function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, prerequisites (e.g., when authentication fails), or exclusions. It lacks context about typical scenarios for reauthentication, making it unclear when an agent should invoke it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool detects keyword cannibalization and explains the negative effects, but lacks details on permissions, rate limits, output format, or whether it's a read-only or mutating operation. This leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose, followed by a concise explanation of the problem, and ends with a clear parameter list. Every sentence earns its place without redundancy, making it efficient and well-structured for quick comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 parameters, no annotations, but with an output schema), the description is reasonably complete. It explains the purpose and parameters adequately, and since an output schema exists, it doesn't need to detail return values. However, it could improve by addressing behavioral aspects like data sources or limitations.
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 0% schema description coverage, the description compensates by explaining all three parameters: 'site_url' (exact GSC property URL), 'days' (lookback period with default), and 'min_impressions' (minimum threshold with default). It adds meaningful context beyond the schema's basic titles, though it doesn't cover validation rules or examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('detect') and resource ('keyword cannibalization'), and explains what it identifies ('queries where multiple pages compete for the same keyword'). It distinguishes itself from siblings by focusing on keyword competition analysis, unlike tools for site management, auditing, or performance metrics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for identifying keyword conflicts that dilute ranking power, but does not explicitly state when to use this tool versus alternatives like 'analyze_page_seo' or 'find_striking_distance_keywords'. No exclusions or prerequisites are mentioned, leaving some ambiguity about its specific application context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses key behavioral traits: local execution, dependency requirements (Node.js, Chrome/Chromium), and CLI-based operation. However, it lacks details on output format, error handling, or performance characteristics, leaving gaps for an agent to understand full behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a purpose statement, prerequisites, and parameter explanations in bullet points. Every sentence adds value with no redundancy, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 parameters with 0% schema coverage and an output schema exists, the description provides good context for usage and parameters. It covers prerequisites and parameter meanings adequately, though it could mention the output schema's role. For a local audit tool, this is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds meaningful semantics for all 3 parameters: url as 'Full page URL', form_factor as 'mobile or desktop', and categories as 'Comma-separated Lighthouse categories'. This provides clear usage context beyond the bare schema, though it could specify category options or URL format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool runs a Lighthouse CLI audit via npx, specifying it's a local audit. It distinguishes from sibling tools like 'audit_live_site' by emphasizing the local execution requirement. However, it doesn't explicitly contrast with all SEO/analytics siblings, keeping it at 4 rather than 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool: for local Lighthouse audits requiring Node.js and Chrome/Chromium. It implicitly distinguishes from 'audit_live_site' (likely remote) but doesn't explicitly name alternatives or state when not to use it, missing full explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool's purpose and constraints (structured data requirements), but lacks details on permissions needed, rate limits, whether the removal is permanent or reversible, or what the output contains. It adds some context but leaves key behavioral traits unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose, followed by important constraints and parameter details in a structured format. Every sentence adds value without redundancy, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a removal request with specific constraints), no annotations, and an output schema (which handles return values), the description is mostly complete. It covers purpose, usage context, and parameters, but could improve by addressing behavioral aspects like authentication needs or error handling.
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 schema description coverage is 0%, so the description must compensate. It explains the single parameter ('url: The full URL to request removal for'), adding meaning beyond the schema's basic type definition. However, it doesn't specify URL format requirements or validation rules, leaving some semantic gaps.
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 specific action ('request Google to remove a URL from the index') and resource ('via the Indexing API'), distinguishing it from siblings like 'request_indexing' (which likely adds URLs) and 'delete_site' (which removes entire sites). The mention of structured data requirements further clarifies its specialized purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit context on when to use this tool ('Only works for pages with JobPosting or BroadcastEvent structured data'), which helps differentiate it from general removal tools. However, it doesn't specify when NOT to use it or name direct alternatives among siblings, such as 'delete_site' for broader actions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It explains what the tool does (finds keywords in positions 5-20 with decent impressions) and the optimization context, but doesn't mention behavioral aspects like rate limits, authentication requirements, data freshness, or what happens when limits are exceeded. It doesn't contradict annotations (none exist).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with a clear purpose statement followed by a well-organized parameter explanation. Every sentence earns its place, and it's appropriately sized for a tool with 4 parameters. The information is front-loaded with the core purpose first.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (4 parameters, no annotations, but with an output schema), the description is reasonably complete. It explains the tool's purpose, usage context, and parameter meanings. Since an output schema exists, it doesn't need to explain return values. However, it could benefit from mentioning data sources (Google Search Console) or typical use cases.
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?
The description adds significant semantic value beyond the input schema, which has 0% description coverage. It explains what each parameter means: 'site_url' as the exact GSC property URL, 'days' as days to look back, 'min_impressions' as minimum impressions to include, and 'row_limit' as max results. This compensates fully for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: finding 'striking distance' keywords (queries ranking at positions 5-20 with decent impressions) for quick-win optimization targets. It specifies the exact resource (keywords/queries) and distinguishes from siblings by focusing on a specific ranking range rather than general analytics or other SEO functions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool: for identifying optimization targets that could reach page 1 with small improvements. However, it doesn't explicitly state when not to use it or name specific alternatives among the sibling tools (e.g., get_search_analytics for broader keyword analysis).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and adds valuable behavioral context: it discloses that the API is free and requires no OAuth (addressing auth needs), specifies the need for a CRUX_API_KEY environment variable (setup requirement), and implies read-only behavior by using 'Get'. It does not mention rate limits or error handling, but covers key operational aspects beyond basic functionality.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the core purpose, followed by concise operational details and parameter explanations. Every sentence adds value without redundancy, making it efficient and easy to parse for an AI agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 parameters, no annotations, but with an output schema), the description is mostly complete: it covers purpose, behavioral traits, and parameter semantics. Since an output schema exists, it need not explain return values. However, it lacks details on error conditions or usage limits, which could enhance completeness for a data-fetching 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?
The schema description coverage is 0%, so the description must compensate. It adds meaning by explaining 'url_or_origin' accepts full URLs or origins with an example, and 'form_factor' specifies allowed values (PHONE, DESKTOP, TABLET) and a default, which clarifies usage beyond the schema's basic types. However, it does not detail format constraints or edge cases for parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Get Core Web Vitals') and resource ('from the Chrome UX Report (CrUX) API'), including the exact metrics (LCP, INP, CLS). It distinguishes itself from siblings like 'get_pagespeed_insights' or 'get_performance_overview' by specifying the CrUX API source and metrics, avoiding tautology with the tool name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool by mentioning it's for retrieving Core Web Vitals from CrUX, which implies usage for performance monitoring. However, it does not explicitly state when not to use it or name alternatives among siblings (e.g., 'get_pagespeed_insights' for different metrics), leaving some guidance gaps.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does well by disclosing key behavioral traits: it's a write operation (implied by 'Request'), has content-type restrictions ('Only works for pages with JobPosting or BroadcastEvent structured data'), and includes rate limit information ('Default quota: 200 requests/day'). It doesn't cover error handling or authentication needs, but provides substantial context beyond basic functionality.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly front-loaded with the core purpose, followed by important constraints and parameter details in just three sentences. Every sentence earns its place with essential information, and there's zero wasted text.
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 an output schema (which handles return values), no annotations, and minimal parameters, the description provides excellent coverage of the tool's purpose, constraints, and parameter meaning. It could potentially mention authentication requirements or error scenarios, but for a single-parameter tool with output schema, it's quite complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and only 1 parameter, the description adds crucial meaning by specifying that the 'url' parameter should be 'The full URL to request indexing for', which clarifies the expected format beyond what the bare schema provides. This fully compensates for the schema's lack of documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Request Google to crawl and index a URL') and resource ('via the Indexing API'), distinguishing it from siblings like 'request_removal' or 'batch_request_indexing' by focusing on individual URL indexing requests rather than batch operations or removal requests.
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 on when to use it ('Only works for pages with JobPosting or BroadcastEvent structured data'), which helps differentiate from alternatives like 'submit_sitemap' or 'batch_request_indexing'. However, it doesn't explicitly state when NOT to use it or compare directly with all sibling 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behavioral traits: 'Processes sequentially with rate limiting,' 'Default quota: 200/day,' and the constraint on page types. However, it lacks details on error handling, response format, or confirmation of indexing success, leaving some gaps in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the first sentence stating the core purpose and key behavioral traits. The second sentence adds quota and constraints, and the 'Args' section efficiently documents parameters. Every sentence adds value without redundancy, making it concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (batch processing with constraints), no annotations, and an output schema present, the description is mostly complete. It covers purpose, usage, behavior, and parameters effectively. However, it could benefit from mentioning the output schema's role or a brief note on what to expect in the response, slightly reducing completeness.
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 has 0% description coverage, so the description must compensate. It adds meaningful semantics: 'urls: List of URLs to index, one per line (max 100 per batch).' This clarifies the format (list, one per line) and constraint (max 100), which are not evident from the schema alone. However, it doesn't specify URL validation rules or examples, slightly limiting completeness.
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 specific action ('Request indexing for multiple URLs') and resource ('URLs'), distinguishing it from the sibling 'request_indexing' tool which presumably handles single URLs. It also specifies the scope ('multiple URLs') and constraints ('pages with JobPosting or BroadcastEvent structured data'), making the purpose highly specific and differentiated.
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: 'Only for pages with JobPosting or BroadcastEvent structured data.' It also implies an alternative by distinguishing it from 'request_indexing' (for single URLs) and sets clear constraints like 'max 100 per batch' and 'Default quota: 200/day,' helping users decide when to use it versus other options.
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 provided, the description carries full burden and excels by disclosing critical behavioral traits: automatic rate limiting handling, specific API limits (2000/day, 600/minute), and per-call limit (50 URLs). These are essential operational details not inferable from the input schema alone.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly structured and concise: purpose statement first, behavioral details second, parameter explanations third. Every sentence earns its place with zero waste, and it's appropriately sized for a 2-parameter tool with complex behavior.
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 (batch operations with rate limits), no annotations, and the presence of an output schema (which handles return values), the description is complete. It covers purpose, behavioral constraints, and parameter semantics sufficiently for an agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates well by explaining both parameters: 'site_url' as 'Exact GSC property URL' with an example, and 'urls' as 'List of URLs to inspect, one per line'. This adds crucial semantic context beyond the bare schema types.
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 specific action ('Inspect multiple URLs for indexing status') and resource ('URLs'), distinguishing it from sibling tools like 'inspect_url' (singular) and 'batch_request_indexing' (different action). It precisely defines scope with 'multiple URLs' and 'indexing status'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool (batch inspection of URLs for indexing status) and implicitly differentiates from 'inspect_url' by handling multiple URLs. However, it doesn't explicitly state when NOT to use it or name specific alternatives beyond what's implied by the sibling list.
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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