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 'detects' opportunities but doesn't explain what the output looks like (e.g., list of URLs with metrics, recommendations), whether it performs analysis or just filters data, or any limitations (e.g., data freshness, processing time). The description is too vague about the tool's actual behavior beyond the high-level purpose.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized for a tool with a clear, focused function and doesn't waste space repeating information available in the schema. The structure is front-loaded with the core functionality.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 9 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what constitutes a 'quick win' (beyond what parameters imply), what format the results take, or how the detection algorithm works. The agent must rely entirely on the parameter schema to understand the tool's operation, which is insufficient for proper tool selection and invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, providing clear documentation for all 9 parameters including defaults and examples. The description adds no parameter-specific information beyond what's already in the schema. According to scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no param info in the description, which applies here.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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 'Automatically detect SEO quick wins and optimization opportunities' which specifies the action (detect) and target domain (SEO opportunities). It distinguishes itself from sibling tools like 'search_analytics' or 'enhanced_search_analytics' by focusing specifically on 'quick wins' rather than general analytics. However, it doesn't explicitly differentiate from all siblings (e.g., 'index_inspect' might also find optimization opportunities).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 prerequisites (e.g., requiring Search Console data access), when this tool is preferred over 'search_analytics' or 'enhanced_search_analytics', or any exclusions (e.g., not for technical SEO audits). The agent must infer usage from the tool name and parameters alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 insight. It mentions 'enhanced performance' and 'quick wins detection' but doesn't clarify what 'enhanced' means operationally, whether this is a read-only or mutating operation, potential rate limits, or what 'quick wins' entails in practice. The description lacks critical behavioral context for a complex tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise—a single sentence that efficiently lists key features without redundancy. It's front-loaded with the core purpose and doesn't waste words, 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.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex tool with 15 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what the tool returns, how 'quick wins' are presented, or the operational implications of 'enhanced' features. The agent lacks sufficient context to understand the tool's full behavior and output.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so parameters are well-documented in the schema itself. The description adds marginal value by hinting at 'regex filters' and 'quick wins detection' which correspond to specific parameters, but doesn't provide additional semantic context beyond what's already in the schema descriptions. Baseline 3 is appropriate given high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs 'enhanced search analytics' with specific capabilities (up to 25,000 rows, regex filters, quick wins detection). It distinguishes from the simpler 'search_analytics' sibling by highlighting enhanced features, though it doesn't explicitly contrast with 'detect_quick_wins' which might overlap in functionality.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like 'search_analytics' or 'detect_quick_wins'. The description mentions capabilities but doesn't specify use cases, prerequisites, or exclusions that would help an agent choose appropriately among siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 what the tool does but fails to mention critical aspects like whether this is a read-only operation, if it requires authentication, rate limits, error handling, or what the output format looks like. This leaves significant gaps for an agent to understand how to interact with it safely and effectively.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, direct sentence that efficiently conveys the core purpose without any unnecessary words. It is front-loaded and wastes no space, 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.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of interacting with Google Search Console (which likely involves authentication and specific data structures), the description is insufficient. With no annotations, no output schema, and minimal behavioral context, it doesn't provide enough information for an agent to use this tool confidently in a real-world scenario.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with clear descriptions for both parameters ('feedpath' and 'siteUrl'), including examples. The description adds no additional parameter semantics beyond what the schema already provides, so it meets the baseline score of 3 for adequate but not enhanced coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Get') and resource ('a sitemap for a site in Google Search Console'), making the purpose immediately understandable. However, it doesn't distinguish this tool from sibling tools like 'list_sitemaps' or 'index_inspect', which might offer related 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.

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_sitemaps' or 'submit_sitemap'. It lacks context about prerequisites, such as whether the site must be verified in Google Search Console, or any exclusions for usage scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 action ('inspect') and outcome ('see if it is indexed or can be indexed'), but lacks details on permissions, rate limits, response format, or error handling. For a tool with no annotations, this is insufficient to fully inform an agent about 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence that directly states the tool's purpose without any fluff. It's front-loaded and efficiently communicates the core function, making it easy for an agent to parse quickly. Every word earns its place, achieving optimal conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (3 parameters, no output schema, no annotations), the description is incomplete. It doesn't cover behavioral aspects like what 'indexed' means in practice, how results are returned, or error scenarios. Without annotations or an output schema, the description should provide more context to be fully helpful for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, so the schema already documents all parameters thoroughly. The description adds no additional meaning beyond what's in the schema, such as explaining relationships between 'siteUrl' and 'inspectionUrl' or practical use cases. With high schema coverage, the baseline is 3, as the description doesn't compensate but doesn't detract either.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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 to see if it is indexed or can be indexed.' It specifies the verb ('inspect') and resource ('URL') with a clear outcome. However, it doesn't explicitly differentiate from sibling tools like 'detect_quick_wins' or 'enhanced_search_analytics', which might also involve URL analysis, so it doesn't reach a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 or contexts where this inspection is preferred over other methods, such as 'detect_quick_wins' for broader analysis or 'submit_sitemap' for indexing actions. This lack of comparative context limits its utility for an agent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 ('List sitemaps') but doesn't describe key behaviors such as whether this is a read-only operation, what the output format looks like, if there are pagination or rate limits, or any authentication requirements. This leaves significant gaps for an agent to understand how to handle the tool effectively.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence that directly states the tool's purpose without any unnecessary words. It is front-loaded and efficient, making it easy for an agent to parse quickly. Every part of the description earns its place by conveying essential information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of a tool with 2 parameters, no annotations, and no output schema, the description is incomplete. It doesn't address behavioral aspects like output format, error handling, or usage context, which are crucial for an agent to invoke the tool correctly. The description alone is insufficient for full understanding without additional structured data.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, meaning the input schema already documents both parameters ('sitemapIndex' and 'siteUrl') with descriptions and examples. The description adds no additional meaning or context about these parameters beyond what's in the schema, so it meets the baseline score of 3 without compensating for any gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('List') and resource ('sitemaps for a site in Google Search Console'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'get_sitemap' or 'submit_sitemap', which also deal with sitemaps in the same domain, 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.

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 explain how 'list_sitemaps' differs from 'get_sitemap' (which might retrieve a specific sitemap) or when to use it over other sibling tools like 'list_sites'. There's no mention of prerequisites or context for usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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. While 'List all sites' implies a read-only operation, it doesn't specify authentication requirements, rate limits, pagination behavior, or what 'all sites' means in practice (e.g., all sites the authenticated user has access to).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that communicates the essential purpose without any wasted words. It's appropriately sized for a simple list operation and front-loads the key information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter list operation with no output schema, the description is minimally adequate. However, without annotations and with multiple sibling tools, it should ideally provide more context about when this tool is appropriate versus alternatives and what the output format looks like.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, and the schema already fully documents this.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('List') and resource ('sites in Google Search Console'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'list_sitemaps' or 'get_sitemap', which would require more specific scope definition.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 sibling tools like 'list_sitemaps' and 'get_sitemap' available, there's no indication of when a user would need to list sites versus sitemaps, or whether this should be used before other operations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 but offers minimal information. It states this is a 'Get' operation (implying read-only) but doesn't mention authentication requirements, rate limits, data freshness, pagination behavior, or error conditions. For a 13-parameter tool with complex filtering options, this is inadequate behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that immediately communicates the core purpose without unnecessary words. It's appropriately sized for a tool with comprehensive schema documentation and follows the principle of front-loading essential information. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex tool with 13 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what 'search performance data' includes (clicks, impressions, CTR, position), doesn't mention data aggregation or formatting, and provides no context about the Google Search Console API limitations or typical use cases. The agent would struggle to use this tool effectively without additional context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, meaning all parameters are well-documented in the schema itself. The description adds no additional parameter semantics beyond the generic 'search performance data' context. This meets the baseline expectation when schema coverage is complete, but the description doesn't enhance understanding of how parameters interact or typical usage patterns.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Get') and resource ('search performance data from Google Search Console'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'enhanced_search_analytics', which appears to be a related alternative. The description is specific but lacks sibling distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 'enhanced_search_analytics' or other siblings. There's no mention of prerequisites, appropriate contexts, or limitations. The agent receives no help in choosing between this and similar tools on the server.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. 'Submit' implies a mutation/write operation, but it doesn't disclose behavioral traits such as required permissions, whether it's idempotent, error handling, or rate limits. This leaves significant gaps for a tool that likely modifies data.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without any fluff or redundancy. It's appropriately sized and front-loaded, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of a mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral aspects like side effects, return values, or error conditions, which are crucial for safe and effective use in an AI agent context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the input schema fully documents both parameters. The description doesn't add any meaning beyond what the schema provides, such as explaining relationships between parameters or additional constraints. Baseline 3 is appropriate when the schema handles the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('submit') and resource ('sitemap for a site in Google Search Console'), making the purpose immediately understandable. It doesn't explicitly distinguish from siblings like 'list_sitemaps' or 'get_sitemap', but the verb 'submit' implies a write operation versus their likely read operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 'list_sitemaps' or 'get_sitemap', nor are there any prerequisites or exclusions mentioned. The description only states what it does without context for selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.