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

No annotations provided, and the description does not disclose behavioral traits such as rate limits, data source, or effects of the analysis. For a tool with no annotations, the description bears full responsibility but fails to convey safety or side effects.

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

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

The description is one sentence, which is concise, but lacks structure and fails to provide any additional details beyond the basic purpose. It earns its place but could be expanded without losing 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?

Despite having an output schema, the description omits context about what the analysis returns (e.g., density percentages, TF-IDF scores). For a tool with two parameters and a likely rich output, the description is insufficient.

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 coverage is 0%, so the description must add meaning. It mentions keyword density and TF-IDF, hinting at the parameters' roles, but does not explain how 'url' and 'target_keyword' are used together or what 'target_keyword' specifically affects.

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?

Description clearly states the tool analyzes keyword density and TF-IDF metrics, providing a specific verb+resource. It distinguishes from sibling tools like check_difficulty or onpage_audit, which focus on other aspects, though not explicitly mentioned.

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 on when to use this tool versus alternatives like analyze_page_speed or keyword_ideas. The description lacks context on appropriate scenarios or exclusions.

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 partially discloses behavior by noting the GOOGLE_PSI_API_KEY requirement, which implies external API dependency. However, it omits other traits like rate limits, latency, potential errors, or whether the tool is read-only.

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 two concise sentences, front-loaded with the core purpose. The second sentence adds a critical prerequisite without excess. 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?

Given the tool's simplicity (2 params, output schema available), the description covers the essential purpose and a key dependency. It does not mention the return format (covered by schema) but could briefly note that it measures performance metrics. Still, it's adequate for a straightforward tool.

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 already covers both parameters (url, strategy) with descriptions and defaults (100% coverage). The description adds no additional meaning beyond the schema, meeting the baseline but not elevating it.

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: 'Analyzes site speed using Google PageSpeed Insights.' It specifies a concrete verb ('Analyzes') and a distinct resource ('site speed'), differentiating it from sibling tools like check_broken_links_on_page or keyword_ideas.

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 lacks guidance on when to use this tool versus its siblings. It only mentions a prerequisite (API key), but no comparisons or exclusions. The agent is left to infer usage context without explicit direction.

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, the description must fully disclose behavior. It only hints at time cost via the 'limit' parameter description, but does not state read-only vs destructive, required permissions, or potential sitemap dependencies. Significant gaps remain.

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

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

Two sentences that front-load the core purpose and a use case. Every sentence adds value with no redundancy or fluff.

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 an output schema exists, return values need not be explained. However, the description assumes automatic sitemap discovery without detailing this process or error conditions. Still adequately covers the main workflow.

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 descriptions (100% coverage) already explain both parameters clearly. The tool description adds no new semantic value beyond what the schema provides, so baseline 3 is appropriate.

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

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

The description clearly states the tool scans a sitemap and runs an On-Page audit on multiple pages, with an example of site-wide issues like missing H1s. This distinguishes it from siblings like 'onpage_audit' which is for single pages.

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?

It provides context for when to use ('finding site-wide issues'), but does not explicitly mention when not to use or point to alternatives. The guidance is clear but lacks exclusions.

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 full burden. It specifies it scans for 404s, which is transparent about the type of broken link. However, it does not disclose other behavioral traits like handling of redirects, timeouts, or whether it scans all links on the page.

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 sentence, front-loaded with the core action. It is concise but could be slightly more informative without adding fluff.

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?

The description is very brief and does not mention the output schema (which exists but is not shown). It lacks details on return values, error handling, or scope of scanning. For a simple tool, this may be sufficient, but given the lack of annotations, more completeness would be beneficial.

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 0%, and the description fails to explain either parameter. 'url' is obvious, but 'limit' (default 20) is not clarified. The description adds no value beyond the schema's structure.

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 it scans a page for broken links (404s), using a specific verb and resource. It distinguishes itself from sibling tools like 'onpage_audit' or 'technical_health_check' by focusing solely on broken links.

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?

Usage is implied by the purpose: use to find broken links on a page. There is no explicit guidance on when to use it versus alternatives, nor any exclusions or prerequisites. The description is adequate but lacks usage context.

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 full burden. It only mentions the API key requirement but does not disclose read-only nature, rate limits, or what 'SERP analysis' entails. 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.

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

The description is a single sentence that efficiently conveys the core purpose and a key requirement. It is front-loaded and concise, though it could be slightly reorganized to separate behavioral info from purpose.

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?

With no annotations and missing usage guidelines, the description is not fully complete. It covers the basics but lacks details on when to use, behavioral traits, and potential limitations. The presence of an output schema mitigates the need to describe returns.

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% coverage, describing both parameters (keyword and country). The description adds no additional meaning beyond the schema, so baseline 3 is appropriate.

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

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

The description clearly states the tool checks keyword difficulty and returns SERP analysis, using a specific verb and resource. It distinguishes from sibling tools like keyword_ideas or onpage_audit by focusing on difficulty and SERP data.

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 mentions a prerequisite (CAPSOLVER_API_KEY) but does not specify when to use this tool versus alternatives like keyword_ideas or onpage_audit. There is no guidance on when not to use it or context for selection 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?

No annotations are provided, so the description must carry the full burden. It only states the action without disclosing what validation entails (e.g., syntax checking, completeness), or what the output looks like. Minimal behavioral context.

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

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

The description is very concise—one sentence—and front-loaded with the essential purpose. However, it could be slightly more informative without losing 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?

The tool has an output schema but the description gives no indication of what the validation result contains (e.g., errors, warnings). For a validation tool, this is a significant gap in completeness.

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 0%, and the description adds no meaning beyond the parameter name 'url'. It does not specify expected format or constraints, failing to compensate for the missing schema descriptions.

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 it validates JSON-LD Schema Markup on a page, specifying both the action and resource. It is distinct from sibling tools like analyze_content_density or check_broken_links_on_page.

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 implies usage when one wants to validate JSON-LD schema markup, but provides no explicit guidance on when to use versus alternatives, prerequisites, or exclusions.

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 burden. It discloses the API key requirement, which is a behavioral constraint, but does not state whether the tool is read-only, has rate limits, or other side effects. For a comparison tool, it likely does not modify data, but this is not explicit.

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

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

The description is two sentences with no unnecessary words. It front-loads the purpose and then adds a prerequisite. Every sentence 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?

Given the low complexity (2 parameters) and the presence of an output schema (not shown), the description covers the essential purpose and a prerequisite. It lacks usage guidelines but is otherwise complete for a simple comparison tool.

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 0%, so the description must add meaning. It clarifies that 'my_domain' and 'competitor_domain' are domains and that the output includes Backlinks, Traffic, DR. However, it doesn't specify domain format or provide examples, leaving some ambiguity.

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 compares SEO metrics (Backlinks, Traffic, DR) of two domains. The verb 'compares' and resource 'SEO metrics' are specific, and the listed metrics distinguish it from sibling tools like 'get_backlinks' or 'estimate_traffic'.

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 mentions the prerequisite 'Requires CAPSOLVER_API_KEY' but provides no guidance on when to use this tool versus alternatives, such as 'get_backlinks' or 'estimate_traffic'. No exclusions or context for selection.

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

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

No annotations are provided, so the description bears full burden. It only mentions the API key requirement but does not disclose whether the tool is read-only, has rate limits, or requires specific permissions. Behavioral aspects are mostly absent.

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 concise sentence that front-loads the tool's purpose. No unnecessary words, and the API key note is integrated naturally.

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?

An output schema exists, so return values are covered. The description is minimal but sufficient for a straightforward estimation tool. It could mention that country filtering is optional, but schema handles that. Slight lack of depth on behavior keeps it from 5.

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 coverage is 100%, so the input schema already documents both parameters (domain and country). The description adds no additional meaning beyond what is in the schema. Baseline 3 is appropriate.

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 estimates monthly search traffic and value for a domain, using a specific verb ('Estimates') and resource ('domain'). It also mentions the required API key, which adds necessary context. It is distinct from sibling tools like 'keyword_ideas' which estimate traffic at keyword level.

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?

There is no guidance on when to use this tool versus alternatives (e.g., 'check_difficulty' or 'keyword_ideas'). The description only notes the API key requirement but does not provide context on appropriate use cases or exclusions.

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

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

No annotations provided, so description carries full burden. It mentions the report is saved locally but lacks details on side effects (e.g., file overwrite, temporary files) or resource implications (e.g., CapSolver costs). Minimal behavioral disclosure beyond what's in the schema.

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?

Two sentences front-loaded with purpose and data sources. No redundant 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?

Output schema exists, so return values are defined. Description covers the key functionality but could elaborate on file naming, location, and whether the report is reusable. Still reasonably complete for a report generation tool.

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 covers both parameters with descriptions. Tool description adds context about combining data types but does not provide additional semantic value beyond what the schema already conveys. Baseline score is appropriate.

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?

Description clearly states it generates a full SEO audit report in Markdown, combining On-Page, Technical, and Ahrefs data. This distinguishes it from sibling tools that focus on specific aspects (e.g., onpage_audit, technical_health_check).

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?

Description implies use for a comprehensive audit but does not explicitly state when to use this tool versus alternatives. No guidance on when not to use or prerequisites.

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, the description carries the full burden. It discloses that the tool uses Ahrefs and requires an API key, and specifies return values. This adds behavioral context beyond a simple read operation. However, it does not mention rate limits, pagination, or error handling, which would make it more complete.

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 two concise sentences with no redundancy. The first sentence immediately states the tool's action and resource, efficiently front-loading the purpose.

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 one parameter and an output schema, the description adequately covers what the tool does, its prerequisite, and what it returns. No missing critical information for agent 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?

Schema description coverage is 100% (domain parameter already described). The description does not add new semantics beyond what the schema provides, so baseline score 3 is appropriate.

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 uses specific verb 'Retrieves' and resource 'backlink data for a domain', clearly distinguishing it from siblings like 'check_broken_links_on_page' or 'analyze_page_speed'. It also specifies the data returned: domain rating, total backlinks, and top referring pages.

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 mentions a prerequisite (CAPSOLVER_API_KEY) indicating when the tool can be used, but lacks explicit guidance on when to use this tool vs alternatives like 'keyword_ideas' or 'compare_competitors'. Usage context is implied by the tool's purpose 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.

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

Without annotations, the description partially discloses behavior by noting the API key requirement. However, it omits details like rate limits, data sourcing, or whether modifications occur. It does not contradict any annotations.

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 concise sentence, front-left, with no redundant information. Every word adds value.

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 output schema exists, the description adequately covers the tool's purpose and key requirement (API key). Minor gaps like output scope or constraints (e.g., keyword length) are not critical for a simple tool.

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 coverage is 100% with both parameters described. The description only mentions 'seed keyword,' adding no new meaning beyond the schema for the country parameter. Baseline score applied.

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 it generates keyword ideas and questions from a seed keyword, using a specific verb ('generates') and output type. It differentiates from sibling tools which focus on SEO analysis rather than keyword generation.

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 implies usage for keyword brainstorming but provides no explicit context on when to use versus alternatives or any prerequisites beyond the API key. No guidance on when not to use.

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

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

No annotations are provided, and the description only discloses that no API key is required. It does not mention side effects, rate limits, destructive potential, or other behavioral traits, leaving the agent with minimal understanding of the tool's impact.

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 with two sentences, no unnecessary words, and front-loads the core action. Every sentence adds value.

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 presence of an output schema (so return values need not be described), the description adequately covers what the tool does and its input. It is complete enough for the agent to select and invoke the tool correctly, though it could hint at optional parameters or results.

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 schema already fully describes the url parameter. The description adds an example (e.g., 'https://example.com/blog/post-1') but does not provide additional semantic meaning beyond what the schema offers.

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 a detailed on-page SEO audit of a specific URL, listing specific checks (meta tags, heading structure, etc.), which distinguishes it from sibling tools that focus on narrower aspects like content density or schema markup.

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 mentions it does not require an API key, which is helpful, but does not provide explicit guidance on when to use this tool versus alternatives like analyze_content_density or check_schema_markup. Usage context is implied but not differentiated.

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 burden of behavioral disclosure. It states it checks robots.txt, sitemap, and headers, but does not mention rate limits, destructiveness, or side effects. It is implied to be read-only, but this is not explicit.

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

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

The description is two sentences, front-loaded with the main purpose, and every sentence adds value. There is no unnecessary 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 tool's low complexity (one parameter) and the presence of an output schema, the description adequately covers the scope. It lists what is checked, though it could briefly mention the output format, but that is handled by the output schema.

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 covers the single parameter 'url' with 100% description coverage. The tool description adds context about what the URL is used for (to check technical SEO aspects), but does not add meaning beyond what the schema already provides. Baseline 3 is appropriate.

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 it 'checks technical SEO aspects' and lists specific items (robots.txt, sitemap.xml, security headers). The verb 'checks' and resource 'technical SEO aspects' are specific, and the tool distinguishes itself from siblings like check_schema_markup or check_broken_links by focusing on infrastructure checks.

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 mentions it does not require an API key, which is useful context, but it does not explicitly state when to use this tool versus alternatives like onpage_audit or check_schema_markup. Usage is implied from the purpose, but no exclusions or scenarios are provided.

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