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

No annotations provided, and the description lacks behavioral disclosure. It does not mention read-only nature, rate limits, authentication needs, or what the output entails. The existence of an output schema is not leveraged.

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?

Extremely concise: two sentences that are front-loaded with the main purpose, followed by a valuable note about being free. No superfluous words.

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 (1 param, no annotations, output schema exists), the description is minimally adequate. It covers the core action but omits details about what 'common issues' are or expected output format.

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?

Single parameter 'url' with 0% schema description coverage. The description adds no semantic meaning beyond the parameter name—no format, examples, or constraints. The description should compensate but does not.

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

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

Description clearly states the verb (Analyze), resource (URL), and purpose (SEO-friendliness). It specifies what it checks (length, structure, common issues), distinguishing it from sibling tools like onpage_analysis which is more comprehensive.

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 siblings. The only hint is 'Free tool - no API key or credits required,' which is not a usage guideline but a pricing note. No context for when to choose this over other SEO analysis tools.

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?

The description discloses the cost (20 credits) and required API key, but with no annotations, it lacks other behavioral traits like rate limits, side effects, or safety. It does not explicitly state if it's 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?

Two concise sentences covering purpose and prerequisites, with no wasted words. The essential information is front-loaded.

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 single parameter and presence of an output schema, the description covers core functionality and credit cost. However, it omits prerequisites like sitemap accessibility or handling of missing sitemaps.

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 only parameter 'domain' has no description in the schema (0% coverage), and the tool description does not clarify the expected format (e.g., with/without protocol, path to sitemap). This leaves ambiguity for the agent.

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 audits an XML sitemap, listing specific checks (total URLs, duplicates, broken links, lastmod coverage). However, it does not differentiate from sibling tools like crawl_website or check_links that might overlap.

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 vs alternatives. It only mentions an API key requirement and checking balance via get_account_info, but does not specify when the sitemap audit is appropriate 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 full burden. It discloses credit cost (10 credits) and the requirement for VISIBLYAI_API_KEY, plus hints to check balance via get_account_info. However, it does not describe error handling, response format, or side effects beyond validation.

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, front-loading the main purpose and then adding essential behavioral info (credits, API key). Every sentence earns its place with no redundancy.

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 simple tool (one parameter, output schema exists), the description covers the core functionality, cost, and prerequisites. It could be slightly improved by adding context about what constitutes a 'valid' hreflang, but overall it is sufficient for the agent to understand the tool's role.

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

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

Schema coverage for the single parameter 'url' is 0%, and the description does not add any meaning about the parameter (e.g., expected format, whether it must be absolute, etc.). The tool's name implies it's a URL but nothing beyond the schema's minimal 'type: string' and 'required'.

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 validates hreflang annotations and lists specific aspects (x-default, language codes, broken targets, bidirectional linking). It distinguishes from sibling tools like check_links and analyze_url_structure which focus on different aspects.

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 implicitly suggests usage when validating hreflang tags but does not provide explicit when-to-use or when-not-to-use guidance, nor does it compare with alternatives. The name alone implies context but lacks 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?

No annotations provided, so description carries full burden. It mentions credits and API key but lacks details on how links are checked (e.g., depth, follow redirects), rate limits, or error handling. Major behavioral aspects are undisclosed.

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?

Very concise: two core sentences plus a line about credits. No redundant words, but 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.

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

Output schema exists to explain return values. Description covers auth and cost but lacks info on scope (e.g., max links, timeouts, redirect following). Adequate for a simple tool but not fully comprehensive.

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 description must add value. It implies 'url' is the page to check, but provides no additional format, constraints, or examples beyond the schema.

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 checks all links on a page for broken/redirect status. This verb+resource combination is specific and distinct from sibling tools like analyze_url_structure or audit_sitemap.

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?

Mentions credits cost and API key requirement, and suggests using get_account_info for balance check. However, it does not explicitly differentiate from sibling tools like onpage_analysis or crawl_website that may also check links.

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 bears full responsibility. It discloses credit consumption and API key requirement, and lists return metrics. However, it doesn't mention if the tool is read-only, rate limits, error handling, or destructive behavior. Basic transparency is present but gaps remain.

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

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

The description is brief (two sentences) and front-loaded with the core functionality. It is concise without unnecessary detail. However, it could be improved by structuring the parameter information and listing the return values more systematically.

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 no annotations but an output schema exists, the description covers main return values and credit cost. However, it lacks detail on parameter usage, error scenarios, and integration context. For a tool with only two parameters and a clear purpose, this is barely adequate.

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 compensate. It does not mention either parameter ('url' or 'strategy') and provides no guidance on their values or defaults. The default for 'strategy' (mobile) is not indicated. This fails to add meaning beyond the schema 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 the tool checks PageSpeed and Core Web Vitals, listing specific metrics (performance, accessibility, SEO scores, LCP, CLS, TBT, optimization opportunities). The verb 'Check' and resource 'PageSpeed' are specific, and the purpose is well-differentiated from sibling tools by its focus on page speed metrics.

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 context like credit cost and required API key, and suggests using 'get_account_info' to check balance. However, it gives no explicit guidance on when to use this tool versus alternatives, nor does it mention when not to use it.

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

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

No annotations provided, so description carries full burden. Mentions credits (15) and implies read-only operation via 'live Google SERP check', but lacks details on side effects, auth requirements, or rate limits.

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

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

Two clear paragraphs: first states purpose, second lists use cases and credits. Efficient but could be more structured with parameter descriptions.

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 not needed. Description covers key output aspects (ranks, content types, features). Lacks handling of edge cases like empty 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 coverage is 0% and description does not explain any parameters (keyword, location, language, depth). No value added beyond the schema 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 the tool checks live Google SERP for a keyword and specifies what information is provided (who ranks, content types, SERP features). It is specific and distinct from sibling tools like get_keywords or classify_keywords.

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?

Explicitly lists use cases: competitive analysis, content gap detection, SERP intent analysis. However, no guidance on when not to use or alternatives 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 carries the full burden. It only mentions credit cost and API key requirement, but fails to disclose behavioral traits like whether it is read-only, destructive, or has rate limits.

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

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

The description is concise with two sentences, effectively front-loading the purpose and credit cost. However, it could be better structured with clear sections.

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 (one parameter, output schema exists), the description provides a basic understanding of what is validated. It does not explain output format, but the existence of an output schema mitigates this gap.

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?

With 0% schema description coverage, the description adds no meaning to the single 'url' parameter beyond what the input schema already provides. Even though the parameter is self-explanatory, the description should compensate for the low 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 validates JSON-LD and microdata on a URL, specifying schema types, required fields, and errors. This specific verb+resource combination distinguishes it from siblings like analyze_url_structure.

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 (requires VISIBLYAI_API_KEY) and suggests checking balance via get_account_info, but does not specify when to use this tool versus alternatives or provide 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, the description bears the full burden. It discloses that the tool is paid, uses an external API, requires an API key, and that credits are dynamic based on keyword count. This gives adequate insight into the tool's behavior and costs, though it could mention rate limits or error handling.

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

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

The description is two paragraphs with clear structure: purpose, method, credits, requirements. Every sentence adds information without redundancy. It is concise and front-loaded with the primary action.

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 7 parameters (1 required), 0% schema coverage, and an output schema that is not elaborated, the description is incomplete. It fails to explain parameter usage, output format, or provide examples. For a complex tool making external API calls, this is insufficient for reliable 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 0%, so the description must compensate. However, it only lists parameter names without explaining their meaning, format, or examples. 'brand_variations' and 'competitors' are particularly ambiguous. The description adds minimal value beyond the schema itself.

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 classifies keywords using two methods: DataForSEO API and regex. It explicitly distinguishes itself from the sibling 'classify_keywords_simple' by claiming higher accuracy for intent detection, fulfilling the specific verb+resource and sibling differentiation criteria.

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 indicates when to use (for more accurate intent detection), mentions the required API key and credit dynamic, and suggests checking balance via 'get_account_info'. While it does not explicitly state when not to use or list all alternatives, it provides sufficient context for appropriate 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?

With no annotations, the description carries full transparency burden. It discloses offline/local regex processing, free usage, and returns multiple analytical attributes. However, it does not mention edge cases (e.g., empty input) or performance limitations, but the core behavior is well-covered.

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 concise (5 short sentences), front-loads the purpose, and avoids redundancy. Every sentence adds value: purpose, outputs, language support, sibling contrast, free status. No wasted words.

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 output schema exists and sibling tools are provided, the description is mostly complete. It covers purpose, usage, key behavioral traits, and language support. The only shortfall is parameter explanation, but for a relatively simple tool, it's adequate.

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 compensate. While 'keywords' and 'brand_name' are self-explanatory, the description does not explain how 'brand_variations', 'product_keywords', or 'competitors' affect classification. This leaves a gap in understanding their role.

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 classifies keywords using local regex patterns, lists specific outputs (intent, funnel stage, brand type, conversion score, topic), and differentiates from the advanced sibling by noting the free/offline nature. The verb 'classify' and resource 'keywords' are precise.

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?

Explicitly provides context for when to use this tool: 'fast, free, offline.' It contrasts with 'classify_keywords_advanced (paid)' for enhanced detection, and emphasizes 'Free tool - no API key or credits required,' guiding the agent toward appropriate 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?

With no annotations, the description carries full burden for behavioral disclosure. It mentions credit cost (15-60) but fails to state if the tool is read-only, if it respects robots.txt, or any rate limits. The agent gains insufficient insight into side effects or safety considerations beyond cost.

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 short and front-loaded with the main action, but it wastes space by repeating 'VISIBLYAI_API_KEY' requirement and credit range, which could be inferred. It is not verbose, but could be more efficient while adding essential parameter 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 no annotations, 0% schema coverage, and an output schema not described here, the description is insufficiently complete. It does not explain the optional OnPage analysis, the output structure, or how the keyword parameter affects results. The tool is complex enough to warrant more detail.

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 0% description coverage, and the description does not explain any of the three parameters (url, keyword, max_pages). The agent must infer that url is the target, keyword is for SEO context, and max_pages limits crawl depth. This is a critical gap for correct tool use.

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 crawls a website and optionally performs a 24-point OnPage SEO analysis. This distinguishes it from sibling tools like onpage_analysis or audit_sitemap, which focus on specific aspects rather than crawling. However, it could better differentiate when to use this tool versus those siblings.

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 required API key and suggests checking account balance via get_account_info. This gives basic usage context, but it does not provide guidance on when to use this tool versus alternatives (e.g., analyze_url_structure). It also doesn't describe any prerequisites or typical workflow.

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 responsibility. It discloses a behavioral nuance (shows free tools if no API key), but does not mention authentication requirements, rate limits, or potential side effects. More detail would be beneficial.

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?

Description is very concise with two sentences. The first sentence covers the main purpose, and the second adds an important conditional behavior. No unnecessary words.

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 no parameters and an existing output schema, the description covers the core functionality and a special case. It does not explicitly mention authentication, but that is likely implicit. Overall fairly complete 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?

Tool has no parameters, so schema coverage is effectively 100%. The description adds meaning about returned information (account status, credit balance, subscription tier) but does not add to parameter semantics since none exist. Baseline score of 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?

Description clearly states the tool checks account status, credit balance, and subscription tier, with a specific verb ('Check') and resource (VisiblyAI account info). It is distinct from sibling tools which focus on SEO analysis, keywords, crawling, etc.

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 does not provide explicit guidance on when to use this tool versus alternatives. It only states what it does, lacking context about when it is appropriate or when other tools should be preferred.

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 must fully disclose behavioral traits. It only mentions that credits vary and an API key is required. It does not state whether the operation is read-only, if there are rate limits, what happens on insufficient credits, or any side effects. The description provides minimal transparency beyond obvious prerequisites.

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: two sentences that front-load the purpose and follow with a prerequisite. Every word serves a purpose with no fluff or repetition. It is well-structured for quick scanning.

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 has 3 parameters and no annotations, the description is incomplete. It covers the basic purpose and a credential requirement, but lacks parameter explanations, usage context, and behavioral details (e.g., pagination, error handling). An output schema exists, so return value documentation is not needed, but the description still falls short of providing sufficient context for correct 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 3 parameters (domain, location, limit) with 0% description coverage. The description adds no meaning to these parameters; it only lists output fields. It does not explain what 'domain' expects (e.g., full URL or just domain), what 'location' values are valid (beyond a default), or what 'limit' controls. The description fails 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 the tool's purpose: 'Get backlink profile' and lists the output fields (Domain Rating, total backlinks, referring domains). This provides a specific verb and resource. However, it does not distinguish itself from the sibling tool 'get_referring_domains', which likely returns a subset of this data, slightly reducing clarity.

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 explicit guidance on when to use this tool versus alternatives. It mentions the requirement for `VISIBLY_API_KEY` and suggests using `get_account_info` to check balance, but does not advise against using this tool when credits are low or indicate any specific scenarios where another tool would be better. No when-to-use or when-not-to-use information is provided.

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 disclose all behavioral traits. It states that credits vary and requires an API key, but fails to mention if the tool is read-only, whether it has side effects, rate limits, or any destructive behavior. The disclosure is insufficient for an AI agent to assess safety.

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 short (2 sentences plus a line about requirements) and avoids verbosity. However, it sacrifices valuable information for brevity, leading to under-specification. It is adequately concise but could be more informative without becoming bloated.

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?

Although an output schema exists (which can document return values), the description does not reference it or any return structure. It lacks information about what the tool returns (e.g., list of domains with metrics). For a tool with 4 parameters and no parameter docs, the description is incomplete.

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 4 parameters with 0% description coverage. The description does not explain the meaning or usage of any parameter (e.g., 'domain' is not clarified as the source domain, 'location' defaults to Germany but no context is given). The agent must rely solely on parameter names, which may be ambiguous.

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: 'Get competitor domains based on keyword overlap.' It specifies the action ('get'), the resource ('competitor domains'), and the criterion ('keyword overlap'). While it doesn't explicitly distinguish from sibling tools, the purpose is specific enough for an AI agent to understand its core function.

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 ('Requires VISIBLYAI_API_KEY') and suggests checking balance via 'get_account_info', but it provides no guidance on when to use this tool over alternatives like 'get_keywords' or 'get_backlinks'. There is no context about typical use cases or when to avoid it.

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 fully bears the burden. It discloses key behavioral traits: it is a read-only operation (shows connections), requires a VISIBLYAI_API_KEY, and costs 0 credits. This is sufficient for a simple informational 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: two sentences with no wasted words. The first sentence states the purpose immediately, and the second adds essential behavioral info (credits and auth). This is ideal for a simple tool.

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 (no parameters, no nested objects, and an output schema exists), the description sufficiently covers all essential context: what the tool does, authentication, and credit cost. No further information is needed for correct 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?

There are 0 parameters, so the baseline is 4. The description adds no parameter-level detail, but none is needed. It correctly conveys the tool's action without relying on parameter documentation.

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 function: 'Show connected Google Search Console and Analytics 4 properties.' It uses a specific verb and resource, and it is distinct from sibling tools like 'get_keywords' or 'get_traffic_snapshot' that serve different purposes.

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 does not mention prerequisites, typical use cases, or conditions under which another tool would be more appropriate.

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

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

With no annotations, the description provides some behavioral context: the tool is free, requires no API key, and the data is scraped weekly. However, it lacks details on rate limits, output format, or any potential limitations.

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 concise, with three short sentences that front-load the core purpose, then provide usage guidance and additional context (free, no auth). No wasted words.

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 that an output schema exists (though not shown), the description adequately covers what the tool does and how to use it. It could mention the expected output format, but the purpose is clear enough for an agent to select and invoke.

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 single parameter 'category' is fully explained. The description states its default is 'list', it can be used to list categories, and enumerates all available categories. This goes beyond the input schema, which only provides a default and no enum 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 retrieves Google Search developer guidelines, specifies the source (scraped weekly from developers.google.com), and lists available categories. It distinguishes itself from sibling tools like analyze_url_structure or crawl_website, which focus on specific analyses.

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 explains to use category='list' to see all categories and provides a list of available categories. It does not explicitly state when not to use this tool, but the context of sibling tools implies this is for guidelines retrieval, not for other tasks.

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 partially compensates by noting that credits vary and data is limited to 5 years. However, it lacks details on rate limits, pagination, or side effects. The cost variability is useful, but overall transparency is moderate.

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 concise, with the purpose stated in the first sentence and prerequisites in the second. It is front-loaded and contains no unnecessary information. 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?

Given 4 parameters (1 required) and an existing output schema, the description omits important context such as required parameter (domain), default values for location and date_from/to, and expected output format. The tool is moderately complex, but the description leaves significant gaps.

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 description adds no parameter details beyond what the input schema provides. It does not explain the meaning of 'location', 'date_from', 'date_to', or the required 'domain'. With 0% schema coverage, the description fails to compensate, leaving the agent without guidance on how to use parameters.

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 retrieves historical traffic trends with a 5-year limit. The verb 'get' and resource 'historical traffic trends' are specific enough, and it implicitly distinguishes from sibling 'get_traffic_snapshot' by specifying historical data. However, it could more explicitly differentiate from other traffic-related tools.

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 'get_traffic_snapshot' or 'get_competitors'. The only usage advice is to check account balance via 'get_account_info', which is more about prerequisites than comparative 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?

With no annotations provided, the description bears full burden for behavioral disclosure. It notes credit consumption and API key necessity, but lacks details on mutation, rate limits, or output behavior. The description is adequate but not comprehensive.

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

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

The description is concise with two sentences: first stating purpose, second adding usage notes. It is appropriate in length for a tool with 3 parameters, though more parameter details could be included without being verbose.

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 has 3 parameters, no annotations, and an output schema, the description provides essential purpose and usage context but omits behavioral details like pagination, error handling, or credit cost specifics. It is moderately complete 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 description coverage is 0%, yet the description adds minimal parameter context beyond the schema (e.g., domain, location, limit). It does not explain default values, allowed input formats, or how parameters affect results. The description should compensate 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.

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

The description clearly states the tool retrieves top ranking keywords for a domain, specifying fields like volume, position, and URL. It distinguishes itself from sibling tools (e.g., classify_keywords_* or get_backlinks) by focusing on ranking 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 API key requirement and variable credits, advising to check balance via get_account_info. While it doesn't explicitly state when to use this tool over alternatives, the context implies it's for obtaining keyword rankings, not classification or analysis.

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 only adds authentication requirement and credit cost (0). It does not disclose read-only nature, side effects, error conditions, or rate limits. The behavioral disclosure is minimal.

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?

Three concise sentences, front-loaded with the primary purpose, zero unnecessary words. 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?

Despite having an output schema (reducing need to explain return values), the description lacks explanation for the input parameter and does not cover error cases or usage context. Incomplete for a single-parameter 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 has 0% description coverage and the only parameter, project_id, is not mentioned in the description. The description fails to explain that the parameter identifies which project to retrieve.

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 'Get' and resource 'project details' and specifies included items (competitors, Google connections), distinguishing it from siblings like get_competitors and get_google_connections.

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 when to use this tool (to get a full project view) but does not explicitly state when not to use it or mention alternatives. There is no guidance on selecting between this and more specific tools like get_competitors.

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 full burden for behavioral disclosure. It only mentions 'Credits: varies' but does not describe whether the tool is read-only, any permission needs, rate limits, or what happens on failure. The behavior around 'authority scores' is also undefined.

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 short at three sentences, but it omits important context. The first sentence defines purpose, but the last two about API key and balance are useful yet brief. It is not excessively wordy but could be improved with more detail without becoming verbose.

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 (3 parameters, output schema, sibling tools), the description is very incomplete. It does not explain what 'authority scores' are, how to interpret results, or any pagination/limit behavior. The output schema exists but the description should add 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 0%, and the description does not explain any of the three parameters (domain, location, limit). It adds no meaning beyond the schema, leaving the agent to guess their semantics.

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 referring domains' and the resource 'with authority scores', which distinguishes it from sibling tools like get_backlinks or get_competitors. The verb and resource are specific and unambiguous.

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 only mentions the API key requirement and a reference to check balance via get_account_info. It does not provide any guidance on when to use this tool versus alternatives like get_backlinks or get_competitors, nor does it explain conditions for 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 exist, so the description must cover behavioral traits. It states the tool is free and requires no credentials, implying a read-only retrieval. But it does not explicitly confirm no side effects or describe the full behavior beyond retrieval.

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 concise: a single clear purpose sentence, followed by a list of valid skills, the special 'list' case, and a note about freeness. Every sentence adds value without redundancy.

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 simple one-parameter input and existence of an output schema, the description adequately explains what the tool returns and how to use it. It could briefly mention the output structure, but that is covered by the 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?

With 0% schema description coverage, the description compensates by explaining that the 'name' parameter accepts specific skill names or 'list' to enumerate all skills. This adds significant semantic meaning beyond the raw schema.

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 retrieves an SEO workflow skill with step-by-step methodology and CTR models. It lists specific skills and the special 'list' option, effectively distinguishing it from sibling tools like seo_agent or seo_checklist.

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 clear guidance on usage: lists valid skill names, explains how to see all available skills via 'list', and clarifies that no API key or credits are needed. However, it does not explicitly state when not to use this tool or suggest alternatives.

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

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

The description discloses that credits vary and requires an API key, offering some behavioral insight. However, since no annotations are provided, more details like rate limits, idempotency, or data freshness would be beneficial for a read operation.

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

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

The description is appropriately concise with three sentences, front-loading the purpose. It avoids fluff, though it could include brief parameter details without significant bloat.

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 has only two parameters and an output schema, the description provides the core purpose and some behavioral context. However, it lacks explanation of the location parameter and expected output format, leaving minor gaps.

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 description only implicitly references the domain parameter, but completely omits the location parameter which has a default but is not explained. With 0% schema description coverage, the description should elaborate on parameters but barely does so.

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 gets current organic and paid traffic for a domain, which is a specific verb+resource. The purpose is straightforward, but it does not explicitly differentiate from sibling tools like get_historical_traffic, so a slight deduction.

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 prerequisites (API key) and a tip to check balance via get_account_info, but provides no guidance on when to use this tool versus alternatives such as get_historical_traffic or get_keywords.

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?

Discloses key behavioral trait: free and no authentication needed. No annotations present, so description carries burden and meets it.

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 concise sentences, front-loaded with purpose and key context, no wasted words.

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?

Tool is simple with no parameters; output schema exists. Description covers purpose and a key behavioral note, fully adequate.

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?

No parameters, baseline score 4. Description adds context about SEO queries and free usage.

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 lists available countries/locations for SEO data queries. It's specific and distinct from sibling tools.

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

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

Indicates it's free and requires no API key or credits, giving clear context. Lacks explicit 'when not to use' but sufficient for a simple tool.

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. It discloses credit cost ('Credits: 0') and authentication requirement ('Requires VISIBLYAI_API_KEY'), which are helpful. However, it does not mention rate limits, data freshness, or any side effects. For a simple list operation, this is moderately adequate.

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: two sentences. It is front-loaded with the main purpose and contains no filler words. Every sentence adds value.

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

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

For a simple list tool with an output schema, the description covers the main purpose and key constraints (credits, auth). However, it lacks details on pagination, ordering, or limits, which are common for list operations. The presence of an output schema partially compensates, but some context is missing.

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?

There are no parameters, and schema description coverage is 100% trivially. Baseline for 0 parameters is 4. The description does not add parameter information, but it is not needed.

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 ('List'), the resource ('EEAT projects'), and the information returned ('scores, domains, and analysis status'). This distinguishes it from sibling tools like get_project which likely retrieves a single project.

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 (e.g., get_project). There is no mention of prerequisites or context, apart from requiring an API key. The description lacks explicit when-to-use or when-not-to-use information.

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 that the tool costs credits and requires an API key, but does not describe the return format, side effects, or execution time. However, since an output schema exists, details of the return are covered there.

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 concise, consisting of two short sentences that convey the purpose, cost, and requirements without any unnecessary words.

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, the description covers the main purpose, cost, and prerequisite. However, it lacks details about the 24-point analysis scope and any limitations or example use cases. For a simple tool with two parameters, it is adequate but not comprehensive.

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 lists 'url' and 'keyword' with no descriptions (0% coverage). The description mentions 'keyword, content, technical checks' but does not clarify what the keyword parameter should be or how it is used. The parameter semantics are insufficient.

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 explicitly states 'Run 24-point OnPage SEO analysis: keyword, content, technical checks', which is a specific verb+resource. It clearly distinguishes from sibling tools that focus on individual aspects (e.g., check_links, check_structured_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 includes usage guidance: it mentions the credit cost (15) and the requirement for VISIBLYAI_API_KEY. It also suggests using get_account_info to check balance, which is a practical alternative for verifying 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 provides some behavioral context: credits=0, auto-selects property, and list of report types. But it omits details on response format, error behavior, or rate limits, which would be valuable.

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 concise with bullet-like lines, but lacks structured formatting. It is front-loaded with key info, but some sentences could be more precise (e.g., 'Credits: 0' is vague).

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 4 parameters and no annotations, the description is incomplete. It does not explain return values (though output schema exists), prerequisites beyond API key, or typical usage scenarios. Adequate for a basic tool but could be more complete.

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 compensate. It adds meaning for report_type (list of types) and ga4_property (auto-selects), but does not fully describe days or limit parameters. Adequate but not comprehensive.

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 queries Google Analytics 4 for traffic, pages, sources, and revenue, listing specific report types. However, it does not differentiate this tool from similar siblings like get_historical_traffic or get_traffic_snapshot.

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. It mentions auto-selection of property and API key requirement, but no context for choosing among many sibling analytics tools.

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. It discloses the tool's behavior: it generates sub-queries, crawls pages, extracts topics, performs semantic matching, and uses ranking keywords from GSC or DataForSEO. It also notes credit usage. This provides good transparency beyond the input schema, though it does not address rate limits or destructive potential.

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 concise (four sentences), front-loads the core function, and includes a bullet list for use cases. Every sentence adds value, with no redundancy.

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

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

Given the tool's complexity (multiple steps, data sources, credits) and the presence of an output schema (not shown), the description covers the process, use cases, and data source options reasonably well. It could include more details on the output format or prerequisites, but it is sufficient for understanding the tool's role.

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%, yet the description only elaborates on 'url' and 'keyword' by stating they are required. 'data_source' is mentioned vaguely ('GSC or DataForSEO'), but default values and the meaning of 'language' and 'gsc_property' are not explained. The description adds minimal parameter-level detail, failing to compensate for the lack of 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 the tool performs 'Query Fan-Out AI Coverage Analysis' for a URL and seed keyword, detailing the process (fan-out sub-queries, crawling, topic extraction, semantic matching) and use cases (content gap analysis, AI-search coverage). This specificity distinguishes it from sibling tools like 'analyze_url_structure' or 'crawl_website'.

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 explicitly lists use cases ('Use for: content gap analysis, AI-search coverage, sub-topic coverage for a page'), providing clear context. However, it does not mention when not to use the tool or compare it to alternatives, so it scores slightly below a 5.

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?

Describes semantic search ranking by relevance and recency, and lists sources. With no annotations, it provides basic behavioral context but omits error handling, rate limits, or access restrictions beyond the API key.

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?

Three sentences plus a brief note on credits and API key is efficient. Purpose is front-loaded, though parameter documentation is missing.

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 an output schema noted but no details, and five parameters, the description is adequate for a search tool but lacks parameter explanations and error/edge-case 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 0%, and the description provides no parameter-level guidance. Parameters like category and document_type are left unexplained, forcing reliance on names only.

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 searches the SEO knowledge base comprising blogs, docs, and Google guidelines, with semantic search. It distinguishes from sibling tools like get_google_guidelines by covering multiple sources, but could be more explicit about its uniqueness.

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?

Mentions credit cost and API key requirement, implying a paid/searched usage context, but lacks explicit guidance on when to use versus sibling tools like get_google_guidelines or when not to use it.

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

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

No annotations provided, so description must disclose behavior. It notes credits=0 and auto-selects property, but does not mention idempotency, pagination, rate limits, or impact. Minimal disclosure for a data retrieval 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?

Short and to the point, but includes minor extraneous info ('Credits: 0'). Most sentences are informative, though structure could be improved.

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?

Has output schema, so return values are covered. However, parameter descriptions are missing, and tool complexity is moderate. Description falls short of providing complete context for all parameters and behaviors.

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 has 6 parameters with 0% description coverage. Description briefly lists some dimensions and says property auto-selects, but does not explain days, limit, country, device, or their defaults. Does not compensate for 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 queries Google Search Console for clicks, impressions, CTR, and position. It names the tool's purpose but does not differentiate it from siblings like query_analytics or get_traffic_snapshot.

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?

Mentions auto-selection of property and API key requirement, but lacks guidance on when to use this tool versus alternatives. No explicit when-not or comparisons with 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?

Lists API key requirement and credit consumption, but does not disclose if actions are read-only or modify data. No annotations to compensate.

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?

Concise at 4 sentences, front-loads main purpose. Could benefit from bullet points for agents.

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?

Covers API key, credits, auto-detection, and project enrichment. Lacks details on agent behaviors and output, though output schema exists.

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%, but description explains several parameters (task, agent, project_id) and their roles. Does not fully explain 'params' or 'content'.

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?

Clearly states it runs a specialized SEO agent and lists available agent types (crawling, seo_analyst, etc.). Suggests differentiation from sibling tools but does not explicitly contrast.

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?

Mentions enriching with project context and checking balance via get_account_info, but no explicit when-to-use or when-not-to-use. Implies general orchestration tool.

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 provides transparency about cost ('Free tool - no API key or credits required') and return type ('actionable checklists'). However, it doesn't explicitly state read-only behavior or potential 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 concise with three sentences, front-loading the purpose. Every sentence adds value (types, return, language, free aspect), with no wasted words.

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 simple retrieval tool, the description covers purpose, parameters, return format, and availability. It lacks details on limitations (rate limits, max results), but given the output schema exists and the tool is free, it's fairly complete.

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%, but the description partially compensates by listing checklist type values (general, blog, etc.) and language options (en, de). However, it does not explain each type's purpose or confirm exact allowed values, leaving 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 it returns an SEO checklist and lists available types (general, blog, ecommerce, etc.). It distinguishes the tool from siblings like seo_agent or seo_guidance by focusing on checklists, but does not explicitly contrast them.

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. It does not mention prerequisites, when not to use, or compare with other SEO tools like seo_guidance or seo_workflow.

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 exist. The description mentions it's free and requires no API key, which is helpful, but does not disclose if the tool has any side effects, rate limits, or the nature of returned data. Output schema exists but is not described.

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, front-loads the core purpose, and lists topics efficiently. Every sentence is meaningful.

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 (one parameter, output schema exists), the description adequately covers purpose, valid inputs, and cost. It could mention return format but output schema compensates.

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 only specifies a string with no enum values, but the description enriches semantics by listing all valid topics (e.g., title_tags, meta_descriptions), providing significant added value beyond the schema.

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 'Get SEO best practices on a topic' with a specific verb and resource. It does not explicitly differentiate from siblings, but the topic enumeration adds clarity.

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 a usage tip (topic='list') and states it's free, but lacks explicit guidance on when to use this tool versus sibling tools like seo_checklist or seo_workflow.

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 full burden. It discloses the requirement for an API key and credit consumption (60-200 credits per workflow), which is helpful for a workflow tool. However, it does not discuss side effects, error handling, rate limits, or what occurs upon credit insufficiency.

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 concise (two sentences plus a workflow list) and front-loaded with the main purpose. It could benefit from bullet points for readability, but it avoids unnecessary verbosity.

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 covers workflow names and credits, but fails to explain three of four parameters (domain, project_id, params). While an output schema exists, the lack of input guidance makes the tool harder to invoke correctly without external knowledge.

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?

Input schema has 4 parameters with 0% description coverage. The description only elaborates on the 'workflow' parameter by listing possible values and their credit costs. It does not explain 'domain', 'project_id', or 'params', leaving their semantics unclear despite the need for compensation.

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 purpose: 'Run a multi-step SEO workflow with report generation.' It lists three specific workflows (seo_performance_audit, indexing_diagnosis, quick_win_analysis) with credit costs, distinguishing this tool from sibling tools that perform single analyses instead of multi-step workflows.

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 prerequisites (VISIBLYAI_API_KEY) and suggests using get_account_info to check balance, but it does not explicitly state when to use this tool vs. alternatives like individual analysis tools. Usage context is implied but not clearly delineated.

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 credit consumption and API key requirement, but omits details like rate limits, error handling, or whether the operation is read-only. The output schema exists but the description itself is minimal on behavior.

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

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

The description is concise with two sentences. It is front-loaded with the primary purpose. However, the requirement of API key and credit info could be structured better (e.g., a separate notes section).

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 does not need to detail return values. It covers prerequisites and cost but lacks information on error scenarios, pagination, or how credits are calculated. For a tool with 4 parameters, the description is moderately complete.

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. However, it does not explain the parameters (keywords, location, language, top_n) beyond their names. The names are self-explanatory but no additional guidance on formats or constraints is given.

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 keywords by providing search volume, competition, and CPC. It distinguishes from sibling tools like classify_keywords_advanced, which classify rather than validate.

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 prerequisites (VISIBLYAI_API_KEY) and suggests checking balance with get_account_info. However, it does not explicitly contrast with alternative tools for similar metrics or specify when not to use this tool.

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