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?

With no annotations, the description carries the full burden and does well: it discloses required scopes (content:approve, content:publish), a side effect (automatic CMS writeback), and differing behavior per suggestion type (topic suggestions only create a query). It omits reversibility/undo behavior and failure modes, but the permission and side-effect disclosure is strong.

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 compact sentences, front-loaded with the primary action and permission gate. Each sentence adds distinct information (base requirement, conditional CMS requirement, topic-suggestion exception) 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?

An output schema exists, so return values need not be explained. The description covers the permission model and per-type behavior, which is the key context for this mutation tool. It could still mention reversibility given the sibling undo/reject tools, but overall it is sufficiently 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% and there is one required parameter (suggestion_id), yet the description says nothing about it — not its format, nor that it should come from list_optimizer_suggestions. The description fails to compensate for the coverage gap.

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?

States a specific verb+resource ('Apply an optimizer suggestion') and elaborates on the different outcomes depending on suggestion type. It does not explicitly name which siblings it is not (reject_optimizer_suggestion, undo_optimizer_suggestion), but the action is 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?

Provides useful conditional guidance on when different permission requirements apply (snippet/link vs topic suggestions), which implicitly frames when the tool acts directly on CMS versus just creating a query. However, it never says when to use this over reject_optimizer_suggestion or undo_optimizer_suggestion, so alternative selection is left to inference.

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?

With no annotations, the description carries the full burden and does so well: it discloses that approval triggers the normal CMS webhook and enumerates the permission and budget prerequisites for queueing. This is exactly the kind of side-effect and authorization context an agent needs before calling a write 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?

Only two sentences and both are dense with operational detail. The opening 'Review an article' is the one soft spot, being somewhat imprecise, but nothing is padded.

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

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

An output schema exists so return values need not be described, and the permission/webhook behavior is covered. Gaps remain: no sibling differentiation for a tool sitting among many article-mutation tools, and no coverage of two of three parameters.

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 adds meaning for the new_status parameter (approved and queued semantics and their requirements) but ignores rejected and archived enum values entirely and says nothing about article_id or project_id.

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 name and enum make the intent clear (changing an article's status to approved/rejected/archived/queued), but the opening sentence 'Review an article' is vague and arguably misleading for a mutation tool. It never states the full verb+resource scope or distinguishes itself from siblings like publish_article or update_cms_article.

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 gives useful when-context for two of the four statuses: approval needs content:approve and queueing needs spending:execute plus several account-level conditions. However, it says nothing about when to choose this tool over publish_article, update_article, or submit_article_draft, and rejected/archived paths are unexplained.

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?

With no annotations, the description carries the full burden, but it does disclose two meaningful traits: the required permission scope (cms:manage) and the critical one-time webhook secret return that must be stored externally. It still omits idempotency, whether creation triggers validation, and what happens on duplicate connections.

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 tight sentences with the core action front-loaded and the operational caveat second. Zero filler, every clause earns its place.

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

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

The one-time secret and permission scope are good additions, and an output schema exists so return values need not be detailed. However, for a six-parameter creation tool with no annotations and no schema descriptions, the absence of any parameter or prerequisite guidance leaves the definition materially 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?

Schema description coverage is 0% across six parameters, so the description is the only place parameter meaning could be added — and it says nothing about cms_type, project_id, config, webhook_url, or webhook_events. The opaque anyOf `config` object and the webhook_* fields in particular go entirely unexplained.

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?

States a specific verb and resource ("Create a CMS connection") so it is clearly distinct from siblings like list_cms_connections, test_cms_connection, and delete_cms_connection. It does not explicitly contrast itself with those siblings, but the operation is 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?

No statement of when to use this tool, what prerequisites exist (e.g., a project must exist first), or which alternative applies for related needs such as testing an existing connection. Usage must be inferred entirely from the tool name.

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 and does well: it discloses that plaintext is returned only once and that cms:manage scope is required. It omits whether rotation invalidates the previous key, which is the main behavioral gap for a key-rotation 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?

Two compact sentences, front-loaded with the core action and followed by the two operational facts that matter most. No filler.

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

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

An output schema exists so return values need not be described, and the description covers the security-relevant facts (one-time plaintext, permission scope) for a simple one-parameter tool. Only the effect of rotation on existing keys is left unaddressed.

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% for the single project_id parameter, but the description's 'project-scoped' wording clarifies its meaning. The parameter name is largely self-explanatory, so the description adds modest 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?

States a specific verb and resource ('Create/rotate a project-scoped Pull API key') with clear scope. The action naturally separates it from its siblings get_contentpilot_key_status and revoke_contentpilot_key without needing to name 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?

The 'create/rotate' phrasing implies the situations in which it is used, so usage is implied rather than stated. It never explicitly contrasts with revoke_contentpilot_key or get_contentpilot_key_status, nor states when rotation is warranted over initial creation.

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

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

With no annotations, the description carries the full disclosure burden. It does add two genuinely useful traits: the operation is paid (spending side effect) and it requires content:write plus spending:execute scopes. It omits cost magnitude, whether an existing query is overwritten, and whether the spend is recoverable, so the mutation/expense profile is only partially 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?

Two tight sentences with the action front-loaded and no filler or redundancy. It is arguably under-sized for the operation's complexity, but nothing is wasted and it reads cleanly.

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 5-parameter, cost-incurring creation tool with no annotations and 0% schema coverage, the description covers only purpose, cost, and scope. An output schema exists so return values need not be explained, but the input contract is entirely undocumented by either structured fields or prose.

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% across 5 parameters, so the description must compensate and it does not. It says nothing about keyword, project_id, or the country/language/persona_id defaults, leaving the agent to infer all input meaning from bare property names.

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?

States a specific verb and resource: 'Run paid SERP/content analysis and create a query.' An agent can tell this produces a content query from a keyword-based SERP analysis. It does not differentiate from siblings like save_content_query_draft, get_content_query, or check_serp, which overlap in the keyword/SERP/query space.

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

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

There is no when-to-use or when-not-to-use guidance, and no alternative is named despite several plausible siblings (check_serp, list_content_queries, save_content_query_draft). The 'paid' qualifier and required scopes hint at caution, but the agent is left to infer the condition that selects this 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the required permission scope but fails to state irreversibility, side effects (e.g., whether associated articles or settings are deleted), or any confirmation behavior—critical gaps for a destructive delete 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 two short sentences, front-loads the action, and contains no redundant or filler text. Every word serves a purpose.

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

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

For a destructive delete tool with no annotations, no parameter descriptions, and an output schema that only covers return values, the description is severely under-informative. It omits parameter explanations, irreversibility warnings, and any behavioral context needed to invoke the tool safely.

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

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

The schema has 0% description coverage for both required parameters (project_id and connection_id), and the description does not mention or explain either parameter. It adds no meaning beyond the bare integer names, leaving an agent to infer their roles entirely.

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 states a specific verb ('Delete') and resource ('CMS connection'), clearly distinguishing it from sibling tools like list_cms_connections, create_cms_connection, and test_cms_connection. An agent can immediately tell what this tool does.

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 states a permission requirement ('Requires cms:manage') and offers no guidance on when to use this tool versus alternatives, no prerequisites beyond the scope, and no exclusions. A user must infer that this permanently removes a connection with no additional context.

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

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

With no annotations, the description carries full burden but does disclose two useful behaviors: it creates a backup and checks the revision. However it omits permission requirements, what happens on a revision mismatch, and other side effects of an 11-parameter mutation.

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 short sentences, no filler, and the core action is front-loaded. It is efficient, though the terseness leaves key terms undefined.

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

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

An output schema exists so return values need not be described, but for a mutation with 11 params, zero schema coverage, and no annotations, the definition leaves too much unspecified for an agent to call it confidently.

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% across 11 parameters, so the description must compensate. It only implies a revision check (mapping loosely to expected_revision) and says nothing about title, content, format, keywords, idempotency_key, or the other fields.

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?

It states the resource (content article) and a mutation verb, but 'Full editor update for editable statuses' is vague about what an 'editable status' is. It also fails to distinguish itself from close siblings like update_article and update_cms_article, which an agent would need to tell apart.

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 only hint of a precondition is the phrase 'editable statuses', with no explanation of which statuses qualify. No when-to-use guidance and no named alternative among the several update-related 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 usefully discloses that generation is queued and requires spending:execute, but omits side effects, reversibility, rate limits, and what happens to the query after queueing.

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?

A single front-loaded sentence with no wasted words. It states purpose first and the key prerequisite second.

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 three-parameter mutation tool with no annotations and 0% schema description coverage, the description is too sparse. It covers the core purpose and permission requirement, but leaves parameter meanings, usage routing, and expected behavior largely undocumented. The output schema covers return values, so that gap is acceptable.

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% across three parameters. The phrase 'from a ready query' weakly implies that query_id must reference a ready content query, but the description says nothing about improve or project_id and adds little usable meaning 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?

States a specific verb and resource: queuing AI article generation from a ready query. This clearly separates it from query-creation and retrieval siblings, though it does not explicitly name alternatives such as regenerate_content_article or optimize_content_draft.

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 only usage guidance is the prerequisite 'requires spending:execute.' It does not say when to use this tool versus alternatives, what a 'ready query' means, or any exclusion conditions.

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?

No annotations are provided, so the description carries the full burden. It usefully discloses read-only status and zero credit cost, but it does not mention authentication, data limits, or any other operational constraints beyond those two facts.

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, front-loads the data scope, and avoids bloat. However, its telegraphic fragment style leaves key meaning unexplained, making it concise but under-specified.

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 an analytics insight tool with two parameters, zero parameter descriptions, no annotations, and an output schema, the description should at least explain project_id/days and how it differs from sibling query_analytics. It only lists output domains and cost/read-only, leaving major calling context 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?

Schema description coverage is 0%, and the description mentions neither project_id nor days. The required project_id and the default days parameter are therefore undocumented in both schema and description.

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 names GA4 data domains (flow, funnel, channels, AI-referrer signals), giving a specific data scope, but it never states the action clearly or what 'insights' are returned. It also does not distinguish itself from sibling query_analytics, so the purpose is only partially clear.

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 'Credits: 0, read-only' note tells the agent this is free and safe, but there is no when-to-use condition, prerequisite, or guidance relative to query_analytics or other analytics siblings. Usage context is therefore minimal.

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

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

With no annotations, the description carries the behavioral burden well: it discloses that the operation is read-only, costs 0 credits, returns text only when include_content=true, chunks content up to 20000 characters, and exposes content_hash changes after edits. It does not cover auth requirements or rate limits, but the core behavioral traits are clearly stated.

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

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

The description is very short and front-loads the core output behavior and pagination note. The opening fragment "One article." is terse and structurally weak, but there is little wasted text.

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 read tool with an output schema available, the description covers key behaviors such as chunking, credits, read-only status, and edit detection. However, with 0% schema description coverage and five input parameters, it leaves important parameter semantics and the project_id argument unaddressed.

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 explains include_content and implies the 20000-character chunk size for content_limit, but article_id and project_id remain unexplained, and it refers to "next_content_offset" while the schema parameter is content_offset, which can confuse pagination calls.

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 says "One article," which identifies the resource but does not itself state a retrieval verb; the tool name get_article supplies that context. It distinguishes a single-article fetch from list-oriented siblings like list_articles, but gives no further differentiation from other article-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?

The description gives a pagination instruction ("Use next_content_offset to continue") but never explains when to use get_article instead of alternatives such as list_articles, get_content_query, or get_content_briefing. There is no when-to-use or when-not-to-use guidance.

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

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

With no annotations, the description carries the full behavioral burden. It does disclose a genuinely useful trait, that content comes back in bounded chunks, implying paging via the offset/limit parameters, and 'Read' implies a non-mutating operation. However, it says nothing about permissions/auth needs, whether project_id must match the backup's project, or rate/volume 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?

A single front-loaded sentence with no filler or redundancy; every word carries information about scope and retrieval behavior.

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

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

An output schema exists, so return values need not be explained, and the chunking hint covers the main retrieval behavior. Still, for a 4-parameter read tool with zero annotation and zero schema description coverage, the absence of any identifier semantics or prerequisite/paging guidance leaves the definition only minimally 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 compensate for all four undocumented parameters. 'Bounded content chunks' hints at the meaning of content_limit/content_offset, but backup_id, project_id, their relationship, and the 12000/0 defaults are left entirely unexplained.

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 names a specific verb (Read) and a specific resource (one saved version, i.e. a backup), plus the delivery mechanism (bounded content chunks). It is clearly a single-item read, but it never distinguishes itself from close siblings like list_article_backups or restore_article_backup, which an agent must infer from the id-based schema.

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

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

There is no when-to-use guidance and no mention of alternatives such as list_article_backups (to find a backup id) or restore_article_backup (to apply one). The agent gets no routing signal between these three closely related 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 and does a solid job: it states 'Writes nothing', discloses the credit cost (0 credits), and adds a subtle state caveat that 'accepted is not completed'. It stops short of describing any permission requirements or pagination behavior, but the safety profile and cost are clearly disclosed.

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, leading with the returned resources before the optional comparison mode. The phrase 'Missing metadata is unknown' is terse to the point of being cryptic, but overall very little is wasted.

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

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

An output schema exists, so return values need not be explained, and the description appropriately focuses on scope, comparison behavior, cost, and the read-only guarantee. The main remaining gap is routing guidance relative to the many sibling read tools, but for a low-risk read operation with a documented output shape this is close to 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% across 3 parameters, so the description must compensate. It meaningfully explains what compare_live does—a comparison of saved revision text, links, images, structure and metadata against the live site—but article_id and project_id are left entirely undocumented beyond being self-evident names, and no formats or constraints are 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 names concrete resources the tool returns: editor links, published article conflicts, and last CMS transfer status. That is more specific than the name 'get_article_workflow' alone would allow, and it implicitly separates itself from a plain content read, though it never names a sibling like get_article or get_content_status.

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 gives conditional guidance for one mode ('With compare_live, compare the saved revision's text, links, images, structure and metadata against the website'), which tells the agent when to set that flag. However, there is no guidance on when to reach for this tool instead of get_article, get_content_status, or recall, so the alternative-selection problem is left to inference.

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?

With no annotations, it discloses read-only status, zero credit cost, and pagination behavior including page.has_more/next_offset. This adds useful operational context, though it omits auth or error 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?

Very concise and front-loaded: purpose first, then cost/safety, then prerequisite and pagination. 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?

Output schema exists, so return values needn't be explained, but the description leaves most parameters undocumented for a 6-param tool with no annotations. It is minimally sufficient to invoke with defaults but incomplete for full correct usage.

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 explain six parameters. It only identifies cluster_key's source and implies pagination via limit/offset, leaving days, country, project_id, and explicit pagination parameters undocumented.

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?

States the resource precisely: keywords of one cluster, with metrics and pagination. The mention of cluster_key from get_gsc_clusters distinguishes it from cluster-listing tools and general keyword 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?

Tells the agent where to get the required cluster_key (get_gsc_clusters), which establishes usage flow. It does not state when to prefer this over get_keywords 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 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?

With no annotations, the description carries the full burden and does meaningfully fill it: it discloses that the operation is read-only, costs 0 credits, and raises a 409 while the analysis is still pending. It does not cover rate limits or pagination, but the cost, safety profile, and failure modes are 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?

Two tightly written sentences: the first front-loads what the briefing contains, the second adds cost/safety and the failure condition. No filler, though the structure is slightly terse for the guidance it is trying to convey.

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

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

The tool has an output schema, so return values need not be explained, and the description covers the safety profile, cost, and the key error state. The main gap is parameter meaning, which is largely a separate dimension, so the description is close to complete for a simple read getter.

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% for two parameters (query_id required, project_id optional) and the description says nothing about either. With such low coverage the description should compensate, but it provides no explanation of what query_id or project_id refer to, leaving the agent to infer from names alone.

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?

States a specific resource and enumerates its contents (terms, entities, questions, outline) for a 'finished content analysis', so an agent knows what it will get. It does not explicitly differentiate itself from siblings like get_content_query or get_content_status, which share the 'retrieve content-analysis state' space.

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 phrase 'of a finished content analysis' plus the '409 query_not_ready while the analysis is still pending' note gives an implied precondition for use. However, no alternative tool is named and no explicit when-not guidance is given beyond the pending-state caveat.

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

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

With no annotations, the description carries the full burden and does disclose meaningful traits: the operation is read-only, the returned key is masked (so no full secret is exposed), and it requires the cms:manage permission. The output schema covers return structure, so this is reasonably complete for a small read 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?

Two short sentences, front-loaded with the action and resource, followed immediately by the permission requirement. 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?

The presence of an output schema removes the need to explain return values, and the description covers read-only, masking, and auth. It still leaves project_id semantics and the relationship to the sibling create/revoke key tools unaddressed, which is a gap for a tool whose result may guide key management decisions.

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% for the single project_id parameter, so the description is expected to compensate. It only implies project scoping through the phrase 'project Pull API key' and gives no format, source, or lookup guidance for project_id.

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 states a specific verb (Read) and resource (masked project Pull API key status), which is clear on its own. It does not explicitly contrast itself with the nearby create_contentpilot_key or revoke_contentpilot_key siblings, but 'status' vs 'create'/'revoke' is distinguishable by inference.

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?

'Requires cms:manage' is a useful prerequisite, which edges it above pure silence. However, it never says when to call this versus create_contentpilot_key or revoke_contentpilot_key, so usage is only implied.

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

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

With no annotations, the description carries the full burden. It does disclose useful traits: the read is bounded and paginated and the draft is optional, implying a read-only fetch. However, it says nothing about auth, permissions, or what 'context' contains, leaving real gaps.

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?

A single front-loaded sentence with no wasted words. It is efficient, though arguably so terse that it omits information the agent needs.

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

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

An output schema exists so return values need not be described, but with 5 parameters at 0% coverage and no annotations, the description is too thin to fully specify 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?

Schema description coverage is 0%, so the description must compensate, but it only loosely alludes to include_draft ('optionally') and the pagination params ('bounded, paginated'). query_id and project_id get no explanation at all.

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 names a specific verb (Read) and resource (query context, plus an optional saved draft), which distinguishes it from create_content_query, save_content_query_draft and list_content_queries. It is clear enough to select, though 'query context' remains somewhat abstract.

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

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

There is no explicit when-to-use guidance and no mention of alternatives such as get_content_briefing or list_content_queries. The agent must infer the use case from the resource name alone.

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

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

No annotations are provided, so the description carries the full burden. It does disclose two useful traits: 'Credits: 0' (no cost) and 'read-only' (safe, non-mutating), which is meaningful for a status call. However, it says nothing about polling cadence, terminal states, or what happens when the query_id is unknown/invalid.

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?

A single compact sentence that front-loads the resource and ends with the two most decision-relevant facts (no texts, free, read-only). No filler, though 'no texts' is slightly telegraphic.

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

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

An output schema exists, so return-value detail is not required, and the read-only/free framing covers behavior adequately for a status tool. The remaining gap is parameter documentation, particularly the optional project_id, which is undocumented everywhere.

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 and does not. The required query_id is only loosely implied by 'a content query', and the optional project_id is entirely unexplained, leaving the agent to guess whether it scopes the lookup.

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?

States a specific resource (analysis status of a content query) plus article generation state, which distinguishes it from get_content_query and list_content_queries. The 'no texts' qualifier usefully signals it is a metadata-only view. It stops short of naming a verb but the name supplies 'get'.

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 call this versus get_content_query or the article-status siblings. An agent must infer that this is a polling endpoint to use after create_content_query or generate_article_from_query. There are no exclusions or prerequisites stated.

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

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

With no annotations, the description must carry the disclosure burden, and it does add real signal: zero credit cost and read-only behavior. It omits scope details such as the analysis window, whether 'trend' needs historical data, and any auth requirements.

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 dense sentences, contents listed first and cost/safety last. Nothing is padded and the key 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?

The output schema covers the return shape, so results needn't be explained, and credit/read-only facts are present. However, for a tool whose sole required argument is undocumented, the definition leaves a real gap 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 required project_id has 0% schema description coverage and is never mentioned in the description, so the agent gets no hint about what a project_id is or where to obtain one. The description does not compensate for the coverage gap.

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?

Names a specific resource (E-E-A-T summary) and enumerates its contents: scores, trend, open todos, competitor comparison. An agent can tell what it returns, though it does not distinguish itself from the nearby get_scorecard sibling.

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 indication of when to reach for this summary versus get_scorecard, get_analytics_insights, or the other reporting tools. The only usage-adjacent text is the cost note 'Credits: 0, read-only', which is not selection guidance.

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 carries the burden and delivers: it declares cost ('Credits: 0'), safety ('read-only'), quota behavior ('Runs on the project owner's Google quota'), and the async state model via 'computing'/'stale' flags. It omits whether results are cached or how long computation takes, but covers the key behavioral traits well.

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?

Front-loaded with the purpose, then structured into a return-value sentence and a parameter/constraint tail. Dense but largely waste-free; the parameter note at the end is slightly abrupt rather than clearly sectioned.

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

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

An output schema exists, so the description needn't explain return shape exhaustively, yet it still summarizes returns usefully. For a 4-parameter read-only tool with no annotations it covers safety, cost, quota, and the drill-down path; the main gap is the undocumented 'days' window.

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, and it only partially does. It adds real meaning for country (ISO alpha-3, e.g. deu) and top_n (clusters by impressions, default counts implied), but 'days' and 'project_id' are never explained in either schema or description.

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?

States a specific verb and resource ('Topic clusters from Search Console') and names the exact sibling it pairs with ('stable cluster_key for get_cluster_keywords'), so an agent can distinguish it from the many other content/SEO tools. It also enumerates what is returned (quick wins, alerts, totals, flags).

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 mention of cluster_key 'for get_cluster_keywords' implies a follow-up workflow, and top_n framing implies ranking usage, but there is no explicit when-to-use vs alternatives or exclusion guidance. Usage is only implied.

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 must carry full behavioral disclosure. It usefully states 'Credits: 0, read-only' and describes conditional output, but it omits authorization requirements, rate limits, and pagination behavior for limit/offset.

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 short sentences, front-loaded with the conditional logic and behavioral facts. Every phrase earns its place with no redundant or filler text.

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

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

An output schema exists, so return-value details are appropriately omitted. The description covers conditional outputs, read-only status, and zero credits, though it still lacks pagination semantics for limit/offset and any scope note for project_id.

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% with four parameters. The description explains only the url parameter (its effect on output), leaving project_id, limit, and offset undocumented anywhere, so it does not compensate for the schema coverage gap.

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?

Names a specific resource (internal link graph) and precisely distinguishes behavior with and without the url parameter. It does not explicitly differentiate itself from sibling tools like check_links or audit_sitemap, but the conditional return description makes the tool's purpose clear.

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 how to use the url parameter to get different outputs (summary/orphans vs inbound links/anchors), which implies two usage modes. However, it offers no guidance on when to choose this tool over alternatives such as check_links, audit_sitemap, or get_backlinks.

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?

No annotations are provided, so the description carries the full burden. It usefully discloses 'read-only' and 'Credits: 0', which is genuine behavioral value, but it omits operation-status semantics (pending vs complete/terminal states) and any auth expectations that matter for a polling 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?

Two compact clauses with the purpose front-loaded and the cost/read-only fact appended. No waste, though extremely terse for an operation-status 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?

An output schema exists, so return values needn't be spelled out. However, with no annotations and 0% param coverage, the description is thin: it does not clarify the polling/async nature of the operation or what a status result implies.

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 single operation_id parameter is undocumented in the schema. The description's 'one of your write operations' only implicitly signals that operation_id references a prior write call; it adds no format or sourcing detail to compensate for the coverage gap.

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?

States a specific verb (retrieve status/result) and resource (a write operation), scoped to 'one of your write operations'. It clearly reads as an operation-status lookup, which none of the siblings duplicate. It stops short of naming a sibling or distinguishing itself explicitly.

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 phrase 'one of your write operations' implies this is used to poll an operation you previously triggered, but there is no explicit when-to-use, no when-not-to, and no named alternative. Usage must be inferred.

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 behavioral burden. The verb "Read" implies a non-destructive operation, but there is no disclosure of permissions required, whether settings are project-scoped, or how the "latest run" data relates to run_content_optimizer. The output schema covers return values, but the mutation/safety profile is left unstated.

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?

A single front-loaded sentence with no filler, which is appropriately sized for a simple read tool. It could not be trimmed without losing content.

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 existence of an output schema means return values need not be explained, and the terse description adequately conveys the read scope. But with no annotations, no parameter documentation, and no routing guidance among the many optimizer siblings, the definition is only minimally sufficient.

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 the single required parameter project_id is documented nowhere in the schema; the description also says nothing about it. While project_id is self-evidently a project identifier, the description adds no meaning beyond the parameter name.

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 names a specific verb ("Read") and a concrete resource ("optimizer/autolink settings, limits, and latest run"), which is enough to tell it apart from the mutation sibling update_optimizer_settings. However, it never explicitly names that sibling or the other optimizer tools, so the differentiation is implied rather than stated.

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

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

There is no explicit when-to-use guidance, no prerequisites, and no mention of alternatives such as update_optimizer_settings or run_content_optimizer. An agent must infer that this is the inspection step before modifying optimizer configuration.

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 are provided, so the description carries the full burden, and it delivers two meaningful behavioral facts: 'read-only' and 'Credits: 0'. It also explains the has_data=false edge case (nothing is estimated yet), which prevents misreading an empty result as zero revenue. It omits auth/permission or rate-limit details, so it is strong but not exhaustive.

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 short lines with zero filler, front-loaded with the resource and its outputs, followed by cost and the has_data caveat. Information is well ordered and every clause earns its place. It is slightly clipped rather than fully polished prose.

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

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

An output schema exists, so the description need not document return shape, and it still flags the has_data edge case. It covers cost, safety posture, and scope. The remaining gap is the absence of any usage routing among the many sibling analytics tools, which keeps it from a 5.

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

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

Schema description coverage is 0%, but there is only one required parameter (project_id), whose meaning is self-evident from its name and type. The description adds no scoping or format detail for it. For a single obvious identifier parameter, 3 reflects adequate-but-unelaborated 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 names a specific resource and scope ('Organic revenue attribution') and enumerates the concrete outputs the tool returns (totals, top keywords/landing pages, Pareto, cluster revenue), so an agent knows exactly what it produces. It doesn't explicitly contrast itself with nearby siblings like get_analytics_insights or get_traffic_snapshot, so it stops short of a 5.

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

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

There is no when-to-use guidance and no named alternative, despite a crowded sibling space with several analytics/reporting tools. The only conditional stated is about the has_data return flag, which is data semantics rather than usage routing. An agent gets no help deciding between this and get_analytics_insights.

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

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

With no annotations, the description carries the full burden, and it usefully discloses two behavioral traits: zero credit cost and read-only (non-mutating). It stops short of disclosing auth requirements, rate limits, or freshness of the indicator data, so it adds real but incomplete context.

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

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

Two terse sentences that front-load the resource and its content, with the cost/read-only qualifier kept compact at the end. No filler or 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?

An output schema exists, so return-value detail is not required, and the description covers the resource, its indicator type, the time window, and the cost/safety profile. The main gap is the unexplained project_id required parameter and the absence of routing versus sibling analytics tools.

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. The phrase '28 or 90 days' usefully constrains the days parameter to two values (information absent from the schema, which only shows a default of 28), but project_id is entirely unexplained, leaving half the parameters undocumented.

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 names a specific resource (KPI scorecard) and its content (leading + lagging indicators) plus a scope window, so an agent knows what is returned. It does not, however, distinguish this from related analytics siblings like get_analytics_insights or get_revenue_insights, so 4 rather than 5.

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

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

There is no statement of when to use this tool versus alternatives such as get_analytics_insights or get_traffic_snapshot. The 28/90-day window is a scope constraint, not usage routing guidance, so this is essentially no guidance.

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 that the tool is free with no key/credits required and that content-nss-optimize involves iterative scoring toward NSS 70/80 with a returned editor link, which is real behavioral context. It still omits whether results are cached, the response shape, or any auth nuances beyond the free-tool note.

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 core purpose leads, followed by the skill list and the special 'list' value; most sentences earn their place. The multi-line enumeration of skill names is a bit sprawling but is genuinely informative rather than filler.

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

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

An output schema exists, so return-value explanation is not required, and the description covers the parameter's valid domain and the free-tool constraint. It is largely complete for a single-parameter retrieval tool, with only light gaps around how skills differ from sibling guidance endpoints.

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 the single 'name' parameter has no schema description, so the description must compensate. It does so well by enumerating the valid skill names and documenting the name='list' sentinel value, giving the agent enough to populate the parameter correctly.

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?

States a specific verb and resource: retrieves an SEO workflow skill containing methodology and CTR models. It enumerates the skill names it can return, so an agent can tell what content comes back. It doesn't explicitly differentiate itself from siblings like seo_guidance or seo_checklist, keeping it out of the top band.

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 says to use name='list' to enumerate all skills and flags it as a free tool needing no API key, which is useful invocation context. It does not say when to prefer this over sibling guidance tools like seo_guidance or seo_workflow, so usage is only implied.

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?

With no annotations, the description carries the full burden and delivers: credits cost of 0, idempotent replay behavior, the exact key rights required (memory:write vs content:write plus a content write role), and that facts land in 'YOUR brain' while rules/personas/profile go to the project. It even describes the response echoing the idempotency key. This is unusually rich disclosure for a mutation tool.

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

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

Front-loads the essential facts (what it writes, cost, idempotency) in the first line, then the payload shape and permission model. Dense but each sentence adds operative information; the parenthetical field lists are long but necessary given the 0% schema coverage.

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 7-parameter mutation with no annotations and no schema descriptions, the description covers the payload shape, the permission/key-right model, idempotency semantics, and the return echo. An output schema exists, so it does not need to detail return values further; nothing an agent needs to call it correctly 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?

Schema description coverage is 0% across 7 parameters, so the description must compensate, and it does for the domain-shaped ones — it explains that facts carry content/category/entities, rules carry rule_type plus term or note, and lists personas and brand_profile fields, all in the shape the preview returned. It does not explain 'source' or 'project_id', leaving two parameters undocumented anywhere.

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?

States a concrete verb+resource ('Write the reviewed selection from import_meeting_preview') and explicitly ties itself to its sibling preview tool, so an agent can tell it is the apply step of a two-phase import. No ambiguity about what is being written or where it comes from.

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?

Implies the workflow condition: use this after import_meeting_preview, passing only the items the user approved. That is clear context for invocation, but there is no explicit when-not or alternative path (e.g., what to do if the user rejects everything or the preview is stale).

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 and delivers: it is non-mutating ('nothing is written'), states cost ('15 per run, charged to the key holder'), and required authorization ('memory:write right and access to the project'). This is unusually rich behavioral context for a preview 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?

Purpose is front-loaded, then cost, return content, workflow, and params in sequence. The sentence is dense but each clause (cost, safety, workflow, constraints) earns its place; only minor tightening is possible.

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, the description still explains the four returned lists and their categories, which aids selection. Combined with cost, auth, workflow, and parameter constraints, an agent has everything needed to invoke it correctly.

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 documents 'text: 200 to 60000 characters, plain text' and 'source: a short name for the transcript', covering two of three parameters well; project_id is only implied by 'for one project'. A small gap remains for the id parameter's expected form.

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?

States a specific verb and resource: 'Turn a meeting or call transcript into a reviewable proposal for one project.' It also names the downstream sibling import_meeting_apply, so the agent can distinguish this preview step from the apply step without opening either schema.

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?

Explicit when-to-use workflow: call this to get a proposal that 'nothing is written', show the four lists to the user, let them strike/edit, then call import_meeting_apply with the selection. The alternative tool and the condition selecting it are named directly.

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

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

With no annotations, the description carries the full behavioral burden. It does disclose one meaningful trait — the returned versions exclude content, which sets expectations for payload size — but says nothing about permissions, ordering, or pagination limits. The output schema covers return shape, so the remaining gaps are modest.

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?

A single front-loaded sentence with zero filler. The scope restriction is attached directly to the verb, so the agent gets the essential information on the first read.

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

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

An output schema exists, so return values need not be described. However, with two required parameters undocumented in both schema and description and no annotations to convey safety or behavior, the definition is adequate but leaves real gaps for an agent invoking it.

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% — both parameters have only bare titles ("Article Id", "Project Id"). The description does not mention either parameter or clarify which project/article the versions belong to, so it fails to compensate for the undocumented 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?

States a specific verb (list) and resource (saved editor and CMS versions/backups), plus a scope qualifier ("without their content") that tells the agent what it will and won't get. It is clearly distinguishable from the singular get_article_backup, though it never names that sibling explicitly, so it falls just short of a 5.

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

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

Usage is implied rather than stated: listing versions before fetching or restoring one is the obvious context, and "without their content" hints this is the lightweight discovery step preceding get_article_backup. There is no explicit when-to-use, when-not-to-use, or named alternative, so it sits at the minimum viable level.

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

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

With no annotations, the description carries the full burden and does meaningful work: it discloses 'read-only' and 'Credits: 0' (cost), states results are metadata only, and specifies ordering and pagination. It omits details like page-size caps or what happens at the end of the result set.

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 short, front-loaded lines with no filler; the core fact (what is listed, ordering, pagination, cost) comes first and the status enum is separated as a reference block. Efficient, though slightly telegraphic.

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

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

An output schema exists, so return values need not be explained, and the description covers cost, safety, ordering, pagination and the status filter. A note about result size limits or linkage to a project would complete it.

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 enumerates the valid status values, which is genuinely useful, but says nothing about limit, offset, or project_id semantics beyond their obvious names.

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?

States a specific verb and resource ('Content articles of a project') plus scope qualifiers ('metadata only', 'newest first, paginated') that make the operation unambiguous. It does not name a sibling to differentiate from, so it stops short of a 5.

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

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

The description gives no indication of when to use this vs alternatives like get_article, list_content_queries, or get_content_status, and no exclusions or prerequisites. The status values hint at filtering but do not constitute usage guidance.

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