seo-audit

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

With no annotations, the description carries the full burden. It discloses the ~7 signals checked, the return type (weighted 0–100 score + top fixes), and the limitation that it returns a summary only (full report via email). It doesn't explicitly state the audit is read-only or mention URL accessibility requirements, but 'Audit ANY URL' implies a non-mutating operation; a small transparency gap remains.

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 front-loaded with the primary purpose and scope, then follows a logical flow: signals checked, output format, parameter, sibling routing, and report escalation. Every sentence contributes distinct information, with no redundancy or 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?

For a single-parameter, read-only audit with no output schema or annotations, the description covers everything an agent needs: what it does, what inputs it takes, what it returns, which siblings to use instead, and how to get the complete report. No critical operational detail 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 100% (url described with 'The website URL to audit, e.g. https://example.com'), so baseline is 3. The description adds 'ANY URL' and the contrast with get_my_store_audit, clarifying that the parameter accepts arbitrary public URLs, not just connected stores. This goes slightly beyond the schema.

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

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

The description states a specific verb and resource ('Audit ANY URL') with a precise scope ('AI-search readiness only (AEO/GEO/LLMO)'), clearly differentiating it from full SEO audits. It enumerates concrete signals checked and the output (0–100 score + top fixes), leaving no ambiguity about what the 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?

Explicitly names alternatives with conditions: 'Use full_seo_audit for the broader SEO picture, or get_my_store_audit for the user's own connected store.' Also routes to email_seo_report for the full written report, informing the agent when this tool suffices and when a sibling is 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 provided, the description carries the full behavioral burden. It discloses the critical consent rule ('never guess or reuse an address'), the weekly re-audit behavior when weekly is true, and the one-click unsubscribe property. This gives the agent the safety-relevant context needed to invoke the tool appropriately.

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 overly repetitive. 'Email the full written SEO/AEO report for an audit this session already ran' largely duplicates the first sentence, 'ONLY use an email address the user explicitly gave you' repeats the earlier consent warning, and 'Offer this after presenting audit results' restates 'ALWAYS OFFER THIS after running an audit.' The content is good but could be condensed to roughly half its length.

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 tool with no output schema and no annotations, this description is complete. It explains when to use it, where the audit_id comes from, how to handle the email address, and what weekly mode does. The agent has enough information to call the tool correctly and 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?

Schema description coverage is 100%, so the baseline is 3. The description adds value by explicitly tying audit_id to the outputs of ai_search_diagnostic or full_seo_audit, and by reinforcing that email must be explicitly supplied by the user rather than guessed. This helps the agent understand parameter provenance beyond the schema.

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

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

The description clearly identifies the tool's purpose: email the complete written SEO/AEO report for an audit run earlier in the session. It also distinguishes this from the audit tools by noting they return a summary of top issues while this sends every check, evidence, and fix in priority order.

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 explicit when-to-use guidance: 'ALWAYS OFFER THIS after running an audit' and 'Offer this after presenting audit results.' It also specifies the source of audit_id (ai_search_diagnostic or full_seo_audit) and instructs the agent to ask for and use only the user's explicitly provided email, which is important operational 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 crawls the URL, requires no login, returns a weighted 0–100 score plus top issues, and returns only a summary while the full report goes via email. It does not mention rate limits or robots.txt compliance, which keeps it just short of a 5.

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 long but densely informative: each clause names a concrete SEO area, and the sibling-tool distinction is front-loaded near the end. No filler words appear, though the first sentence is quite packed and could be split for easier parsing.

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 only one parameter and no output schema, the description fully covers input format, audit scope, output type, authentication expectation ('no login needed'), alternatives, and where the complete report is delivered. The agent has enough context 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 description coverage is 100%: the `url` property already explains it is the website URL with an example. The description merely repeats 'Takes a `url`' and adds 'ANY URL', which adds only marginal clarification. Baseline 3 is appropriate since the schema already handles 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 opens with a specific action ('Crawl-audit'), a clearly defined target ('ANY URL'), and a bounded scope ('the WHOLE SEO surface'), then enumerates the covered areas: AI-search signals, on-page SEO, technical SEO, and Shopify schema. It distinguishes itself from get_my_store_audit, so the agent knows exactly what this tool is and is not.

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 explicitly states when to use this tool ('ANY URL', 'arbitrary website', 'no login needed') and names the alternative for a different case: 'for the user's OWN connected store with real analytics, use get_my_store_audit.' It also mentions email_seo_report for the full written report, giving clear routing 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 the full behavioral disclosure burden and does real work: it reveals authentication requirements (API key via Bearer header or api_key argument), the prerequisite of a connected store, and the internal nature of the audit using real catalog, performance, and analytics data. It does not discuss side effects, but the 'Get ... audit' phrasing implies a read-only operation and the auth mechanics are transparently documented.

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 information-dense and front-loaded with the core purpose, followed by the key differentiator and authentication details. Each sentence earns its place, though the phrase 'far beyond what crawling a URL can see' is slightly promotional and overlaps with the more concrete 'Takes no url' statement. Overall it remains well-structured and scannable.

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 audit tool with one optional parameter, no output schema, and no annotations, the description covers the essential invocation context: what the audit covers, the prerequisite connected store, the API key requirement, and the accepted authentication methods. It does not explain the response format or error behavior, but the request itself is fully specified and an agent has enough to call the tool 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?

The single optional api_key parameter is already well documented in the schema, including the inxy_sk_ prefix and the Bearer-header alternative. The description adds the key's source ('free at inxy.ai → Settings') and reinforces the two ways to pass it, but this is marginal value beyond what the schema already states. Since schema coverage is 100%, the baseline 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?

The description states a specific verb and resource: 'Get the user's OWN connected Shopify store audit' and identifies it as a deep 12-category in-app report. It distinguishes the tool from URL-crawl-based audits by saying it goes 'far beyond what crawling a URL can see' and explicitly 'Takes no url.' This makes the tool's purpose unambiguous and separates it from siblings like full_seo_audit.

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 clear context for when to use it: for the caller's own connected Shopify store, not a public URL, and only with an Inxy API key and connected store. It does not explicitly name an alternative tool or state a when-not-to-use condition, but the prerequisites and 'Takes no url' caveat effectively tell an agent when this tool is 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 carries the full burden. It discloses the return value (a personalized signup link), that payment/store connection happens in the browser, and the important privacy constraint to only pass email/store_url if the user explicitly provided them. It does not explicitly state that the tool itself does not immediately perform the listed SEO actions, but the overall transparency 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?

The description is front-loaded with the core action and then provides relevant supporting details. The product feature list is somewhat long but all sentences carry useful context for the agent to understand the service. It could be trimmed slightly, but it remains organized and purposeful.

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

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

The description covers the tool's purpose, return value, browser-based side effects, and parameter constraints. Since there is no output schema, the stated return of a personalized signup link is sufficient. Minor ambiguity remains about whether the SEO actions described occur immediately or as part of the ongoing subscription, but this does not prevent 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 coverage is 100%, so the baseline is 3, but the description adds meaningful semantics: the optional parameters are for team follow-up, and it strongly reinforces the condition to never invent them. This goes beyond the schema's descriptions by explaining purpose and emphasizing consent.

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 opens with a specific verb and resource, "Start an inxy subscription," and then details what the subscription entails for Shopify stores. This clearly differentiates the tool from the sibling audit/diagnostic tools by making the action a signup rather than an analysis.

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 clearly implies this tool is for initiating an inxy subscription, and the pricing/free trial context reinforces that intent. It does not explicitly name alternatives or state when not to use it, but the subscription-vs-audit distinction is evident from the sibling list and service description.

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