HubVibe Site Audits

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

With no annotations provided, the description fully carries the burden and does an excellent job: it discloses atomic behavior (if any dimension fails, the whole call fails and nothing is billed), pricing ($0.10 per call), and return structure. This goes well beyond basic safety hints and covers critical operational behavior.

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

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

The description is three sentences, front-loaded with the core action, followed by atomicity, cost, and return details. Every sentence adds essential 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 one-parameter tool with no output schema, the description fully explains what to expect: pass boolean plus four sub-result objects. It also covers unique behaviors like atomicity and billing, making it complete for an agent to select and invoke 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 input schema already fully describes the single parameter 'url' as 'Live URL to audit' (100% coverage). The description adds minimal extra meaning beyond confirming 'one URL', so baseline 3 is appropriate.

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

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

The description clearly states that the tool runs four audit dimensions (wcag, seo, security, performance) against a single URL in one call. This specific verb+resource+scope distinguishes it from sibling tools that audit individual dimensions.

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: when you need all four audit dimensions, and notes it is billed as a single call. However, it does not explicitly state alternatives like 'use individual audit tools for single-dimension checks', so it misses explicit exclusion 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 provided, the description carries the full burden of behavioral disclosure. It transparently discloses the cost per call ($0.03), specifies that it is a single real page load rather than a synthetic or full audit, and outlines the return shape (pass, metrics, findings with id/severity/detail). This gives the agent a clear picture of what to expect, though it does not mention whether the tool makes a live network request or any 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 two sentences, extremely concise, and front-loaded with the key metrics. Every word earns its place: it states what is measured, clarifies scope, notes the cost, and describes the return structure. There is no redundancy or fluff.

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

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

Given the simple one-parameter schema and no output schema, the description adequately covers the return format and main purpose. It also adds useful context like the cost and the distinction from a full audit. It is slightly lacking in not mentioning potential use cases or interaction with sibling tools (e.g., when to choose performance over bundle), but it is complete for a focused utility.

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

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

The input schema already provides 100% coverage with a clear description for the 'url' parameter ('Live URL to audit'). The tool description adds minor context by specifying 'real page load' and naming the measured metrics, but it does not provide additional parameter-level guidance beyond what the schema already offers. This aligns with the baseline of 3 for high schema coverage.

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

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

The description clearly states the tool measures DOM node count, transferred bytes, and request count from a single real page load, which is a specific and actionable purpose. It also explicitly distinguishes itself from a full Lighthouse audit and is clearly differentiated from sibling tools that target other audit categories (security, SEO, WCAG, bundle).

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 by listing performance-specific metrics and contrasting with a full Lighthouse audit, but it does not explicitly name alternatives or state when not to use it. The 'not a full Lighthouse audit' note provides a useful boundary, though a direct reference to a heavier alternative would strengthen 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 burden and does well by disclosing the return format (pass bool, findings[] with id/severity/detail), the fact that it uses a live HTTP response, and its scope limitations. It doesn't cover error handling or rate limits, but for this simple tool the disclosure is adequate.

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

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

The description is a single, dense sentence that efficiently lists checks, exclusions, cost, and return format. It is not overly long and front-loads the core purpose, though it could be slightly better organized by separating the return value description.

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 one-parameter tool with no output schema, the description adequately covers scope, limitations, cost, and return format, enabling correct invocation. It lacks information about failure behavior or response time, but these are not critical for this simple audit 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 schema already provides 100% coverage for the url parameter with 'Live URL to audit'. The description reinforces the 'live' aspect but adds no new parameter-level details, so it meets the baseline of 3 for high schema coverage.

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

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

The description precisely states the tool audits specific security headers (HTTPS, HSTS, CSP, X-Content-Type-Options, clickjacking protection, Referrer-Policy, CORS) from a live HTTP response. It also differentiates from TLS/cipher scans and penetration tests, making it distinct from sibling audit tools like audit_performance or audit_seo.

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 what it is not (not a TLS/cipher scan or penetration test) and mentions the cost per call, which helps an agent decide when to use it. However, it does not directly reference alternatives or provide explicit conditional guidance, so it falls short of a 5.

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

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

With no annotations provided, the description carries the full burden. It adds useful behavioral context by disclosing cost ($0.03 per call) and return structure (pass bool, findings with id/severity/detail). However, it omits details such as network usage, authentication requirements, or potential failure modes, making it adequate but not thorough.

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 exceptionally concise—two sentences that front-load the core purpose (audit checklist) and then efficiently provide cost and return details. Every word 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?

The description covers the audit items and return format, while the schema clarifies parameter usage. Given the tool's relative simplicity, this is nearly complete, though a bit more detail on the findings structure (e.g., fields beyond id/severity/detail) would enhance it. The lack of an output schema makes the brief return description acceptable but not exhaustive.

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 descriptions are complete (100% coverage), so the description does not need to explain parameters. The description does not add semantics beyond the schema, but the baseline of 3 applies because the schema already documents both url and html clearly.

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 specifically lists the SEO elements audited (title, meta description, H1, canonical, OpenGraph, structured data, lang), clearly distinguishing it from sibling audit tools like audit_security or audit_performance. The verb 'audit' plus the detailed checklist makes the tool's scope 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 implies when to use the tool (for SEO-specific audits) through its listed elements, and sibling tool names reinforce the differentiation. However, it does not explicitly state when not to use it or mention alternative tools, so it falls just short of a full 5.

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

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

No annotations are present, so the description carries the burden of disclosure. It transparently specifies the cost ($0.03 per call) and the detailed return format (pass bool, violations[] with id/impact/help/help_url/nodes_affected). It does not discuss side effects, but for a read-only audit tool, these are the key behavioral traits.

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

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

The description is two sentences long and front-loaded: the first sentence states the core purpose and implementation, the second adds cost and return information. Every sentence earns its place without 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?

No output schema is provided, but the description compensates by specifying the return fields. It does not explicitly note that at least one of url/html is required (both are optional in the schema), which is a minor gap given the potentially ambiguous input requirements.

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 provides complete descriptions for both parameters (url and html) with 100% coverage, so the baseline is 3. The tool description adds no additional parameter semantics beyond what the schema already states, leaving parameter meaning solely to the schema.

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

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

The description clearly states it performs a 'WCAG 2.1 A/AA accessibility audit via axe-core', specifying both the tool's verb ('audit') and its unique resource (accessibility standards). This distinguishes it from sibling audit tools like audit_performance and audit_security, which focus on different domains.

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 clear context for accessibility audits but does not explicitly mention alternatives or when not to use. Since the sibling tools cover other audit types (e.g., performance, security), the WCAG focus implies the appropriate use case, though it lacks explicit exclusionary guidance.

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