mcp-seo-audit

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

With no annotations provided, the description carries the full burden and adds valuable behavioral context: it discloses that the API is free and requires no OAuth (addressing auth needs), specifies the need for a CRUX_API_KEY environment variable (setup requirement), and implies read-only behavior by using 'Get'. It does not mention rate limits or error handling, but covers key operational aspects beyond basic functionality.

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 sized and front-loaded: the first sentence states the core purpose, followed by concise operational details and parameter explanations. Every sentence adds value without redundancy, making it efficient and easy to parse for an AI agent.

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 moderate complexity (2 parameters, no annotations, but with an output schema), the description is mostly complete: it covers purpose, behavioral traits, and parameter semantics. Since an output schema exists, it need not explain return values. However, it lacks details on error conditions or usage limits, which could enhance completeness for a data-fetching 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 description coverage is 0%, so the description must compensate. It adds meaning by explaining 'url_or_origin' accepts full URLs or origins with an example, and 'form_factor' specifies allowed values (PHONE, DESKTOP, TABLET) and a default, which clarifies usage beyond the schema's basic types. However, it does not detail format constraints or edge cases for 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 specific action ('Get Core Web Vitals') and resource ('from the Chrome UX Report (CrUX) API'), including the exact metrics (LCP, INP, CLS). It distinguishes itself from siblings like 'get_pagespeed_insights' or 'get_performance_overview' by specifying the CrUX API source and metrics, avoiding tautology with the tool name.

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 this tool by mentioning it's for retrieving Core Web Vitals from CrUX, which implies usage for performance monitoring. However, it does not explicitly state when not to use it or name alternatives among siblings (e.g., 'get_pagespeed_insights' for different metrics), leaving some guidance gaps.

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