Audit Content Quality

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

Beyond the readOnlyHint annotation, the description discloses the return shape ('0-100 score with per-category breakdown and actionable recommendations') and defines the scope of what is—and isn't—analyzed. This adds meaningful behavioral context without contradicting the annotations.

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 compact and front-loaded: it opens with the core action, lists the evaluated dimensions, describes the output, and closes with an explicit exclusion and alternative. Every sentence contributes value, and there is no redundant wording.

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 3-parameter tool with no output schema, the description supplies the essential operational context: what it analyzes, the result format, and its boundary relative to audit_onpage. Required parameters are fully covered by the schema, and no critical invocation 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%, so the schema already documents url, locale, and timeout. The description adds only slight context by mentioning 'multilingual' readability, which relates to locale, but it does not substantially expand parameter semantics beyond what the schema provides.

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 with a specific verb ('Analyze content quality of a web page') and enumerates the concrete aspects it evaluates: word count, readability, text-to-HTML ratio, heading structure, link density, media richness, and engagement signals. It also explicitly distinguishes itself from audit_onpage by stating what it does NOT check, making it easy for an agent to select the correct tool.

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 guidance by stating that it does not check SEO meta tags and directs the agent to 'use audit_onpage for that'. This establishes a clear condition for choosing between audit_content_quality and its sibling tool, which is sufficient for correct tool selection.

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