Content quality score

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 lists what factors are scored but doesn't disclose how the score is computed, whether it's a numeric score or a report, whether it makes network requests, or any side effects. For a tool with no annotations, this is a significant gap.

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 concise sentence that front-loads the main action and lists the key factors. It's efficient and easy to parse, though it could be slightly more structured with a second sentence for usage guidance.

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 no annotations, no output schema, and only 0% schema description coverage, the description is too thin. An agent doesn't know what the output looks like, how the score is calculated, or what to do with the result. Sibling tools like readability_score and content_gap_analysis suggest related but distinct functions, and the description doesn't clarify the boundary.

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 add meaning by explaining what the tool does with the URL (scores content quality based on listed factors), but it doesn't clarify the URL format beyond the schema's 'uri' format, nor does it explain what the output looks like. The description adds some value but not enough to fully compensate for the 0% 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 states a specific verb ('score') and resource ('content quality'), and lists the dimensions it evaluates: word count, links, media, schema, meta, headings. This distinguishes it from siblings like readability_score (which focuses on readability) and extract_keywords (which extracts keywords), though it doesn't explicitly name any 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?

The description implies usage: call this when you need a content quality score based on the listed factors. However, it doesn't explicitly state when to use this tool versus alternatives like readability_score or content_gap_analysis, nor does it mention any exclusions or prerequisites (e.g., URL must be accessible).

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