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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), and the description adds substantial context beyond them: the rules are fixed patterns rather than a model, the text is not stored, results are capped, a low score is not proof of authorship, and the tool does not rewrite. This is exactly the extra behavioral detail annotations cannot carry.

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 purpose is front-loaded and the return-value summary is useful, but the authorship disclaimer is repeated three times ('It cannot say who wrote the text', 'cannot say whether an AI wrote it', and the 'not proof of who wrote the text' clause). That redundancy costs space without adding information.

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 tool with a full output schema, the description covers everything an agent needs: limits, return shape, scoring rationale, non-storage, and the meaning of a finding. Nothing material is left unstated.

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% and the property description already states the 12,000-character cap, plain-text/Markdown support, and code-block/link skipping. The description's 'pass the text exactly as written' and the character limit largely restate the schema, so it adds little beyond the baseline for a fully documented single parameter.

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?

States a specific verb and resource ('Flags writing habits') and immediately bounds it ('It cannot say who wrote the text'), which is the key distinction an agent needs. The sibling tools (get_feedback_reply, index_tools, submit_feedback) share no overlap, and the description makes the scope unmistakable.

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?

Gives an explicit trigger ('Use it when the user asks which parts read like AI writing') plus two concrete example phrasings ('find the filler in my draft', 'what makes this email read as machine-written'). It also states the inverse constraint that it cannot determine authorship.

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