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

With no annotations provided, the description carries the full burden, and it delivers richly: it discloses the JSON return shape, the meaning-vs-wording preservation caveat, the authentication requirement with 401 rejection, the paid-model nature, input/output limits and truncation, the rate limit of 30 calls/hour, and the possibility of cached results for identical inputs.

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?

Although relatively long, every sentence earns its place: core function, output shape, verbatim-use warning, sibling routing, auth, cost, limits, rate limit, and caching. It is dense but logically ordered and front-loaded with the purpose, not padded.

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 absence of annotations and an output schema, the description is remarkably complete for a paid, restricted, truncation-prone tool. It covers input constraints, output format, failure modes (401, 413 implied), rate limits, caching, and the semantic caveat, leaving no critical gap for an agent to call it safely.

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 baseline is 3. The description repeats the 10,000-character input cap and adds output-truncation context, but it adds no meaning for the level parameter beyond the schema's already-complete enum explanation. It does not compensate beyond the baseline.

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 opens with a specific verb and resource ('Rewrite text you already have so it reads less like model output'), clearly distinguishing it from generation tools. It explicitly names siblings generate_text and draft_email and states that 'this one only transforms text it is given,' so an agent can disambiguate it from the other tools in the set.

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 explicit when-to-use and when-not-to-use guidance. It says to use generate_text for new prose and draft_email for whole emails, and warns against using this tool on text that must stay verbatim such as quotes, legal copy or code. This directly routes the agent to the correct sibling.

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