find_ai_words

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

With no annotations, the description carries the full burden and does well: it discloses the return shape (clean boolean, count, every occurrence with its sentence) and a comparative cost/precision trait versus score_ai_text. It stops short of stating any auth, rate-limit, or side-effect behavior, but the tool is an analysis read so the gap is minor.

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?

Front-loaded with the core action in the first sentence, then value-add detail about return values, workflow, and sibling comparison. Every sentence earns its place; the trailing clause is compressed and informative rather than filler.

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?

No output schema and no annotations, yet the description covers the return payload, the workflow loop, and the stopping criterion. An agent has everything needed to invoke it and act on the result.

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% for the single required 'text' parameter, so the description must compensate. It implies the input is a draft and gives post-processing instructions about 'every fact, figure, name and link', but never states the format, size limits, or whether text is plain or markdown.

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 ('Check') and resource ('a draft for stock AI phrasing') plus the output scope ('report exactly where it appears'). It explicitly distinguishes itself from the sibling score_ai_text, so an agent can tell the two apart without opening either schema.

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 explicit sequencing ('Run it after humanize_text'), the follow-up action ('rewrite each flagged sentence'), and a stopping condition ('Repeat until clean is true'). It also names the alternative and the condition that selects this tool over score_ai_text.

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