humanize

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

With no annotations provided, the description carries the full burden. It discloses the internal pipeline (preprocess, surface-tell substitution, watermark scrub, stylometric smoothing, optional paraphrase passes), which is valuable behavioral context. It does not explicitly state whether the tool is read-only or has side effects, but for a text transformation tool this is largely implicit.

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 concise and front-loaded: a one-sentence purpose, one sentence on process, and one sentence pointing to an alternative. Every sentence adds value with no filler or redundancy.

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's complexity (configurable pipeline) and rich schema/output schema, the description is complete enough for selection. It explains the purpose, distinguishes from the diagnostic variant, and provides a pointer to further architecture docs without over-explaining return values already covered by the output schema.

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 tool description itself does not add substantial parameter meaning beyond the schema; it references docs and list_styles but repeats concepts already covered in the schema's property descriptions. Thus it does not exceed 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+resource+outcome: 'Rewrite AI-generated text so it reads as human-authored.' It distinguishes itself from sibling humanize_and_verify by explicitly noting that the latter provides diagnostic output.

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 clearly tells when to use this tool vs the alternative: use humanize for the final text, and humanize_and_verify for diagnostic output. It also points to list_styles for enumerating available style presets, giving practical usage context.

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