Detect AI-written text

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

With no annotations, the description carries the full burden and adequately discloses key behaviors: returns an overall score (with direction), supports optional per-sentence scores, and imposes a 15,000-character limit. It lacks details on error handling or rate limits, but is sufficient for the tool's simplicity.

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?

Four short sentences, each adding essential information: action, return values, use case, and limit. No fluff 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 there is no output schema, the description effectively explains the return values and their meaning. It also covers the maximum input length and provides a practical use case. The tool is simple, and the description covers all necessary context.

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%, giving a baseline of 3. The description adds value by explaining the score interpretation ('lower = more human-like') and referring to per-sentence mode as 'depth mode', which goes beyond the schema's wording.

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 clearly states the tool scores text for AI-likelihood using Rephrasy's AI detector, with a specific verb ('Score') and resource. However, it does not explicitly differentiate from the sibling tool 'humanize', so it misses the top score.

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 a clear use case ('verify a draft before publishing') and implies when to use it, but it does not mention when not to use it or explicitly name the alternative 'humanize' tool. This is a clear context without exclusions, scoring a 4.

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