Detect AI text

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

Discloses on-device processing, per-signal breakdown, confidence band, no yes/no verdict, directional and biased nature. No annotations provided, so description fully handles transparency.

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?

Two sentences, front-loaded with purpose and key traits, second sentence adds bias and recommendation. No fluff, every sentence earns its place.

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 one parameter, no output schema, no annotations, description covers purpose, usage, transparency, bias, follow-up tool. Complete for agent decision-making.

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?

Only one parameter 'text' with schema description 'The text to analyze.' Description adds context: 'passage', 'AI-written', 'reads as', enhancing meaning beyond schema. Baseline 3 for high coverage, but description provides valuable extra context.

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 it scores likelihood of AI-written text on a 0-100 scale with no yes/no verdict, distinguishes from sibling find_ai_tells by mentioning it provides per-signal breakdown and suggests using find_ai_tells for spans.

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?

Explicitly says to treat as second opinion, not proof, and advises to call find_ai_tells after for rewriting. Also notes bias against non-native English writers, setting appropriate expectations.

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