voice_verify

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 statistical method (null resampled from the user's own writing, same length), defines thresholds (under 75, over 97), and notes that it names specific words that fall outside the range—providing thorough behavioral context.

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?

Every sentence earns its place: it defines the purpose, explains interpretation, contrasts with sibling, gives usage guidance, and mentions output. The description is dense but not wordy, and it is front-loaded with the core concept.

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?

Despite having no output schema, the description explains the return value (authorship percentile) and the additional output (specific out-of-range words). It provides enough context for the agent to understand when to use the tool and what to expect.

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?

The schema covers 100% of parameters with descriptions, so the baseline is 3. The tool description mentions 'text' but does not elaborate on the 'path' parameter; it adds no semantic value beyond what the schema already provides.

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 identifies the tool as an authorship verification test ('impostor test') and explains its output (authorship percentile). It distinguishes itself from voice_score, making the purpose unambiguous and specific.

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 explicitly instructs to run both voice_verify and voice_score on any draft before showing it, and explains the difference in what each catches. This gives clear when-to-use and when-not-to-use guidance that differentiates from sibling tools.

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