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

The annotations already declare read-only, idempotent, non-destructive, and closed-world behavior. The description adds useful behavioral context beyond annotations: invalid input returns an error object instead of a protocol error, and retrying after correction is safe. It does not deeply discuss permissions or rate limits, but those appear low-risk for this local analysis tool.

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 core purpose and constraints are front-loaded, and most sentences add useful selection or invocation guidance. The response example and error-handling paragraph are somewhat long, especially because an output schema exists, but they still reduce ambiguity for an agent.

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 rich annotations, full schema coverage, and an output schema, the description is complete for selecting and invoking the tool. It covers the minimum sample requirements, intended use, exclusions, downstream use, error behavior, and retry safety.

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 coverage is 100%, so the schema already documents both parameters clearly. The description still adds practical meaning by specifying at least 2 samples, 150+ combined words, real writing by the same person, and a typical input shape. It does not add much about the optional label beyond what the schema says.

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 states a specific operation: build a measurable voice profile from a person's real writing samples. It distinguishes the tool from sibling ai_tell_scan and explains how its output connects to humanize_plan and verify_rewrite. An agent can identify the resource, action, and downstream role without ambiguity.

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?

It gives explicit inclusion criteria: use samples the person actually wrote, with 2+ samples and 150+ words total. It also names exclusions and alternatives: not for scoring an unknown draft, which belongs to ai_tell_scan, and not for text the person did not write.

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