fit_check_prompt

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

No annotations provided, so the description should disclose behavioral traits. It only says 'build the prompt' without indicating whether it has side effects, requires authentication, or modifies state. The non-destructive nature is implied but not confirmed.

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 a single concise sentence, but it is too sparse. While it has no wasted words, it lacks necessary detail, making it less effective.

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 no annotations, 0% schema coverage, and 3 parameters (2 required), the description fails to provide enough context. It does not explain the input, output, or how the tool integrates with Gate 1 fit-checking. The output schema exists but is not leveraged in the description.

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 0% and the description does not explain any parameters. The agent has no clue what cluster_slug, candidates, or definition mean or how they contribute to the prompt. This is a critical gap.

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 action (build) and the resource (Gate 1 fit-check prompt for an AI to score). It distinguishes from sibling tools like fit_check_apply and fit_check_audit by focusing on prompt generation. However, it could be more specific about what 'fit-check' entails.

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?

No guidance on when to use this tool versus alternatives like fit_check_apply or fit_check_drift. The description does not mention prerequisites, context, or exclusions. The agent must infer usage from the name alone.

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