校验并完成报告证据包

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

The annotations are all false, offering no safety or mutability hints. The description adds behavioral context by detailing the validation steps (checking stages, hashes, duplicates, order, output files) and the generation of JSON/Markdown packages, which implies a write operation. It also discloses the complete=false constraint, which is a meaningful behavioral rule. This goes beyond the minimal annotation information, but it does not mention side effects like overwriting existing files or failure behavior.

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 concise (two sentences) and front-loaded with the primary action. Every clause contributes meaningful information: the checks, the output generation, and the critical condition. There is no redundancy or filler.

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 the tool's complexity (validation and generation) and the presence of an output schema, the description covers the key aspects: what is checked, what is produced, and a critical precondition. It does not explain error handling or what happens if validation fails, but the output schema may cover return values, and the description is otherwise adequate for a finalization tool.

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 has only one parameter, 'session_id', with no description (0% schema coverage). The tool description does not mention this parameter at all, failing to compensate for the low coverage. While the parameter name is self-explanatory, the description provides no additional meaning about its role or constraints, so the parameter semantics are weak.

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's function: verifying required stages, screenshot hashes, duplicates, order, and output files, then generating JSON and Markdown evidence packages. The verb '校验' (verify) and '生成' (generate) specify the actions, and the resource '证据包' (evidence package) is explicit. This distinguishes it from sibling tools like capture_evidence or register_output.

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 specific usage condition: 'complete=false 时不得进入报告生成' (must not enter report generation when complete=false), which guides when not to proceed. It also references '按指导书顺序' (per the instruction book order), implying a recommended sequence. However, it does not explicitly name alternative tools or exclude cases where other tools should be used, so it falls short of a perfect score.

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