Review-Code

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool builds prompts and does not directly call LLM, which clarifies it's a preparatory step rather than an execution tool. However, it lacks details on permissions, rate limits, error handling, or what the output looks like, which are critical for a tool with 4 parameters and no output schema.

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, efficient sentence that front-loads the core purpose without unnecessary details. It wastes no words, though it could benefit from slightly more structure to improve clarity.

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 complexity (4 parameters, 0% schema coverage, no annotations, no output schema), the description is incomplete. It doesn't explain parameter roles, output format, or behavioral constraints, making it inadequate for an agent to use the tool effectively without additional context or trial-and-error.

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 description coverage is 0%, so the description must compensate for undocumented parameters. It mentions 'single-file review and scoring' but doesn't explain what filePath, content, style, or commitMessage mean or how they relate to prompt building. This leaves key parameter semantics unclear, failing to add meaningful value beyond the bare schema.

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 purpose: '构建用于单文件审查与打分的 LLM 提示词（不直接调用 LLM）' which translates to 'Build LLM prompts for single-file review and scoring (does not directly call LLM)'. This specifies the verb ('build'), resource ('LLM prompts'), and scope ('single-file review and scoring'), though it doesn't explicitly differentiate from sibling tools like review_code or review_diff.

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 no guidance on when to use this tool versus alternatives. It mentions 'single-file review and scoring' but doesn't specify scenarios, prerequisites, or exclusions compared to siblings like review_code or parse_review_score, leaving the agent to infer usage context.

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