Review-Code

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions parsing and extracting scores in a specific format, but doesn't describe what happens if the format isn't found (e.g., returns null, error), whether it handles multiple scores, or the output structure. This leaves key behavioral traits unspecified for a tool with mutation-like parsing.

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 extremely concise—a single sentence in Chinese that directly states the tool's function. It's front-loaded with the core action and format, with zero wasted words, making it efficient and easy to parse.

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 (parsing task with no annotations, 0% schema coverage, and no output schema), the description is incomplete. It doesn't explain the return values, error handling, or edge cases, which are critical for a parsing tool. The lack of output schema means the description should cover return behavior, but it doesn't.

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. It implies the parameter 'reviewText' is the input text to parse, but doesn't explain its expected content (e.g., Chinese text, length limits) or provide examples. With 1 parameter undocumented in the schema, the description adds minimal semantic value beyond the parameter name.

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: parsing scores from review text, specifically extracting scores in the format '总分:XX分'. It uses specific verbs ('解析', '提取') and identifies the resource (review text). However, it doesn't explicitly differentiate from sibling tools like review_code, review_diff, or review_file, which might handle different aspects of reviews.

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 doesn't mention sibling tools or specify contexts where this parsing is appropriate (e.g., for text reviews vs. code reviews). There's no information on prerequisites or exclusions, leaving usage unclear.

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