review_diff

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

With no annotations provided, the description carries full burden. It clearly discloses that the tool does not invoke an LLM, which is critical behavioral context. It does not describe return format or side effects, but for a prompt-building tool, the non-LLM-calling behavior is the key transparency point.

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 that front-loads the core purpose and key behavioral constraint (no direct LLM call). There is no superfluous content; every word earns its place.

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?

For a 3-parameter tool with no output schema, the description is complete enough. It explains the tool's function and boundary (no LLM call). The missing output spec is not critical since the tool's purpose is to produce a prompt, and the user likely knows what a prompt is.

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 100%, so the baseline is 3. The description does not add any parameter-specific context beyond what the schema already provides (e.g., no examples, no explanation of how 'style' affects output). The description remains high-level about the tool's function.

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: to build an LLM prompt for reviewing and scoring Git diff changes, explicitly noting that it does not directly call an LLM. It distinguishes itself from siblings by focusing on prompt construction for diff review, not general code review (review_code) or file review (review_file).

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 implies use when an LLM prompt for diff review is needed, and the sibling names suggest alternatives for code or file review. However, it lacks explicit guidance on when not to use this tool versus the alternatives, and there is no mention of prerequisites like having diff content ready.

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