code_review_local

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

No annotations provided. Description indicates it is a read-only, safe operation (quick review) but does not disclose any potential side effects, limitations, or failure modes. It adds moderate context beyond annotations (none) but lacks depth.

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?

Description is three concise sentences: purpose, usage guideline, and parameter description. No wasted words, and key information is front-loaded.

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?

Tool has two parameters (one required) and an output schema (not shown but exists). Description does not cover return values, but output schema handles that. It lacks mention of prerequisites or edge cases, but overall adequate for a simple 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?

Schema description coverage is 0%, so description must compensate. It explains the 'diff_or_code' parameter as 'A unified diff or a code block to review,' adding clarity. However, the 'model' parameter is not described at all in the description, leaving some ambiguity.

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?

Description clearly states it performs a 'quick first-pass code review' using the local model, catching 'obvious bugs, style issues, and risky patterns.' It distinguishes itself from a deeper cloud model review, and no sibling tool has a similar purpose.

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?

Explicitly recommends using this tool as a 'cheap pre-filter before asking the cloud model for a deeper review.' This gives clear context on when to use it. However, it does not explicitly mention when not to use it or name specific alternative tools.

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