ai-tools__fix_code

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

With no annotations and no output schema, the description carries the full burden of behavioral disclosure. It only says 'fixes' but does not state whether it returns corrected code, modifies anything persistently, requires an existing file, or produces any diagnostics. This is a significant gap for an operation-oriented tool.

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 clear sentence with no redundant wording. The '[AI Code Analysis]' prefix adds minor branding context but does not hurt clarity. It could arguably be more informative, but it earns its place as concise.

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 simple two-parameter tool, the description is minimally viable: it names the operation and the inputs are well-described by the schema. However, the lack of any output/return behavior or usage context leaves an agent guessing about what the tool actually produces, which is a meaningful gap.

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 schema already documents both parameters clearly. The description adds no further semantic value beyond the schema, but it does not need to because the parameter names and descriptions are self-explanatory.

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 action (fixes bugs or issues) and the resource (given code). It distinguishes itself from siblings like explain_code or review_code by implying a modification operation, though it does not explicitly differentiate itself from edit_code.

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?

No guidance is provided about when to use this tool versus alternatives. The description implies use when code has a known issue, but it does not mention exclusions or clarify how it differs from ai-tools__edit_code or ai-tools__test_code.

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