local_explain_code

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

Annotations declare readOnlyHint=true, and the description reinforces this by stating the code is read server-side and does not enter Claude's context. It also reveals that a local model generates the explanation, implying potential limitations.

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 well-structured but slightly verbose, with some repetition (e.g., 'Revisa la explicación: la genera un modelo local' echoes earlier statements). It could be more 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?

Given 3 parameters, an output schema, and no complex nested objects, the description adequately covers what the tool does, when to use it, and how to use it. It leaves no critical gaps.

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?

With 0% schema coverage, the description compensates by explaining the three parameters: code, path (mutually exclusive), and question (optional). It adds clarity on usage beyond the schema types.

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 explains code in prose using a local model, and explicitly distinguishes it from reading files with Read, especially for large files. It lists the parameters and their purposes.

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 gives explicit guidance on when to prefer this tool over Read (large files, need explanation not literal content), but does not compare with sibling tools like local_summarize or local_classify.

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