ai_code_generate

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

The only behavioral information is the cost (40 sats per call). With no annotations, the description should disclose more about side effects, authentication, or failure modes; it does not.

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 short but mixes purpose and pricing. It is not verbose, but could be structured better (e.g., separate usage notes).

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 5 parameters and no output schema, the description lacks essential context: parameter roles, when L402 fields are needed, and what to expect in the response.

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?

The description does not explain the parameters. Schema coverage is low (40%), and the description adds no parameter-level detail. The cost note is unrelated to parameter meaning.

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 (generate code) and the input (natural-language spec). It distinguishes from many siblings (e.g., ai_summarize) but not from ai_code_review, which is a related code-focused tool.

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 on when to use this tool versus alternatives (like ai_code_review). The cost is mentioned but not the context for using L402 parameters.

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