generate_code

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

With no annotations, the description carries full burden, but it only states the generative action. It fails to disclose side effects, idempotency, error behavior, or safety implications, which is essential for a code generation 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, concise sentence with no filler. It is front-loaded with the key action and resource. However, it could be restructured to include brief usage context without losing conciseness.

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 code generation tool with no output schema, the description is insufficient. It does not explain the return format, code quality, or limitations, leaving the agent without critical information for safe invocation.

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 input schema covers both parameters with descriptions, achieving 100% coverage. The tool description does not add any extra meaning beyond what the schema states, so it meets the baseline but provides no additional semantic value.

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 identifies the tool's primary function: generating modern Zig code from natural language. The verb 'Generate' and resource 'Zig code' are specific, and the source 'natural language descriptions' distinguishes it from sibling tools that analyze, estimate, or optimize 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. It does not mention prerequisites, limitations, or typical use cases, leaving the agent to infer context from sibling names alone.

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