generate_code_example

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

No annotations are provided, so the description bears full responsibility. It mentions generating code but offers no details on side effects, authentication requirements, output format, or constraints (e.g., supported APIs). This is insufficient for an AI agent to understand behavioral implications.

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 sentence that conveys the core purpose concisely. It is front-loaded and contains no filler, though it could be expanded with usage tips 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?

Given the absence of an output schema and annotations, the description is incomplete. It does not explain what the generated code example looks like, how to interpret the output, or any prerequisites. For a code generation tool, this information is critical.

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?

Input schema covers 100% of parameters with descriptions, so the baseline is 3. The description adds no extra meaning beyond the schema, providing no additional context or examples for parameter usage.

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's action ('Generate a complete TypeScript code example') and the target resource ('an endpoint'), distinguishing it from sibling tools like get_api_info or get_endpoint_details which return metadata or documentation.

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 implies usage (when you need a code example) but provides no explicit guidance on when to use vs alternatives like search_endpoints or get_schema_details. No when-not-to-use or alternative names are given.

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