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

The description adds behavioral details beyond annotations: insertion location, return of modified code plus diagnostics, and side-effect-free claim. Annotations indicate not read-only and not destructive, which aligns with the description's side-effect-free assertion (no permanent state change).

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 three sentences, with a clear front-loaded usage statement. The third sentence about faceLabels and lookup_api is relevant but somewhat tangential; it could be separated. Overall, it is concise and well-structured.

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 presence of an output schema and annotations, the description covers key aspects: insertion logic, return value, side-effect-free nature, and an advanced tip. It could mention edge cases (e.g., no return statement) but is sufficient for typical usage.

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 coverage is 100% with descriptions for both parameters. The description adds an example for feature_code, clarifying the expected format and syntax beyond the schema's 'Single-statement source line to insert'. This provides practical guidance.

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 verb 'insert' and the resource 'new feature line into a script', with precise location 'before the last top-level return statement'. This distinguishes it from sibling tools like add_constraint or add_part, which add different script elements.

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 begins with 'Use this when you need to insert a new feature line into a script', providing a clear use case. It also mentions side-effect-free behavior and a tip about faceLabels, but does not explicitly exclude when not to use it or compare to alternatives like add_connector.

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