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

No annotations are provided, so the description carries the behavioral disclosure burden. It does disclose the key behavior: statically linting CPCL input and returning JSON findings with severity and position. However, it does not mention error behavior, response structure nuances, or whether any external calls occur, leaving some behavioral uncertainty.

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 with the primary verb front-loaded. Every clause earns its place: the action, the target format, and the output type. No filler or redundancy.

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 one-parameter, side-effect-light linter, the description provides a usable input/output contract. The main gap is that no output schema exists and the description does not specify the exact shape or field names of the returned JSON findings, so an agent may need to infer how to consume them.

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 description coverage is 100%; the schema already describes the single parameter as 'Raw CPCL code'. The description's mention of 'CPCL label code' adds no new semantic detail such as encoding, format constraints, or examples.

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 names a specific verb ('Lint'), a specific resource ('CPCL label code'), and the return form ('positioned findings with severity as JSON'). This clearly distinguishes it from render-oriented siblings like cpcl_preview and from validators for other languages such as zpl_validate.

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 no explicit when-to-use guidance and names no alternatives or exclusions. An agent must infer from the tool name and the word 'CPCL' that this is for validating CPCL code rather than e.g. using zpl_validate or rendering via cpcl_preview.

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