Validate CPCL label code and receive a structured diagnostics report with error positions and severity to fix label formatting issues before printing.
Lint/validate CPCL label code and return the structured diagnostics report (findings with positions and severity) as JSON.
| Name | Required | Description | Default |
|---|---|---|---|
| cpcl | Yes | Raw CPCL code |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While it mentions 'lint/validate' and 'return the structured diagnostics report (findings with positions and severity) as JSON', it does not explain what happens on invalid input (e.g., error messages, exit codes), whether it mutates anything (it shouldn't, but it's not stated), or if there are any side effects. For a read-only validation tool, the lack of explicit non-destructive confirmation is a gap.
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, complete sentence that is front-loaded with the core action ('Lint/validate CPCL label code') and then details the output. It has no filler words and every part earns its place.
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 tool with a single parameter and no output schema, the description covers the main purpose and return type. However, it lacks important context such as example input/output, error handling, or limitations. Given the simplicity, it is adequate but not exhaustive.
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 schema describes the parameter ('cpcl') with a description 'Raw CPCL code'. The tool description adds the context that this code is 'label code' to be validated, but it doesn't add syntax or format details (e.g., encoding, maximum length). Since schema coverage is 100%, the baseline is 3, and the description adds only marginal value by clarifying the purpose of the parameter.
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 what the tool does: 'Lint/validate CPCL label code' and specifies the resource (CPCL label code). It distinguishes itself from siblings like zpl_validate by explicitly focusing on CPCL, which is a different label language. The verb 'Lint/validate' is specific and action-oriented.
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 does not provide any guidance on when to use this tool versus alternatives. It doesn't mention scenarios where CPCL validation is preferred over other validation tools (e.g., zpl_validate, epl_validate, tspl_validate). There are no explicit exclusions or conditions, leaving the agent to infer usage from the language name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.