zpl_compatibility

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently states what the tool reports (language posture, evidence level, size-rule findings, scope of preview) and what it never claims ('it works'). This gives the agent a clear understanding of the tool's output and limitations, which is more than most descriptions provide.

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 two sentences with zero fluff. It front-loads the purpose and immediately disambiguates from an emulator, then enumerates the output components. Every clause earns its place, and the structure is easy to parse quickly.

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?

Despite having no output schema, the description lists the key elements the tool returns (language posture, evidence level, size-rule findings, scope of preview), which gives the agent a reasonable expectation of the response. It also covers the model format. It doesn't go into exhaustive detail on output structure, but for a risk-analysis tool this is sufficient for an agent to decide whether to invoke it.

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 already describes both parameters with 100% coverage. The description adds value by giving a concrete example for the model parameter ('zebra/zd421') and clarifies the expected format (manufacturer/model). This goes beyond the schema's generic description and helps the agent construct valid input.

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 a specific verb and resource: 'Compatibility RISK analysis of ZPL code against a specific printer model'. It also distinguishes itself from an emulator and explicitly states it never says 'it works', which sets it apart from sibling tools like zpl_preview and zpl_validate. The example manufacturer/model format further anchors the purpose.

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 clear context: it is for compatibility risk analysis, not emulation, and it explicitly says 'NOT an emulator'. It also implies its role by mentioning 'reports the model's language posture', which signals it is for assessment, not validation or preview. However, it does not explicitly name sibling tools as alternatives (e.g., 'use zpl_validate for syntax checking'), leaving the agent to infer the distinction from the sibling names.

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