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labelixa-mcp

labelixa-mcp

Official
by Labelixa
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

zpl_compatibility

Analyze ZPL code for compatibility risks against a given printer manufacturer/model, reporting language posture, evidence level, size-rule findings, and preview scope without a print guarantee.

Instructions

Compatibility RISK analysis of ZPL code against a specific printer model, given as manufacturer/model (e.g. 'zebra/zd421'). NOT an emulator and never says 'it works': reports the model's language posture with evidence level, size-rule findings and the scope of our preview.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "zpl": "<zpl>",
      "model": "<model>"
    },
    "name": "zpl_compatibility"
  }
}

Input Schema

NameRequiredDescriptionDefault
zplYesRaw ZPL code
modelYesPrinter model as manufacturer/model, e.g. zebra/zd421

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.5.2
    • removedInput schema / additionalProperties
      Removed value: -false
  2. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

No annotations exist, so the description carries the burden and does well: it discloses the epistemic posture ('never says it works'), the evidence-level reporting, the size-rule findings, and the preview scope. It doesn't cover determinism, cost, or whether the analysis is static vs simulated beyond the emulator disclaimer, leaving a small gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose is front-loaded in the first clause with the model-format hint immediately after, and the negative framing follows as a guardrail. Dense but essentially waste-free; slightly overpacked into long clauses.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With two fully documented params, no output schema, and no annotations, an agent needs to know what comes back and what the result does not claim — the description covers both (language posture with evidence level, size-rule findings, preview scope, no 'it works' verdict). Minor gaps remain around output shape and whether unsupported models produce an error.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and both parameters are already documented, including the manufacturer/model example. The description repeats the 'manufacturer/model (e.g. zebra/zd421)' format rather than adding new semantics, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Compatibility RISK analysis of ZPL code against a specific printer model') with the exact input format expected. It also pre-emptively separates itself from the emulation/preview siblings by saying 'NOT an emulator' and referencing 'the scope of our preview', so an agent can distinguish it from zpl_preview and zpl_validate without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Clear about the context of use (risk assessment for a given model, not a pass/fail guarantee) and explicitly excludes the emulator interpretation, which is the most likely misread against zpl_preview. It stops short of naming siblings like zpl_validate or stating when to prefer those, so it isn't full routing guidance.

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

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