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ChartQuery MCP Server

ChartQuery MCP Server

by chartquery
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TypeScript
Hybrid

Label Validate

label_validate
Read-only

Validates raw printer commands for TSC, ZPL, EPL, and other languages by submitting source and language, helping catch syntax or format issues before printing.

Instructions

Label Validate. Validate printer commands. POST source (the raw commands) and language (tsc, zpl, epl, …). Credit cost: 1 credit per call.

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": {
      "source": "<source>",
      "language": "<language>"
    },
    "name": "label_validate"
  }
}

Input Schema

NameRequiredDescriptionDefault
fieldsNoComma-separated list of fields to keep in the response, with dot notation for nested fields (e.g. name,location.city). Does not change the credit cost.
sourceYesRaw printer commands to validate. Also send language.
languageYesLanguage of the source commands. Example: tsc or zpl. Allowed values: tsc, zpl, epl, cpcl, dpl, sbpl, ipl. Default: "tsc".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds genuinely useful non-schema behavior — a cost of 1 credit per call — but says nothing about what a validation result looks like (pass/fail, error listings, partial tolerance), which is the main thing an agent needs before committing a credit.

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?

Three short sentences, front-loaded with purpose and with the credit cost stated last where it is easy to find. The opening 'Label Validate.' merely repeats the title and could be dropped.

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

Completeness3/5

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

For a simple read-only validation tool with full schema coverage and no output schema, the definition covers purpose, required inputs, and cost. It stops short of describing the validation outcome or failure modes, which leaves an agent guessing about what it will get back for its credit.

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 description coverage is 100%, including allowed language values and the fields projection parameter, so the schema carries the load. The description's parenthetical '(the raw commands)' and the 'tsc, zpl, epl, …' list duplicate what the schema already documents, adding no new meaning.

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

Purpose4/5

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

States a specific verb+resource: 'Validate printer commands' taking raw label source in a given language. However, it draws no boundary against the many similar siblings (label_parse, label_compile, label_convert, label_render, label_view), so an agent cannot tell from the description alone which of those it wants.

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

Usage Guidelines2/5

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

There is no when-to-use or when-not-to-use guidance and no named alternative among the label_* siblings. The only procedural hint is 'POST source ... and language', which restates the required parameters rather than helping selection.

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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