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Zovo QR Code Maker

Generate text QR code

generate_text_qr_code
Read-onlyIdempotent

Use this when the user wants a PNG and SVG QR image that displays plain text when scanned. Accepts up to 1,500 characters, preserves whitespace, and reports contrast, density and optional print width. Encoded UTF-8 content must fit 1,273–2,953 bytes depending on error correction. Static codes only; does not read QR images or make barcodes or Wi-Fi codes.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "generate_text_qr_code"
  }
}

Input Schema

NameRequiredDescriptionDefault
textNoPlain text to encode, up to 1,500 characters; whitespace is preserved. Example: Table 12 - ask for the specials.
backgroundNoBackground colour as hex, e.g. #FFFFFF (default).
foregroundNoCode (module) colour as hex, e.g. #111111 (default). Dark colours scan best. Basic colour names like navy or black also work.
error_correctionNoDamage tolerance, e.g. M: L 7%, M 15% (default), Q 25%, H 30%. Use H for printed codes that may get scuffed or carry a logo sticker.
scan_distance_cmNoOptional distance in centimetres from which people will scan the printed code, e.g. 300 for a poster across a room; used to recommend a minimum print size.

Output Schema

NameRequiredDescriptionDefault
svgYes
kindYes
modulesYes
payloadYes
requestYes
summaryYes
versionYes
warningsYes
downloadsYes
backgroundYes
foregroundYes
contrast_ratioYes
error_correctionYes
min_print_size_cmYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Beyond the annotations, the description discloses important behavioral constraints: the 1,500-character limit, whitespace preservation, static-only codes, UTF-8 byte budgets depending on error correction, and reported contrast/density/print-width details. This is substantial context that helps the agent avoid incorrect expectations for a read-only, idempotent generation tool.

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

Conciseness5/5

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

The description is front-loaded with the primary use case, followed by concise constraints and exclusions. Every sentence contributes relevant selection or invocation information without redundancy.

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

Completeness5/5

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

The tool has rich annotations, full schema descriptions, and an output schema, so the description does not need to explain return values in detail. It still covers the main use case, key limits, output image formats, and exclusions, making it complete enough for correct tool selection and invocation.

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

Parameters4/5

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

Schema description coverage is 100%, so the parameters are already well documented. The description still adds useful meaning beyond the schema by explaining the encoded-content byte budget and its dependency on error correction, which is not obvious from the individual parameter descriptions alone.

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?

The description gives a specific verb and resource: generating a PNG/SVG QR image that displays plain text. It is clear and precise, but it does not explicitly distinguish this tool from the sibling generate_qr_code, so sibling differentiation is left implicit.

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?

It clearly states when to use the tool ('when the user wants a PNG and SVG QR image that displays plain text') and gives exclusions ('does not read QR images or make barcodes or Wi-Fi codes'). It does not explicitly route the agent between this tool and the sibling generate_qr_code, so it falls short of full when/when-not/alternative 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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