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qr_code

Generate QR codes from text or URLs in PNG or SVG formats. Customize size, colors, and error correction level for reliable scanning.

Instructions

Generate a QR code from text or a URL as PNG or SVG, with size, colours and error-correction level. $0.01.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
darkNo
sizeNo
textYes
lightNo
formatNopng
ec_levelNoM
output_pathNo
idempotency_keyNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.6.0

TDQS

B3.4/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It mentions the $0.01 cost, which is useful, and the generation itself implies a non-destructive operation. However, it does not disclose side effects like writing to output_path, what happens when output_path is omitted, idempotency behavior, or any input validation beyond the schema. An agent cannot predict whether the tool returns raw data or writes to a file system, which is a significant gap for a tool with 8 parameters.

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 a single, well-structured sentence that front-loads the core action ('Generate a QR code') and packs all primary features and the price into a compact format. There is no filler or redundant wording, and every phrase contributes to the agent's understanding of the tool.

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

Completeness2/5

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

Given 8 parameters, 0% schema coverage, and no output schema, the description is too sparse to be complete. It fails to explain the purpose of output_path (does it write to disk?), the role of idempotency_key, or what the tool returns when output_path is absent. The price is a nice touch, but for a tool with this complexity, the description leaves too many operational details to guesswork.

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 0%, so the description must compensate. It adds meaning to text ('text or URL'), format ('PNG or SVG'), size, colours (mapping to dark/light), and ec_level. But it omits output_path and idempotency_key entirely, leaving those parameters unexplained. The description improves on the bare schema but does not fully cover all parameters, so a score of 3 is appropriate.

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?

The description states a specific verb and resource: 'Generate a QR code from text or a URL as PNG or SVG'. It also lists key options (size, colours, error-correction level), which clearly distinguishes it from all sibling tools that handle document/image conversions or PDF operations. An agent can immediately identify what this tool does without ambiguity.

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

Usage Guidelines3/5

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

The description implies when to use the tool (whenever a QR code is needed) but provides no explicit exclusions or alternatives. Since none of the sibling tools generate QR codes, there is no direct alternative to name. The usage context is clear from the purpose, but there is no guidance on edge cases such as when not to use it or whether it should be preferred over other encoding methods.

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