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generate_qr_code

Create custom-styled QR codes from URLs or text, generating base64-encoded SVG images with multiple visual design options for saving or display.

Instructions

Generate a QR code with custom styling. Returns base64-encoded SVG image data that can be saved or displayed. Supports multiple visual styles.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe URL or text content to encode in the QR code
styleNoVisual style preset for the QR code. Default: slate-ember
sizeNoQR code dimensions in pixels. Default: 768. Range: 256-2048
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It discloses that the tool 'Returns base64-encoded SVG image data that can be saved or displayed,' which is useful behavioral context. However, it lacks details on permissions, rate limits, error handling, or whether the operation is idempotent—critical for a generation tool with no annotation coverage.

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?

The description is appropriately sized and front-loaded, with two sentences that efficiently convey the core functionality and output. Every sentence adds value: the first defines the action and output, the second notes styling support. No wasted words, though it could be slightly more structured for a perfect 5.

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?

Given the tool's moderate complexity (3 parameters, no output schema, no annotations), the description is partially complete. It covers the output format and styling but lacks details on error cases, performance, or integration with siblings. Without annotations or output schema, more behavioral context would improve completeness for safe agent use.

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?

The description adds minimal value beyond the input schema, which has 100% coverage. It mentions 'custom styling' and 'multiple visual styles,' hinting at the 'style' parameter, but doesn't elaborate on the semantics of styles or other parameters. With high schema coverage, the baseline is 3, as the schema already documents parameters well.

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 clearly states the tool's purpose: 'Generate a QR code with custom styling.' It specifies the verb ('Generate') and resource ('QR code'), and mentions the output format ('base64-encoded SVG image data'). However, it doesn't explicitly differentiate from sibling tools like 'generate_qr_urls_batch' (batch processing) or 'preview_qr_url' (preview functionality), which would be needed for a score of 5.

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?

The description provides no guidance on when to use this tool versus alternatives. It mentions 'custom styling' and 'multiple visual styles,' but doesn't compare to siblings like 'generate_qr_urls_batch' for bulk operations or 'preview_qr_url' for testing. There's no explicit when/when-not usage context, leaving the agent to infer based on tool names alone.

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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