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jan3dev

Agentic AQUA

by jan3dev

qr_decode

Decodes a QR code from an image file and returns the raw string content, supporting Bitcoin addresses, Liquid addresses, Lightning invoices, and Lightning addresses.

Instructions

Decode a QR code from an image file and return the raw string content. Supports Bitcoin addresses, Liquid addresses, Lightning invoices (BOLT11), and Lightning addresses.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
image_pathYesAbsolute path to the image file containing the QR code (PNG, JPG, WEBP supported)
Behavior3/5

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 supported image formats via the parameter description but does not mention error handling, file system access requirements, or any side effects. The behavioral transparency is adequate but not thorough for a tool with no annotations.

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 incredibly concise with two sentences that front-load the main action and then provide additional context about supported content types. There is no redundant or unnecessary information.

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?

For a simple tool with one parameter and no output schema, the description is fairly complete. It explains the input format, main function, and types of output expected. However, it does not discuss error conditions or what happens when decoding fails, which would be beneficial for an AI agent.

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% for the single parameter, so the schema already explains its meaning. The tool description adds context about supported content types, which is more about the tool's output than the parameter itself. No additional parameter-level guidance is needed, so a baseline 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 clearly states the verb (decode), resource (QR code from image file), and outcome (raw string content). It also lists supported content types, making the tool's purpose unambiguous and distinguishing it from sibling tools like lightning_decode.

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 provides context by listing supported content types, implying when to use this tool (for Bitcoin addresses, Lightning invoices, etc.). However, it lacks explicit guidance on when not to use it or alternatives, such as limitations to specific image formats or that it may not support other QR code types.

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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