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decode_qrcode_full

Scan any image to find and decode all QR codes, returning decoded content and diagnostic status to guide retry or enhancement actions.

Instructions

Scan the entire image for QR codes and decode them. Returns all detected codes with detailed diagnostics. Agent should decide next step based on result_code:SUCCESS → use content; SUCCESS_WITH_WARNING → check warnings;RETRYABLE → call enhance_and_decode;NO_QR_FOUND / QR_UNRECOVERABLE → inform user.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
image_urlNoPublic image URL. Use when the image is at a remote location accessible by the server.
image_pathNoLocal image absolute path — preferred when available.Pass the path string directly — zero pipe overhead, no timeout.
symbologiesNoOptional whitelist of barcode types to decode. Supported: QRCODE, EAN13, EAN8, CODE128, CODE39, CODABAR, I25, UPC-A, UPC-E, PDF417, DataMatrix, Aztec. Default (empty or omitted) = all types. Use e.g. ['EAN13'] for receipts, ['QRCODE'] for URLs.
image_base64NoBase64-encoded image. Use when the image is in memory or when a local path is unavailable. Large images are auto-resized.
Behavior4/5

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

With no annotations provided, the description carries the full burden and discloses key behavioral details: it scans the entire image, returns all detected codes with diagnostics, and defines a result_code decision tree. It could further elaborate on what 'detailed diagnostics' includes, but the provided behavior is sufficient for an agent.

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 compact—three sentences that front-load the purpose, then present a terse decision tree. Every sentence contributes value, with no redundant or filler content.

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?

Given the lack of an output schema and annotations, the description provides a solid decision framework with result_code mappings. It could specify the exact output structure, but the guidance is enough for an agent to act on the tool's results.

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 coverage is 100% with rich descriptions for each parameter, including usage precedence (e.g., image_path preferred over image_url) and examples for symbologies. The description itself adds no parameter information, but the schema already handles it, so a baseline 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 tool scans the entire image for QR codes and decodes them, which is a specific verb+resource action. It adds that it returns all detected codes with diagnostics, distinguishing it from simpler or partial decode tools.

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

Usage Guidelines5/5

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

The description explicitly guides the agent on next steps based on result_code, including a direct alternative: 'RETRYABLE → call enhance_and_decode'. It also instructs to inform the user for NO_QR_FOUND or QR_UNRECOVERABLE, providing clear usage context and alternatives.

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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