qr_read
Decode a QR code from a base64 PNG/JPEG image or image data URI and classify its content.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| image_data | Yes | Base64 image bytes or a PNG/JPEG data URI. |
Decode a QR code from a base64 PNG/JPEG image or image data URI and classify its content.
| Name | Required | Description | Default |
|---|---|---|---|
| image_data | Yes | Base64 image bytes or a PNG/JPEG data URI. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations (readOnlyHint=true) already indicate a read-only operation. The description adds 'classify its content', which is a behavioral trait beyond the annotation, providing useful context without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with the verb 'Decode', no superfluous words. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one parameter, no output schema, and adequate annotations, the description is sufficiently complete. It covers what the tool does and the input format. The classification aspect adds contextual value.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear description. The description does not add new information about the parameter beyond what the schema provides, such as constraints or format specifics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Decode', the resource 'QR code', and specifies input format 'base64 PNG/JPEG image or image data URI'. It also mentions classification, distinguishing it from sibling tools that generate QR codes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies using this tool to read QR codes, but does not explicitly state when to use it versus alternatives. Sibling tools are all generation-focused, so context is implied but not articulated.
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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Each tool targets a distinct QR code type or action: payment (single/batch), reading, text, vCard, and WiFi. No overlap in purpose; descriptions clearly differentiate.
All tools follow a consistent 'qr_<purpose>' pattern (e.g., qr_payment, qr_read). Underscores and lowercase are used uniformly.
Six tools cover the core QR generation and reading needs without being excessive. Each tool has a clear role, and the count feels appropriate for the domain.
The tool set covers common QR code types (text, vCard, WiFi) and payment QR both singly and in batch, plus a decoder. No significant gaps for the stated purpose.