aiQrcode

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool recognizes QR code content from images in a storage bucket, implying a read-only operation that returns extracted text. However, it doesn't describe error handling (e.g., for invalid images), performance traits (e.g., speed), or output format (e.g., plain text or structured data). For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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?

The description is a single, efficient Chinese phrase: '图片处理-二维码识别-识别存储桶内二维码图片内容'. It's front-loaded with the core purpose and avoids unnecessary words. However, it could be slightly more structured (e.g., separating function from scope) for clarity, but it's highly concise with zero waste.

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?

Given the tool's moderate complexity (QR code recognition from images), lack of annotations, and no output schema, the description is minimally adequate. It covers the basic purpose and scope but misses details like output format, error conditions, and usage context. For a tool with no structured behavioral data, it should provide more completeness to guide an AI agent effectively.

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?

The input schema has 100% description coverage for its single parameter 'objectKey', which is documented as 'COS对象键（完整路径）示例: images/qrcode.jpg' (COS object key - full path example: images/qrcode.jpg). The description doesn't add any parameter-specific information beyond what the schema provides, such as format constraints or examples. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but doesn't need to heavily.

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 tool's purpose: '图片处理-二维码识别-识别存储桶内二维码图片内容' (Image processing - QR code recognition - Recognize QR code image content in storage bucket). It specifies the verb (recognize), resource (QR code images), and scope (in storage bucket). However, it doesn't explicitly differentiate from sibling tools like 'imageSearchPic' or 'imageSearchText' that also process images, though the QR code focus is distinct.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an image in the storage bucket), exclusions (e.g., non-QR code images), or comparisons to siblings like 'imageSearchPic' for general image search. Usage is implied by the scope ('in storage bucket') but lacks explicit context.

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