ocr_paddle

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 behavioral aspects such as the impact of the 'use_angle_cls' parameter, accuracy/speed claims, and the return structure (dict with text and optional regions). It does not cover potential side effects or failure modes, but for a read-only extraction tool this is sufficient.

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 concise, using a short introductory paragraph followed by a bulleted 'Best for' list and a structured Args section. Every sentence adds value; no filler or repetition. The formatting aids readability and quick scanning.

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 presence of an output schema and the complexity of the tool (4 parameters, 1 required), the description covers all necessary aspects: purpose, use cases, parameter details, and return value summary. It is complete and leaves no obvious gaps for an AI agent to use the tool correctly.

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?

With 0% schema description coverage, the description adds significant meaning: for 'image_path' it specifies absolute/relative path and supported formats; for 'language' it lists example codes; for 'detail_level' it defines 'normal' vs 'high'; and for 'use_angle_cls' it explains the behavior when True. This goes well beyond the schema's bare type/default information.

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 starts with a clear action verb and resource: 'Extract text from an image using PaddleOCR'. It distinguishes itself from sibling tools like 'describe_image' and 'ocr_image' by detailing specific use cases (multi-language, CPU-only, high-volume) and mentioning superior accuracy over general vision models.

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 explicit guidance on when to use this tool: 'Best for: Multi-language documents, CPU-only servers, High-volume batch OCR'. It implies when not to use by contrasting with general vision models, but does not explicitly state alternatives or exclusions for other sibling tools.

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