ocr_text_paddleocr_vl

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

With no annotations, the description carries the full burden. It discloses output structure (full text, per-line confidence, bounding boxes), backend/model details (PaddleOCR-VL 0.9B), hardware requirement (Apple Silicon M1+), and external dependency (paddleocr-vl Swift CLI). It stops short of explicitly stating that the tool is read-only or how it handles errors, but the described behavior is transparent for a typical OCR read operation.

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 appropriately sized, front-loaded with purpose and output, then gives relevant backend context. Each sentence provides useful information without repetition. Slightly verbose in the backend block but still efficient.

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?

The description covers output, backend, hardware, and dependencies, but lacks parameter semantics and explicit guidance on mode/lang behavior. Without an output schema, it compensates with output structure, but the missing param details leave the context incomplete for full usage.

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 description coverage is 0%, and the description adds no explanation of the parameters (path, lang, mode). It does not mention what lang or mode do, default values, or acceptable values. This is a critical gap for an agent to invoke the tool correctly.

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 'Extract text from an image' and lists specific outputs (full text, per-line confidence, bounding boxes). It also names the backend (paddleocr_vl) and highlights differentiators (most accurate, 109 languages, supports tables/formulas/charts), which distinguishes it from sibling OCR tools like ocr_text_vision and ocr_text_paddle.

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 when to use this tool by citing 'Most accurate, 109 languages, supports tables/formulas/charts' and noting the Apple Silicon requirement. However, it does not explicitly mention when to prefer alternatives or what trade-offs exist (e.g., speed vs accuracy). So clear context but no explicit exclusions/alternatives.

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