ocr_batch_vision

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 backend details (Apple Vision, GPU/ANE inference), platform requirement (macOS 10.15+), language support, and that results are 'consolidated'. This adds meaningful context beyond the basic operation, though it does not detail output structure or error behaviors.

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 and front-loaded with the main action, then adds backend context in a separate section. Each sentence serves a purpose, but the backend details could be integrated more smoothly without affecting clarity.

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?

With no output schema and no annotations, the description should reasonably explain return values and parameter usage. It covers the main functionality but leaves out specifics about the 'consolidated results' format and how to use 'lang' and 'mode', making it minimally adequate rather than fully complete.

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 does not compensate by explaining the parameters (paths, lang, mode). While 'paths' is self-explanatory, 'lang' and especially 'mode' remain ambiguous without any semantic detail beyond their default values.

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 function: 'OCR multiple images at once' with a specific verb and resource scope. It distinguishes itself from siblings by emphasizing batch processing and the 'vision' backend, which aligns with the sibling names (ocr_batch_vision vs single-image variants and other backends).

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 context on when the tool is appropriate: 'Best for CJK + major European languages' and 'Zero install on macOS'. It implies a preference for Apple Vision over other backends, but does not explicitly mention alternatives or exclusion criteria, so it falls short of a 5.

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