ocr_table_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 external dependency (Swift CLI), platform requirement, and output format (CSV/JSON), which is useful. However, it does not mention whether the operation is read-only, potential side effects, error conditions, or performance characteristics, leaving gaps.

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 front-loaded with the core action and then provides backend context in a second paragraph. It is reasonably concise, though the backend details could be slightly tightened without losing value.

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 has 3 parameters, no schema descriptions, no annotations, and no output schema, the description is not complete enough. It leaves lang and mode ambiguous and does not fully clarify prerequisites or behavior, making correct usage uncertain.

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 provides no parameter-specific meaning. The '109 languages' phrase hints at the lang parameter, but mode and path are not explained at all. The description fails to compensate for the lack of schema documentation.

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 first sentence 'Extract tables from an image' clearly states the specific verb (extract) and resource (tables from an image), with output mentioned. The backend name 'paddleocr_vl' distinguishes it from sibling tools like ocr_table_paddle and ocr_table_vision.

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 clear usage context: it is the 'Most accurate' backend and supports 109 languages, implying it is the preferred choice for accuracy. It also specifies a prerequisite ('Requires paddleocr-vl Swift CLI') and platform limitation (Apple Silicon M1+). However, it does not explicitly name alternatives or exclusions, so it stops 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.