id_card_ocr

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

With no annotations, the description must cover behavioral traits. It explains what fields are returned per side but does not disclose image requirements, error handling, or authentication needs. The read-only nature is implicit but not explicitly stated.

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 with two well-structured sentences. The first sentence states the core purpose, and the second sentence adds detail and use cases without unnecessary words.

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 simplicity of the tool (2 parameters, no output schema), the description adequately covers the return fields for each side. However, it could be more complete by mentioning the output format (e.g., JSON object) and any image constraints.

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 coverage is 100%, so the description adds limited parameter-level meaning beyond the schema. The 'side' parameter's enum values are described, but no additional detail about the 'image' parameter is provided beyond what the schema already states.

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 extracts structured data from a Chinese national ID card, specifies front and back side fields, and lists use cases. It distinguishes itself from sibling OCR tools for other document types.

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 by stating best-fit use cases (identity-data prefill, document digitization, onboarding automation). However, it lacks explicit guidance on when not to use this tool versus alternatives like driver_license_ocr or bank_card_ocr.

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