ocr_extract

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

No annotations provided, so description discloses internal method (space-ocr), output structure (JSON with bounding boxes), and ensures non-hallucinated data. Does not discuss auth or rate limits, but sufficient for a read tool.

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?

Two concise sentences front-load the purpose, then detail two usage paths. Every sentence adds value with no redundancy.

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?

Despite no output schema, description explains return format (JSON with extracted fields and bounding boxes) and quality guarantee. Covers all key behavioral aspects for a complex extraction tool.

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 100% schema description coverage, baseline is 3. Description adds value by clarifying that template_id auto-resolves fields/prompt, fields are for custom schemas, and prompt overrides. Adds context beyond enum 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 extracts structured data from document images, listing example types (receipt, invoice, ID) and distinguishes from sibling list_templates by specifying extraction behavior.

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?

Provides guidance on using template_id for built-in types and fields for custom schemas, plus a hint to call list_templates(). Lacks explicit when-not-to-use, but context is clear.

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