content_extract

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

Adds valuable implementation context beyond annotations: explicitly mentions 'Gemini's response_json_schema' as the underlying mechanism and warns of 'error dict on parse failure'. Annotations already indicate read-only/open-world status, so these details supplement rather than duplicate safety information.

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?

Well-structured docstring format with clear separation of description, Args, and Returns. Front-loaded with the core purpose. Minor redundancy between Args section and input schema, but acceptable given the clarity it provides. No wasted sentences.

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?

Adequate for a tool with existing output schema and safety annotations. Mentions error handling behavior and implementation details (Gemini). Could optionally mention size limits or schema complexity constraints, but complete enough for basic invocation decisions.

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?

Input schema has 100% description coverage ('Text content to extract from', 'JSON Schema defining the extraction structure'). The Args section in the description provides nearly equivalent information, meeting the baseline of 3 without adding significant semantic depth beyond the schema definitions.

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?

States a specific action (extract structured data) and mechanism (using JSON Schema). Clear verb-resource combination. Distinguishes implicitly from content_analyze by specifying 'structured data' and schema-driven extraction, though lacks explicit contrast with siblings.

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 implied usage context through mention of 'structured data' and 'JSON Schema', signaling when to use (schema-defined extraction) vs general analysis. However, lacks explicit when-to-use guidance or named alternatives from the sibling list (e.g., content_analyze).

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