content_extract

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

Annotations already indicate read-only and open-world behavior. The description adds that it uses Gemini's response_json_schema for guaranteed structured output, providing insight into the mechanism and output reliability. However, it does not disclose potential limitations or error conditions.

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 extremely concise and front-loaded, consisting of two clear sentences without any unnecessary words. Every part contributes to understanding.

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 presence of an output schema and adequate annotations, the description is sufficiently complete for this tool. It explains the core functionality and the mechanism (Gemini's JSON schema output). Minor improvements could include mentioning that the schema must be a valid JSON Schema, but this is implied by the input schema description.

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 coverage is 100% with both parameters described. The description adds minimal extra meaning beyond the schema, as it simply restates the purpose of the schema parameter. Baseline score of 3 is appropriate.

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 action (extract), the resource (content), and the method (using a JSON Schema). It distinguishes itself from sibling tools like content_analyze and content_batch_analyze by focusing on structured extraction rather than analysis.

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 implies usage for extracting structured data with a schema but does not explicitly mention when to use it versus alternatives like content_analyze. No exclusions or alternative suggestions are provided.

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