set_document_extracted_data

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

No annotations are provided, so the description carries full burden. It confirms writing fields back and explains that extracted_data must match the folder schema, but lacks details such as whether it overwrites existing data, required permissions, error handling, or update behavior.

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 sentences, no fluff. First sentence states purpose and usage, second clarifies a parameter. Every word earns its place.

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 (indicated by context signals), the description need not cover return values. However, for a mutation tool, it should disclose behavioral context like whether this is a partial update or full replacement, and any prerequisites. It provides adequate but not complete context.

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?

The description adds meaning to extracted_data by specifying it is a JSON object string matching the folder's schema, which is not evident from the schema (just 'string'). This compensates for the 0% schema description coverage. However, document_id is not explained further.

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 uses a specific verb 'Write structured fields back onto a document' and specifies the use case 'after you run your own bring your own AI extraction', clearly distinguishing it from other document operations like get_document or upload_document.

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?

It explicitly states when to use this tool (after extraction), providing clear context. However, it does not mention when not to use it or reference alternatives among sibling tools.

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