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

No annotations are provided, so the description must carry the full burden. It discloses cost (3 credits) which is helpful for budgeting, but says nothing about rate limits, permissions, or that it returns structured data according to the given schema. It is a mutation-like operation (extraction) with no safety profile disclosed.

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 short sentences, front-loaded with the purpose, followed by cost. No wasted 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?

For a tool with four parameters, including a nested schema object, no annotations, and no output schema, the description is minimal. It omits how the 'schema' parameter interacts with 'extraction_prompt', what happens if both are provided, and what the output will be, leaving the agent to infer critical behavior.

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 description coverage is 100%, so the schema fully documents each parameter. The description adds only the cost information, not parameter semantics. Baseline 3 is appropriate when the schema does the heavy lifting.

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 clear action ('Extract structured data') and input sources ('URLs or content'). However, the tool name 'documents' is opaque and doesn't clearly map to the extraction purpose, and the description doesn't distinguish it from siblings like 'scrape' or 'research' which also handle web content.

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?

No guidance is given about when to use this tool versus alternatives such as 'scrape' (which likely fetches content) or 'research'. The relationship to scrape is implied only by the 'Pre-scraped text content' param, leaving the user to infer that this tool is for extraction, not scraping.

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