extract_structured

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

No annotations are provided, so the description carries the full burden. It discloses the mechanism (runs a fixed question set over PaperQA2, assembles a markdown table), and notes the prerequisite (scope must be built with index_library_pdfs()). No destructive actions implied, and the behavior is well described.

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 concise with three focused paragraphs: purpose, output format and use case, parameter details. It is front-loaded and efficient, with no unnecessary 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?

The description covers purpose, output format (markdown table with citations), parameter details, and prerequisite (indexing). With an output schema present (though not shown), the description is sufficient for an agent to understand the tool's behavior and requirements.

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 0%, but the description compensates by explaining all three parameters in the Args section: topic (subject), fields (optional comma-separated, default set), scope (index, with build note). This adds clear meaning beyond the bare schema.

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 it extracts a structured, cited evidence brief from the PDF library using a fixed question set, producing a markdown table with citations. This distinguishes it from sibling tools like search_literature or ask_library by focusing on structured extraction for systematic-review scaffolding.

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 provides the use case ('systematic-review scaffolding') and explains parameters (topic, fields, scope) but does not explicitly state when not to use it or mention alternatives among siblings, though the context is clear.

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