extract_paper

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

With no annotations, the description carries the full burden and does so: it warns summaries may be incomplete or inaccurate, notes the first call downloads model weights if uncached, that calls are serialized due to memory limits, that cached chunks resume after interruption, and that partial extraction is labeled. This is unusually rich operational context.

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?

Front-loaded with the most decision-relevant fact (LEGACY/SLOW/OPTIONAL) and every subsequent sentence carries distinct information: cost, preference, resumption, and return value. No filler.

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?

No output schema exists, and the description covers the return value (summary_id for read_summary) as well as runtime cost and failure modes. An agent has everything needed to decide whether and how to call it.

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 coverage is 0% for two parameters. The description clarifies the question parameter ('Use the original research question') but says nothing about paper_id semantics or format. It compensates for one of two parameters, so it lands at a minimum-viable 3.

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 verb+resource (read every body chunk, save a summary) and immediately distinguishes itself from siblings by naming the preferred alternative (index_papers + retrieve_evidence). The 'LEGACY, SLOW, OPTIONAL' prefix makes its role unambiguous without opening any schema.

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?

Explicitly says to prefer index_papers + retrieve_evidence and that this tool is not part of the default RAG workflow, plus the concrete condition 'Use the original research question'. Both when-to-use and when-not-to-use are spelled out.

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