ask_research_question

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

With no annotations provided, the description carries the full burden. It transparently describes the process: searches academic papers, uses an LLM to synthesize, and provides citations. It implies a read-only query operation, though it does not mention specific limits or auth requirements. No contradictions.

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 highly concise, with a clear opening sentence, a one-line explanation of the process, and well-structured args and returns sections. Every sentence adds value, and the format is easy to parse.

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 tool's low complexity, the description covers the essential aspects: what it does, how it processes, the output format. It mentions return values (answer with citations and DOIs), which compensates for the lack of visible output schema. Slightly more detail on edge cases or limitations would push it to 5.

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%, so the description must compensate. It explains the 'question' parameter with an example and clarifies 'num_references' with default (8) and max (15), adding meaning beyond the schema's type and constraints.

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 tool asks a research question and gets an AI-generated answer with citations. It distinguishes from siblings like search_papers (which returns papers) and get_paper_details (which gives details). The verb 'ask' and resource 'research question' are specific and clear.

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 explains when to use the tool (to ask a research question) and provides an example. It does not explicitly state when not to use it or mention alternatives, but the context of siblings implies its unique role in synthesizing answers rather than just searching or retrieving details.

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