research_get_paper_details

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

No annotations are provided, so the description carries the burden. It discloses the tool returns metadata, citation metrics, summaries, and ideas, implying it is a read-only operation. However, it does not mention error handling for missing papers or prerequisites like the paper being in the library.

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 extremely concise with two sentences plus an Args section, front-loading the purpose and immediately providing parameter details without any superfluous content.

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 has one parameter, an output schema, and low complexity, the description adequately explains what is returned and the parameter format. It could mention the requirement that the paper exists in the library, but overall it is sufficiently complete.

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?

With 0% schema description coverage, the description adds value by clarifying the arxiv_id format ('Normalized arXiv ID (e.g. 2106.00001)'), which is not obvious from the schema alone.

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 retrieves 'full metadata, citation metrics, summaries, and ideas' for a specific paper, distinguishing it from sibling tools like 'research_search_papers' (searching) and 'research_remove_paper' (removing).

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 implies usage for papers already in the local library and specifies the arxiv_id format, but does not explicitly guide when to use this tool over siblings like 'research_generate_summary' or 'research_generate_ideas'.

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