get_paper_detail

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

No annotations are provided, so the description must disclose behavior. It mentions automatic external source fetching, which is key. However, it does not discuss error handling, network failures, or rate limits, leaving some gaps in transparency.

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: a brief statement of purpose followed by a structured argument list. Every sentence adds value, and no extra information is present.

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 simplicity (3 optional parameters, output schema present), the description covers core functionality and parameter usage. It lacks details on error handling and edge cases, but overall is complete enough for an agent to use effectively.

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?

The input schema has 0% description coverage, but the description compensates by explaining each parameter's purpose, format expectations, and constraints (e.g., 'title and URL are mutually exclusive', engine choices with default). This adds significant meaning beyond the 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 the tool gets detailed info of a single paper and automatically fetches the full abstract from an external source. This distinguishes it from sibling tools like search_papers (which returns multiple results) and analyze_relevance (which performs analysis).

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 guidance on when to use each parameter (title exact match better, URL restricted to specific engine, engine options with default and fallback). It implies usage for single-paper details but does not explicitly contrast with siblings.

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