recommend_papers

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'citation network analysis' but does not explain how recommendations are generated, whether the tool modifies state, what kind of graph is expected, or what the response contains. This is a significant gap.

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 a single concise sentence with no filler or repetition. However, it is under-specified rather than truly concise; while the structure is clean, the missing details prevent it from being excellent.

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 that there are three parameters, no output schema, and no annotations, the description is inadequate for an agent to correctly invoke the tool. It does not explain the required graph format, how seed_doi is used, or what the return value looks like, making the description incomplete for the tool's complexity.

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 zero description coverage, and the description does not define parameters such as graph, seed_doi, or max_recommendations. The phrase 'citation network analysis' weakly implies that graph is a citation network and seed_doi is a starting point, but this is far from explicit and offers little value beyond what the parameter names suggest.

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 recommends papers using citation network analysis, which is a specific verb and resource. It stands apart from sibling tools like pagerank or analyze_author_impact by naming the 'recommend' action, though it does not explicitly contrast itself with those alternatives.

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?

No guidance is provided on when to use this tool versus alternatives such as build_citation_network or analyze_author_impact. There are no stated prerequisites, expected inputs, or exclusions, leaving the agent to infer usage context from the name alone.

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