find_related_research

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

No annotations are provided, so the description is the sole source of behavioral info. It mentions data sources (OpenCitations, Crossref, DataCite) and coverage (publications, datasets, software) but omits details like rate limits, DOI-not-found handling, or whether full records are returned. The output schema fills some gaps but the description itself lacks full 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, well-structured with bullet points, and front-loaded with the core purpose. Every sentence adds value without redundancy.

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 only 2 parameters, no annotations, and an existing output schema, the description covers purpose, usage scenarios, data sources, and param behavior. It is complete for an agent to decide when and how to invoke the tool.

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 100% schema coverage, the baseline is 3. The description adds value with examples for 'doi' and explains 'limit' default (200) and automatic pagination. This goes beyond the schema's minimal documentation.

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 finds publications, datasets, and software that cite a given DOI, using a specific verb ('find') and resource. It distinguishes itself from sibling tool 'get_metadata' by focusing on citation links rather than metadata retrieval.

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 explicitly lists four use cases under 'Use this tool when you want to:' (e.g., find what publications cite a dataset). It provides clear context but does not explicitly state when not to use it or compare with alternatives.

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