search_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 explains the embedding model, dimensions, similarity ranking, and the vector_name feature for searching different summary dimensions. It does not describe the output structure, but the output schema exists, and the search operation is inherently read-only.

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 dense paragraph that leads with the core purpose and method, then adds filter options and vector_name details. It is longer than strictly necessary but every sentence contributes useful information without repetition or fluff.

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 complexity (14 parameters) and the presence of an output schema, the description is remarkably complete. It covers the embedding mechanism, query semantics, structured filters, and vector_name customization, providing the agent with sufficient context to select and invoke the tool correctly.

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 successfully explains the meaning of major filter parameters (year, venue, collection acronym/id, field of study, author) and vector_name. However, limit and min_score are not explicitly described beyond their inferred names, leaving a minor semantic gap.

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 identifies this as a semantic search tool for ACL conference papers, with a specific verb ('Semantic search'), a defined resource, and a distinctive method (embedding with Sentence-Transformers and cosine similarity). It distinguishes itself from siblings like list_papers and get_paper by emphasizing ranked relevance search.

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 states when to use the tool: 'USE THIS when the user has a research topic or question and wants to find relevant papers.' This gives clear usage context, but it does not mention when to use alternatives (e.g., list_papers or get_paper), so it stops short of a full when/when-not comparison.

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