research_search_papers

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

No annotations provided, so description carries full burden. Discloses that it imports papers (mutation), returns a list with specific fields, and notes performance impacts of enrich and summarize options.

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?

Concise 4-line description with clear docstring structure. Front-loaded with purpose, parameter details in bullet list, no wasted words.

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?

Covers all 5 parameters meaningfully, mentions return structure (arXiv IDs, titles, citation counts), and notes performance trade-offs. Output schema exists, so return details need not be exhaustive.

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%, but description fully compensates by explaining query format, max_results range (1-50), primary_category as optional filter, auto_enrich as Semantic Scholar fetch, and summarize as post-import generation.

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?

Description clearly states it searches arXiv and imports papers into the local library, with specific verb (search) and resource (arXiv papers). Differentiates from siblings like research_query_library (queries existing library) and research_get_paper_details.

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?

Provides guidance on parameters like max_results, auto_enrich, and summarize with speed implications. Lacks explicit when-to-use versus alternatives but gives enough context for typical use.

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