search_papers

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

With no annotations, the description carries the full burden and does well: it discloses the return shape (titles/abstracts), the post-processing contract (instructs the MAIN LLM to rerank), null-abstract handling, explicit counts/errors, and an important caveat that 100 unique papers is not guaranteed. It does not cover auth, rate limits, or API failure handling, which keeps it from a 5.

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 core behavior and default are front-loaded in the first two sentences, and each following sentence carries a distinct piece of information (param semantics, return handling, caveats) with no filler. Line breaks aid scanning rather than padding.

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?

There is no output schema or annotations, so the description must cover both invocation and result semantics; it covers returns, reranking handoff, counts, errors, and a key guarantee caveat. What is missing is only secondary: failure behavior if one source errors and how to paginate beyond the candidate cap.

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, and it does: it distinguishes query ('a concise keyword search') from question ('the full research question') and explains per_source_limit's default and totals (100 candidates across both sources). This is meaningful semantic detail beyond the bare schema types, though formats/lengths are unstated.

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 states a specific verb and resource and names both upstream sources ('Get up to 50 DOI-bearing candidates each from OpenAlex and Semantic Scholar'), which makes the retrieval behavior concrete. It does not explicitly contrast itself with siblings such as index_papers or retrieve_evidence, so an agent must infer the boundary, keeping it below a 5.

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?

It gives clear guidance on one parameter's usage ('Default to per_source_limit=50... Reduce only when the user explicitly requests a smaller search'), which is useful operational context. However, it never says when to choose this tool over the sibling search/retrieval tools, leaving the main routing question implied.

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