assess_relevance

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

With no annotations provided, the description carries the transparency burden. It discloses meaningful behavior: results are per paper, abstracts come from OpenAlex, and the server deliberately returns evidence rather than a verdict or score. It does not mention auth, rate limits, or side effects, but the read-only screening nature is strongly implied.

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 and well-structured: purpose first, then return contents, then usage guidance. Three sentences carry all necessary information without redundancy or filler.

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, so the description needs to explain return values, and it does: abstract, scored topics and keywords, and matched/unmatched context terms. It could be more precise about the exact output structure or scoring, but it is complete enough for triage use.

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 100%, so the baseline is 3. The description reinforces the purpose of identifiers and research_context and ties research_context to term-overlap, but it does not add substantial meaning beyond the schema's own parameter descriptions.

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 leads with a specific verb and resource: 'Screen one or more papers against a research context.' It clearly distinguishes the tool by emphasizing batch triage of a whole search result set and explicitly says it returns evidence, not a verdict, which sets it apart from sibling tools like get_abstract_details or search_scopus.

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 gives clear guidance on when to use it: 'Use it to triage a whole search result set in one call, then judge relevance yourself.' It stops short of explicitly naming alternatives or stating when not to use it, but the intended workflow and division of responsibility are clear.

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