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

Annotations are empty, so description must disclose behavior. It mentions the dataset size and result content but omits details on pagination, rate limits, authentication, or whether results are read-only. For a search tool with no annotations, this is insufficient.

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?

Single sentence under 20 words, front-loaded with verb 'Search', no redundant information. Every word is functional.

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 simplicity (2 parameters, no output schema), the description covers purpose and result types well. However, it could mention that it returns a list of works and the default limit behavior, which is already in the schema. Minor gap.

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 covers 100% of parameters with descriptions. The description adds context about result content (institution data, bibliometrics) but does not enhance parameter meaning beyond the schema, so baseline 3 is appropriate.

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 includes specific verb 'search', resource 'works via OpenAlex', and distinctive data types (institution data, bibliometrics, citation counts), effectively differentiating from sibling search tools like search_arxiv and search_pubmed.

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?

No explicit guidance on when to use this tool over alternatives such as search_arxiv or search_papers; the description implies usage context through data types but lacks when-not-to-use or exclusion criteria.

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