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

Annotations already signal readOnly and openWorld, and the description adds behavioral context by listing the exact returned data elements (e.g., h-index, ORCID, most-cited works). This goes beyond the annotation's safety profile, though it doesn't discuss ambiguity resolution for common names or pagination behavior.

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?

Two sentences, front-loaded with the core function and value, then a compact list of outputs and use cases. No filler or redundancy.

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 output schema exists (return values are handled elsewhere), the description sufficiently covers the tool's purpose, key behaviors, and typical use. It doesn't mention potential edge cases like ambiguous author names, but the existing schema and annotations make this adequate.

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 coverage is 100%, but the description adds meaning by clarifying that works_limit refers to 'most-cited works,' which sharpens the schema's vague 'top works.' The name parameter is already well-documented in the schema, so the description provides a small but meaningful improvement.

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 uses a specific verb ('Look up a researcher') and clearly identifies the resource (OpenAlex) and the output fields (works count, citations, h-index, affiliation, ORCID, most-cited works), distinguishing it from sibling tools like search-literature or citation-graph.

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?

Explicitly states when to use the tool ('to gauge a source author's expertise and track record, or to find a researcher's key papers'), giving clear context. It doesn't name alternative tools or exclusions, but the use cases are sufficiently distinct.

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