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

No annotations exist, so the description carries the full burden, and it discloses a lot: pagination, sort dimensions, returned fields, cost ('Free · 1 credit'), and two non-obvious response modes — an `ambiguous` result listing candidate people with `openalex_id`s instead of figures, and a `name_only` result for un-disambiguated names. It does not cover auth requirements, rate limits, or total-count/pagination metadata, which keeps it short of 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?

Front-loaded with purpose, then usage, then edge cases, then cost — a sensible order with little waste. The `name_only` sentence ('A name nobody is told apart under yet answers by name') is grammatically tangled and costs a beat to parse, which slightly hurts readability.

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?

With no output schema, the description does the work of describing return content (venue, citations, stars, co-authors) and the shape of the ambiguous-name response, which is the hardest thing to guess. Remaining gaps — total result counts, page-size ceiling behavior, and error conditions beyond ambiguity — are minor for a read-only listing tool.

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 50%, with `page`, `page_size` and `sort` undocumented in the schema, and the description compensates by naming the sort dimensions ('date, citations, GitHub stars or hype') that map to the `sort` enum and by framing results as paginated. It also explains the relationship between `name` and `openalex_id` through the ambiguity flow, which is meaning beyond the schema's field 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?

Opens with a specific verb+resource and scope: 'Every paper under an author's name, paginated and sorted by date, citations, GitHub stars or hype.' It also lists the returned fields (venue, citations, stars, co-authors), which lets an agent tell it apart from the sibling `author` top-10 endpoint without inspecting either schema.

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 routes the agent: 'Use after `author` when the top-10 list is not enough or you need the chronological output.' It also gives the escalation path for ambiguous names (re-query with an `openalex_id` from the returned list), so the decision points are stated rather than inferred.

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