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 affiliation resolution policy (curated table first, else the newest paper's first page), the exact metrics set, the degradation behavior for shared names (no figures, only `ambiguous` identities with openalex_ids), and the `name_only` fallback. It does not cover rate limits, error modes, or how `more` hints are shaped, so it stops short of fully transparent.

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 the payload and then the usage rules; every clause is informative and the pricing tag is clearly demarcated. It is dense to the point of being run-on, with several semicolon-joined ideas packed into single sentences, which slightly slows parsing but wastes no words.

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 must describe returns — and it does, listing each returned block (affiliations, metrics, top papers, collaborators, `more` hints) and the two special response shapes (`ambiguous`, `name_only`). For a read-only profile tool with three fully documented params, nothing essential is missing.

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% and the schema already documents all three parameters with examples and a pattern, so baseline is 3. The description adds meaning the schema cannot: that a name may map to several people, that `openalex_id` is precisely 'the ids a shared name's answer lists', and that name resolution has a curated-table-first precedence.

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 ('An author's profile by name or id') and then enumerates the payload: affiliations, metrics, 10 most-cited papers, top 10 collaborators with shared-paper counts. It also explicitly demarcates itself from siblings by saying it only provides `more` hints pointing to author_papers / coauthor_network rather than duplicating them.

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?

Gives an explicit trigger ('Use when a question names a person') plus a named alternative with a precondition ('use search to find the exact name first'). It further specifies the retry path for the ambiguous case (ask again with one `openalex_id`) and what happens for undifferentiated names (`name_only`), covering when-to-use and what-to-do-next.

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