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

With no annotations, the description carries the full behavioral burden and does so well: it explains hop limits, top-20/8-coauthor cutoffs, consortium-paper skipping, node and edge attributes, and special ambiguous/name_only return cases. It also discloses the 2-credit cost.

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 definition is dense but front-loaded: the graph behavior comes first, followed by use cases and edge cases. It is longer than typical descriptions but nearly every sentence carries substantive behavioral detail, with only minor awkwardness in phrasing.

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?

For a graph tool with no annotations and no output schema, the description is complete enough to call correctly. It explains the graph construction, node/edge meaning, identity ambiguity handling, and cost, so an agent has the key behavioral context it needs.

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?

The schema already documents 75% of the parameters, including name, openalex_id, and author_id. The description adds useful identity-resolution semantics for names and openalex_ids, including ambiguous and name_only outcomes, though it does not explicitly explain how the depth parameter maps to hop 1 versus hop 2.

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 specifies a concrete resource and relationship: a co-authorship graph around an author. It immediately defines hop 1 and hop 2, which makes the tool distinct from citation-oriented siblings such as citation_graph or citation_walk.

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?

It gives clear usage contexts: mapping a research group, finding who bridges two labs, or picking reviewers. It does not explicitly name alternative tools or state when not to use this one, so it falls short of full when/when-not guidance.

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