get_professor_details

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

No annotations provided, so the description carries full burden. It discloses behavior: fetches multiple sources, includes source/confidence metadata, and provides homepage_search_query if homepage_url is null. However, it omits error handling or rate limits.

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 description is well-structured with a clear summary first, then bullet-like details for each argument and return values. It is concise enough but every sentence serves a purpose. Minor room for improvement in brevity.

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 3 parameters (none required) and no output schema, the description covers inputs thoroughly and explains the output fields including edge cases. It is complete for a tool of this complexity.

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 description coverage is 0%, but the description compensates well by explaining each parameter: professor_id is the preferred OpenAlex ID, name is used if ID is missing, and university aids disambiguation. This adds value beyond the schema.

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 clearly states the tool's purpose: 'Get detailed multi-source profile for a professor.' It specifies the sources (OpenAlex, DBLP, homepage) and key data points, making it distinct from sibling tools like 'search_professors' which likely performs broader searches.

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?

The description explains when to use the tool (to get a detailed profile) and the parameter usage (preferred professor_id, fallback name+university). It does not explicitly exclude cases or name alternatives, but the context implies it for detailed profiles vs. broader searches.

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