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

Annotations already convey read-only/idempotent/non-destructive behavior. The description adds useful behavioral context beyond annotations: results are page-paginated, each call costs 10 Zooq credits, and records are professional plus education-linked. No contradiction with annotations.

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?

Three short sentences, each carrying useful information: data scope, pagination, and use case/cost. It is efficient and front-loaded, though the phrase 'professional records + the education link' is slightly cryptic.

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 search tool with rich schema descriptions, an output schema, and safety annotations, the description adds the missing contextual pieces: pagination behavior, cost, and intended recruiting use. It is complete enough for an agent to invoke correctly, though it could name related tools.

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 100%, so the description does not need to repeat parameters. It adds only the generic 'page-paginated' hint, which is already implied by the page/limit parameters; no additional semantic 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 identifies the target data (alumni and current students of an institution) and the intent (recruiting and warm-intro sourcing), which makes the tool's purpose clear. It does not explicitly say 'search' or name sibling alternatives, so it lacks explicit differentiation from generic people-search tools.

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 provides clear context: use this when sourcing alumni/current students for recruiting or warm intros. It does not state exclusions or point to alternatives such as search_people, so it falls short of full when-to-use/when-not-to-use guidance.

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