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

The description goes well beyond annotations by disclosing the atomic credit charge, the 'only newly unlocked people cost credits' rule, the free ownership behavior, and the out-of-credits error instead of overspending. This gives agents critical cost and failure-mode transparency.

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 and every sentence earns its place: purpose, return data, email separation, autonomous-use warning, and error behavior. It is thorough without being redundant.

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?

Despite having no output schema, the description enumerates exactly what is returned (name, title, company, location, LinkedIn URL, id), explains credit costs, notes the next step for emails, and states the error behavior. An agent has enough context to call this tool correctly and safely.

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%, but the description enriches the count parameter by explaining it means up to that many credits may be spent and that already-owned people are free. It also ties query to the same grammar as people_search, adding useful cross-tool context.

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 states a specific verb and resource: it 're-runs a plain-English people search and unlocks up to count full profiles.' It clearly differentiates itself from people_search by emphasizing the batch unlock and from fetch_email by explicitly saying emails are not fetched here.

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 explicit routing guidance: after unlocking, call fetch_email with each person's id to get verified emails. It also warns autonomous agents to choose count deliberately and confirm before large batches, which is clear when-to-use and cautionary context.

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