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

With no annotations provided, the description carries the full burden, and it does well: it discloses that the tool has no side effects ('Does not save anything, does not contact anyone, does not spend credits') and that the return is only aggregate counts plus a small sample. It omits details like auth requirements or rate limits, but the no-credit and no-side-effect guarantees are highly valuable for an agent.

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 two sentences with no filler. The core purpose and the critical preview-only behavior are front-loaded, and every sentence adds meaningful information.

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 complex 13-parameter search tool with no output schema and no annotations, the description covers the high-level purpose and safety profile but is incomplete. It does not describe the return structure beyond 'aggregate counts and a small sample,' filtering semantics, or how searchMode/query parameters relate, so an agent would need to infer several important invocation details.

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%, so the description must compensate, but it only names a subset of filters (countries, industries, positions, tags, must-have-email) and uses 'etc.' It does not explain important parameters like searchMode, exactKeyword, semanticQuery, mustHavePhone, mustHaveLinkedin, companySizes, or how they interact. With 13 parameters, this leaves significant ambiguity.

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: 'Search the people graph for prospects matching filters.' It enumerates the main filter dimensions and explicitly marks the tool as PREVIEW-only, which clearly distinguishes it from save_audience, launch_audience_set, and buy_audience_set among the siblings.

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 gives clear context: this is a preview/search operation that returns counts and a sample, and it explicitly says it does not save, contact, or spend credits. This implies when to use it, though it does not explicitly name the alternative tools for saving or launching an audience.

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