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

The description discloses key behavioral traits beyond annotations: the job runs asynchronously (3–10 minutes), returns a jobId immediately, and every lead counts against the workspace quota. It also explains that limit is a target, not a cap, which is essential for setting expectations. 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?

The description is efficient and front-loaded: the main purpose is stated first, followed by essential operational details (jobId, polling, quota) and a clear caveat. Every sentence contributes to correct usage; there is no fluff or redundancy.

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 the tool's async nature and quota implications, the description covers all necessary aspects: how to start, what to expect immediately, how to retrieve results, and the cost. The presence of an output schema further reduces ambiguity, and the description aligns with it.

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?

While schema coverage is 100% (both parameters have descriptions), the description adds critical nuance: it clarifies that limit is a target rather than a hard cap and that results may exceed it, and it provides a concrete example for the query parameter. This significantly enriches understanding 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 verb 'start' and the resource 'live B2B lead search', and explicitly contrasts with sibling fetch_leads by describing the immediate jobId return and the polling flow. It also gives a concrete example ('find 5 fintech founders in NYC'), making the purpose unambiguous and distinct from other 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 explicitly tells the agent when to use this tool (start a search), what to pass (natural-language brief), and how to proceed afterward (poll fetch_leads with jobId until completed). It also clarifies the limit parameter's intended usage, leaving no ambiguity about invocation flow.

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