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

The description discloses important behavioral traits beyond the annotations: it spends credits, has a 30-day caching/short-circuit behavior, returns immediately, and requires polling for readiness. These details meaningfully inform an agent about cost and asynchronous behavior, and they do not contradict any annotation.

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 compact and front-loaded: it states the action first, then the critical cost caveat, then the response/polling behavior. Every sentence earns its place and there is no redundant filler.

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?

The description covers the core workflow, cost implications, caching behavior, and the polling handoff to get_person_intelligence. With an output schema presentable to the agent, there is no missing information needed to correctly invoke this tool.

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 parameters are already fully documented in the schema. The description adds little to parameter semantics beyond restating that personUrl is a LinkedIn URL; that baseline of 3 is appropriate given the schema carries the weight.

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 uses a specific verb ('Start') with a clear resource ('Person Intelligence snapshot') and target ('a person's LinkedIn URL'). It also distinguishes the tool from its sibling get_person_intelligence by describing the run-then-poll relationship, so an agent can tell them apart without opening the schema.

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 explicitly states the action triggers a snapshot and gives concrete guidance about when it should not be run ('unless a snapshot from the last 30 days already covers this person'). It also names the correct follow-up tool ('poll get_person_intelligence until status is "ready"'), which is strong usage direction.

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