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

Beyond the annotations it discloses the commercial model (paid, requires a key, charged per hit for e-mail and phone, per-field credit prices and caps), the side effect (records land in the key's agent list in ListPlus, visible to the user), and the async contract (wait up to 25 s, then return a job_id to poll). That is exactly the cost/effect/latency context an agent needs before a non-read-only call.

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?

Cost and the estimate-first instruction are aggressively front-loaded, which is correct for a paid tool, and most sentences carry distinct information. The run of per-field price and cap figures is dense and could be trimmed to the two or three values that matter most.

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 6-parameter, async, billable mutation with no output schema, the description covers cost, key requirement, side effects, timeout, and the follow-up polling tool. An agent has everything required to call it safely and interpret the response.

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%, so baseline is 3; the description still adds meaning by explaining the economic intent of the estimate flag (free, no key, price only) and the per-field charge structure that makes max_credits relevant. It does not clarify request_id deduplication or language beyond what the schema already says.

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 and resource plus a concrete field inventory (work e-mail, mobile, job title, LinkedIn, company, domain, industry, size, place) and states the input shape (name + company). It never names or contrasts itself with siblings like find_person or check_records, so the agent must infer which enrichment path is right.

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 a clear operating sequence: run estimate:true first for a free exact price, then the paid call, then poll get_job if the 25 s window elapses. It does not say when to prefer find_person or verify_email instead, so the alternative-selection guidance is incomplete.

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