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

Annotations already declare non-read-only, open-world, non-idempotent, non-destructive. The description adds real behavior beyond that: the billing model (charged per unique value, reverse lookups only when found) and the asynchronous 'returns the job, then poll' contract. It omits whether repeat calls create duplicate jobs and whether items can be re-submitted, which would matter given idempotentHint=false.

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?

Two tight sentences, front-loaded with the scale and async nature, followed by the exact polling path. No filler and no repetition of the title or annotations.

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?

There is no output schema, so the description correctly covers the async return and polling path plus billing. However, for a 5-parameter mutation tool at 0% schema coverage it leaves key inputs (webhook_url, default_country, tier, allowed type values) unexplained, so an agent could not configure a job confidently from this text alone.

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% across 5 parameters, so the description carries the full burden and mostly does not: tier, webhook_url, default_country, and the meaning of the type enum values are all unexplained. Only 'up to 100,000 values' hints at an items constraint, leaving most parameters undocumented in both places.

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?

States a specific verb and resource ('Check up to 100,000 values in the background') with scope and scale, and explicitly distinguishes itself from the single-lookup flow it bills against. It also names the follow-up siblings (get_bulk_job, get_bulk_results), so an agent can place it in the workflow without opening any 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?

Clearly signals the batch/async use case and routes the agent through poll get_bulk_job then get_bulk_results, which is strong sequencing guidance. It does not state when to prefer single lookups instead, or when a bulk job is inappropriate (e.g. tiny item counts), so it falls short of explicit when/when-not/alternatives.

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