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

With no annotations, the description carries the full burden and does so well. It discloses quota deduction per record, default and maximum limits, fingerprinting, the need for an API key, and the existence of a bulk alternative. This is strong behavioral disclosure beyond the minimal 'pull records' phrasing.

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 dense but every sentence earns its place: purpose, metering warning, default/max limits, bulk API alternative, auth requirement, and free alternatives. It is front-loaded with the core purpose and immediately surfaces the critical cost constraint.

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 no annotations and no output schema, the description covers the important operational context: quota impact, auth, limits, output shape, bulk endpoint, and free alternatives. The only residual gap is detailed filter semantics, but those parameters are optional and reasonably self-explanatory, so the tool is still safely invocable.

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 only 17%, so the description needed to compensate for the five undocumented parameters: scope, states, scoreMax, scoreMin, and industries. It clarifies limit's cost semantics and mentions 'filters' generally, but does not explain filter behavior, accepted values, or interactions, leaving most parameters semantically underspecified.

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: 'Pull full licensed records from the Engagemii dataset.' It also distinguishes this tool from the free-browsing siblings by noting it returns the same shape as a purchased file, so an agent can tell it apart from dataset_sample and search_companies.

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 explicit usage context: it is metered, limits should stay small, bulk pulls should go through the raw API, and free browsing should use search_companies or dataset_sample instead. It also names the required API key, leaving little ambiguity about when this tool should be selected.

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