get_enterprise_counts

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

No annotations are provided, so the description carries the full burden. It discloses defaults (EU27+NO+CH), the UK unavailability post-Brexit, the meaning of exclude_micro, the automatic latest year behavior, and the return structure including caveats. This is rich behavioral disclosure.

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 well-structured with a concise summary followed by per-argument details and a return note. It is appropriately detailed for a four-parameter tool; no sentence is wasted.

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 all aspects needed to use the tool correctly: parameter formats, defaults, caveats, and return values. It is complete even though an output schema exists, and it adds useful business context like the TAM sheet note.

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 0%, but the description fully compensates by explaining every parameter: NACE code format including valid dotted notation, geo default and country breakdown, year default behavior, and exclude_micro semantics. This exceeds what the schema alone provides.

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 tool returns enterprise counts for a single NACE Rev.2 code, bucketed into SME and Corp, summed across specified geographies. It is specific about the resource and aggregation, but it does not explicitly contrast with sibling tools such as get_segment_counts or get_company_count, so it lacks explicit sibling differentiation.

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 strong context for use: it explains the single NACE code requirement, default geographies, country breakdown option, and year behavior. It does not explicitly state when not to use this tool or name alternatives, so it is a 4 rather than a 5.

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