nc_get_company_statistics

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

With no annotations, the description carries the full burden of behavioral disclosure, but it only states that the tool returns aggregate statistics. It does not reveal whether the operation is read-only (though a GET is implied by the name), what the response format looks like, whether pagination exists, or what 'statistics' means precisely (e.g., counts, averages, distributions). This lack of context is a significant gap for an unannotated tool.

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 a single, efficient sentence that is front-loaded with the core purpose. It avoids unnecessary detail and is appropriately sized for a simple tool. However, it could briefly mention the response type or use case without becoming verbose, which would push it to a 5.

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 tool is simple with one parameter and no output schema, so the description is not severely incomplete. However, it does not specify what kind of statistics are returned (e.g., count of companies per group) or any constraints on data range, and it omits any behavioral notes (auth, pagination). Given the lack of annotations, a more detailed description would help an agent understand the output, but the current description is minimally adequate for basic selection.

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?

The schema already provides a description for the single parameter group_by ('How to group the statistics') and an enum with four values. Since schema coverage is 100%, the baseline is 3. The tool description adds no extra nuance about the parameter, such as clarifying that 'forme_juridique' refers to legal form or that 'ape' is an activity code, but it also does not need to because the enum values are reasonably self-explanatory and the schema provides adequate guidance.

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 ('Get'), a resource ('aggregate statistics about companies'), and a location ('New Caledonia'). It clearly conveys the tool's function, and it distinguishes itself from siblings like nc_get_company (individual company data) and nc_search_companies (search for specific companies). However, it does not explicitly name any sibling alternative, leaving the differentiation implicit.

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 provides no guidance on when to use this tool versus others, nor does it mention any conditions or exclusions. It does not say 'use this to get counts or distributions of companies grouped by legal form' or indicate when to prefer a sibling like nc_get_companies_by_sector. An agent receives no context about the appropriate scenarios for choosing this tool.

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