Get comprehensive statistics for a French department. Returns total associations, active count, top cities, sector breakdown, and temporal evolution. Use department codes: 01-95 for metropolitan France, 2A/2B for Corsica, 971-976 for overseas.
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | Department code (e.g., "69" for Rhône, "75" for Paris, "2A" for Corse-du-Sud) |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It mentions the tool returns statistics, implying a read operation, but does not explicitly state it is read-only, nor does it discuss auth needs, rate limits, or data freshness. The description is adequate but not explicit.
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 two concise sentences: one stating purpose and output, one giving input guidance. No unnecessary words, and information is front-loaded.
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 the single parameter and no output schema, the description provides a good overview of what the tool returns and valid input. Minor gaps exist, such as not mentioning whether results are paginated or if any restrictions apply, but overall it is sufficiently informative.
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% for the single parameter 'code', which already provides examples. The description adds value by specifying valid code ranges (01-95, 2A/2B, 971-976) beyond the schema, helping the agent select correct inputs.
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 'Get comprehensive statistics for a French department' and details the data returned (total associations, active count, top cities, sector breakdown, temporal evolution). It also specifies valid department codes, distinguishing it from sibling tools like get_france_overview or get_association.
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 explicit guidance on valid department codes (01-95, 2A/2B, 971-976), but does not explicitly state when to use this tool versus alternatives like get_france_overview or get_platform_stats. However, the purpose is clear enough to infer the appropriate context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
