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Recorded crime of a French commune

crime_stats
Read-onlyIdempotent

Offences recorded by police and gendarmerie (SSMSI, latest year) for a French commune — by name, INSEE code or position — per indicator, as rates per 1,000 inhabitants (per 1,000 dwellings for burglaries), next to its département, région and France, with the yearly trend.

Input Schema

NameRequiredDescriptionDefault
latNoLatitude (WGS84).
lngNoLongitude (WGS84).
placeNoCity, city start or postcode (e.g. "Carnac", "Paris 11e", "75011"); with address, the place it is in. Ignored when lat and lng are given.
addressNoStreet address with its postcode or city (e.g. "17 rue Gambey, 75011 Paris"), located where its sales were recorded (else its street's). Ignored when lat and lng are given.
communeNoCommune name or INSEE code (e.g. "Carnac", "56034"), or a département code ("56").

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / place / description
      Previous value: -"City, city start or postcode (e.g. \"Carnac\", \"Paris 11e\", \"75011\", \"SW1A\"); with address, the place it is in. Ignored when lat and lng are given."New value: +"City, city start or postcode (e.g. \"Carnac\", \"Paris 11e\", \"75011\"); with address, the place it is in. Ignored when lat and lng are given."
  2. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent and non-destructive, so safety is covered. The description adds real behavioral context beyond the annotations: the data source (SSMSI), recency (latest year), unit normalization (per 1,000 inhabitants / per 1,000 dwellings for burglaries), and comparative framing (département, région, France) plus yearly trend. This is useful disclosure, though it omits known caveats such as suppression for small communes.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

It is a single dense sentence, but front-loaded with the core purpose and scope; every clause (source, unit, comparison set, trend) carries information. Slightly packed with em-dash asides, which costs a point.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so the description must convey the return shape, and it does: normalized rates, comparator geographies, and yearly trend. Combined with full parameter coverage and safety annotations, an agent has enough to call it correctly; only edge-case caveats are missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents all five parameters thoroughly. The description's 'by name, INSEE code or position' only loosely maps to place/commune/lat/lng without adding format or precedence detail, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb+resource: recorded offences from police/gendarmerie (SSMSI) for a French commune, with the exact output units. This clearly separates it from the property- and amenity-oriented siblings. It stops short of naming a sibling (e.g. commune_profile) to contrast against, so it isn't a full 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied: you call it to get crime statistics for a commune, addressable by name, INSEE code or position. There is no explicit when-to-use/when-not guidance and no stated alternative (commune_profile, find_place) for locating a commune first. Adequate but leaves the agent to infer routing.

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

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