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by io.github.pipeworx-io
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Reverse Geocode

reverse_geocode
Read-onlyIdempotent

Reverse-geocode a coordinate to the nearest French address/feature. Returns scored GeoJSON matches with label, postcode, citycode (INSEE), context and distance (metres). France only.

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "lat": 48.8566,
      "lon": 2.3522
    },
    "name": "reverse_geocode"
  }
}

Input Schema

NameRequiredDescriptionDefault
latYesLatitude (WGS84).
lonYesLongitude (WGS84).
typeNoRestrict to a feature type.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "lat": 48.8566,
+    "lon": 2.3522
+  },
+  {
+    "lat": 43.2965,
+    "lon": 5.3698,
+    "type": "street"
+  }
+]
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already provide safety hints (readOnly, idempotent, non-destructive). The description adds meaningful context beyond that: it specifies the return format (scored GeoJSON matches) and the exact fields returned (label, postcode, citycode, context, distance in metres), as well as the France-only limitation. No contradictions with annotations.

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

Conciseness5/5

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

The description is two sentences, front-loaded with the primary action and scope, followed by a compact summary of the return fields. Every sentence earns its place with no redundancy or fluff.

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?

The tool is relatively simple (3 params, no output schema). The description adequately covers the purpose, return format, and geographic constraint. It could mention that multiple matches may be returned or how they are ordered, but the main context is sufficiently covered.

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?

The schema descriptions cover 100% of parameters, including units (WGS84) and the 'type' enum. The description adds no additional param-specific meaning beyond what the schema already provides, so the baseline of 3 is appropriate.

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

Purpose5/5

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

The description uses a specific verb 'reverse-geocode' combined with the resource 'coordinate' and clearly states the geographic scope ('France only'). This distinctly differentiates it from the sibling tool 'geocode' (forward geocoding) and other location tools.

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

Usage Guidelines4/5

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

The description clearly establishes the tool's context (reverse geocoding for French addresses) and geographic constraint ('France only'), but it does not explicitly name alternatives or state when not to use it. The verb itself implies the use case, so this is still clear.

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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