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Hug0x0

mcp-reunion

reunion_find_commune

Find the canonical commune for approximate or misspelled La Réunion names. Returns INSEE code, EPCI, department, region. Handles case, accents, abbreviations.

Instructions

Fuzzy resolver: takes an approximate or misspelled La Réunion commune name and returns matching canonical communes with INSEE code, EPCI, department, region. Handles common variations: case insensitive, accent insensitive ("Etang Sale" → "L'Étang-Salé"), abbreviations ("St-Denis" → "Saint-Denis"), missing punctuation. Always call this first when a user provides a commune name with any uncertainty before passing it to commune-filtered tools that expect exact prefix matches.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesApproximate commune name. Examples: "saint denis", "St-Pierre", "etang sale", "Le Tampon"
Behavior5/5

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

No annotations are provided, so the description carries full burden. It thoroughly discloses behavior: fuzzy matching, handling of common variations, and return fields (INSEE code, EPCI, department, region). There is no suggestion of destructive or write behavior.

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?

The description is a single paragraph that efficiently conveys the tool's purpose, handling, and usage guidance. It is appropriately sized and front-loaded with the core purpose.

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

Completeness5/5

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

Given no output schema, the description mentions return fields, explains fuzzy behavior, and provides usage context. For a simple resolver, it is complete and leaves no critical gaps.

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

Parameters4/5

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

While the schema description covers 100% of the single parameter with examples, the description adds context about the fuzzy matching logic and the types of variations it handles, enriching the semantic understanding beyond the schema.

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 clearly identifies the tool as a fuzzy resolver for La Réunion commune names, specifying the types of variations handled (case, accent, abbreviation, punctuation). It distinguishes itself from sibling tools by stating that it should be called first when uncertainty exists, before using tools requiring exact prefix matches.

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

Usage Guidelines5/5

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

The description explicitly states when to use this tool ('always call this first when a user provides a commune name with any uncertainty') and what not to use it for (before passing to commune-filtered tools expecting exact matches). It implies that alternatives are those exact-match tools by stating 'before passing to commune-filtered tools'.

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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