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Hug0x0

mcp-reunion

reunion_get_waste_tonnage

Get annual tonnage of household and assimilated waste in La Réunion, broken down by waste type (residual, selective, green waste, etc.) for waste-policy monitoring and recycling analysis.

Instructions

Annual tonnage of Déchets Ménagers et Assimilés (DMA, household + assimilated waste) collected in La Réunion, broken down by waste type (ordures ménagères résiduelles, collecte sélective, déchèteries, encombrants, déchets verts, etc.). Returns year, waste-type code and label, tonnage in tonnes, department. Sorted by year descending. Source: SINOE / ADEME via data.regionreunion.com. Use for waste-policy monitoring, recycling rate analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNoYear filter (4 digits, e.g. 2022)
waste_typeNoWaste-type label prefix. Examples: "Ordures ménagères résiduelles", "Collecte sélective", "Déchets verts", "Encombrants", "Déchèteries"
limitNoMax rows to return (1-200, default 50)
Behavior4/5

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

With no annotations, the description carries full burden. It discloses sorting (by year descending), source (SINOE/ADEME via data.regionreunion.com), and output fields. It doesn't cover pagination or auth requirements, but for a read-only tool, this is sufficient transparency.

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?

Single paragraph, no wasted words. Front-loads purpose, then details output, ends with usage suggestions. Perfectly concise and well-structured.

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?

For a simple data-retrieval tool with 3 optional params and no output schema, the description adequately explains output fields, sorting, and source. It lacks pagination behavior or error handling notes, but overall it's comprehensive enough.

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?

Input schema has 100% description coverage. Description adds minor value by listing waste-type examples and noting year is 4-digit, but schema already provides parameter descriptions. Baseline 3 is appropriate as description does not significantly enhance parameter meaning.

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?

Description explicitly states tool returns annual tonnage of DMA waste in La Réunion broken down by waste type, with fields like year, waste-type code/label, tonnage, and department. It clearly distinguishes from sibling tools (e.g., commune profiles, air quality) as the only waste-tonnage tool.

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?

Provides explicit use cases: 'Use for waste-policy monitoring, recycling rate analysis.' However, it does not mention when not to use the tool or suggest alternatives. Given the unique nature of this tool among siblings, the guidance is clear enough.

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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