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Gastaan

Swiss Grounding MCP

by Gastaan

Waste collection dates

waste_collection
Read-onlyIdempotent

Find the next collection dates for cardboard, paper, household waste, and green waste in Swiss municipalities. Enter your town, postcode, or street to get accurate schedules.

Instructions

Next waste collection dates (cardboard, paper, household waste, green waste…) from municipal open data. Needs the municipality; some cities also need postcode or street (the tool will say).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
placeNoMunicipality, postcode, address or canton as the user said it, in any language (e.g. 'Lugano', '8003', 'Genf', 'Bahnhofstrasse 1, Zürich').
streetNoStreet (and number) if the user gave one.
from_dateNoISO date to start from; default today.
waste_typeNoe.g. Karton/carton/cartone, Papier, Kehricht, Grüngut, Metall. Omit for all types.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
statusYes
summaryYes
guidanceNo
citationsNo
missing_contextNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering safety. The description adds behavioral context beyond that: it mentions the tool may request additional input ('the tool will say') and specifies the data source ('municipal open data'), which is not in annotations. This is useful supplementary information.

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 a single, compact sentence that front-loads the core function and then gives a concise usage note. Every word serves a purpose, with no redundancy or filler.

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 the tool's simplicity (4 optional, well-documented parameters, output schema present, safety annotations), the description is complete. It covers what the tool returns, what input is needed, and how it handles missing information. No critical operational detail is missing.

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?

Schema coverage is 100%, so the baseline is 3. The description adds value by clarifying that a municipality is effectively required ('Needs the municipality') and that additional parameters may be needed conditionally, which is not captured in the schema's optional flags. This supplements the parameter documentation meaningfully.

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 states a specific verb ('Next waste collection dates') and resource (municipal waste data), and lists example waste types. It clearly differentiates from sibling tools like public_transport or current_weather, which address entirely different domains.

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 says 'Needs the municipality' and notes that some cities need postcode or street, giving practical input requirements. It does not explicitly name alternatives or state when not to use it, but the tool name and sibling context make the intended use obvious. Slight gap in explicit exclusion guidance.

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