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Kolada Se

by io.github.pipeworx-io
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List Org Units

list_org_units
Read-onlyIdempotent

Kolada, the Swedish municipal and regional KPI database run by RKA — list the organizational units it tracks (schools, preschools, eldercare facilities) within one of Sweden's 290 municipalities or 21 regions. Returns id, title, municipality. OU ids can be used for unit-level data drilldowns. Filter by title substring and/or municipality id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleNoSubstring of the unit name (Swedish), e.g. "skola" or "förskola".
municipalityIdNoRestrict to a municipality/region id, e.g. "0180".

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "municipalityId": "0180",
+    "title": "skola"
+  },
+  {
+    "title": "förskola"
+  }
+]
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent behavior. The description adds context about the data source (RKA/Kolada) and return fields (id, title, municipality), plus the hint that OU ids enable further analysis. This complements the annotations without contradiction.

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 compact, front-loads the core action ('list the organizational units'), and packs domain context, return fields, and a usage hint into two sentences with no fluff.

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?

For a simple list tool with optional filters and no output schema, the description adequately covers what is returned (id, title, municipality), how to filter, and the domain background. No critical information is 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?

The input schema fully documents both parameters with examples and descriptions, and schema coverage is 100%. The description only restates the filter capability without adding new semantic detail, so baseline 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 clearly states the tool lists organizational units tracked by Kolada within Swedish municipalities/regions, with specific examples (schools, preschools, eldercare). It distinguishes itself from siblings like list_municipalities by focusing on units rather than municipalities.

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 gives clear context: use when you need org units and their ids for drilldowns. It does not explicitly name alternatives or exclusions, but the scope is obvious and the mention of OU ids for unit-level data drilldowns implies a specific use case.

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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