# Sozio Thin

> Use this tool when you need to analyze Swiss open-data resources efficiently, as it enables reproducible analysis by searching profiles, executing SQL queries, and formatting results. It solves problems related to data validation, execution, and reproduction, providing a streamlined interface for inputs like SQL queries and outputs like formatted analysis results. Ideal for use cases requiring reliable and transparent data analysis, such as research or policy-making, where reproducibility and data integrity are crucial.

Canonical page: https://skillsregistry.net/skills/fabianbartschdatenanalyse-sozio-thin  
JSON: https://api.skillsregistry.net/v1/skills/fabianbartschdatenanalyse-sozio-thin

## Description

Enables reproducible analysis of 100 curated Swiss open-data resources by searching profiles, materializing PXWeb data, validating and executing SQL, and formatting reproduction details, with reasoning delegated to the MCP client.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** search
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/x7wzz45opg)
- **Repository:** <https://github.com/FabianBartschDatenanalyse/sozio-thin>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "fabianbartschdatenanalyse-sozio-thin"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/fabianbartschdatenanalyse-sozio-thin` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/fabianbartschdatenanalyse-sozio-thin/pull`

---
SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt