# ExpenseDesk

> ExpenseDesk — imarmang-expensedesk. Use this tool when you need to easily query a company expense database without requiring technical expertise in SQL. ExpenseDesk solves the problem of complex expense data analysis by converting text questions into executable SQL queries, providing accurate and relevant results. It takes in natural language queries as input and outputs relevant expense data, making it ideal for non-technical users to retrieve expense information in a user-friendly manner.

Canonical page: https://skillsregistry.net/skills/imarmang-expensedesk  
JSON: https://api.skillsregistry.net/v1/skills/imarmang-expensedesk

## Description

A chatbot that converts text questions into SQL queries and runs them against a company expense database. Uses RAG to retrieve relevant SQL examples and improve query accuracy. Built with FastAPI, Ollama, MCP, and SQLite.

## Trust

- **Trust score (0–1):** 0.94
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/imarmang/ExpenseDesk)

## 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": "imarmang-expensedesk"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/imarmang-expensedesk` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/imarmang-expensedesk/pull`

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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