# QuantMinds

> QuantMinds — saisreenivasreddy-quantminds. Use this tool when you need to streamline and automate data processing and analysis tasks, particularly in the context of hackathons or data science projects, to efficiently manage and integrate code repositories using git. It solves problems related to data pipeline management, version control, and collaboration. The QuantMinds RAG Pipeline takes in code and data inputs and outputs a streamlined and automated workflow.

Canonical page: https://skillsregistry.net/skills/saisreenivasreddy-quantminds  
JSON: https://api.skillsregistry.net/v1/skills/saisreenivasreddy-quantminds

## Description

QuantMinds Hackathon - RAG Pipeline

## Trust

- **Trust score (0–1):** 0.88
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** devops-ci
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/SaiSreenivasReddy/QuantMinds)

## 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": "saisreenivasreddy-quantminds"
    }
  }
}
```

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