# scomp_link

> scomp_link — giacomosaccaggi-scomp-link. Use this tool when you need to automate and streamline your machine learning workflow, from data profiling to model deployment and monitoring. It solves problems such as tedious manual preprocessing, model selection, and explainability, providing a zero-code CLI interface for easy integration and outputting interactive HTML reports. Ideal for data scientists and engineers looking to efficiently build, train, and validate ML models with Python 3.10+.

Canonical page: https://skillsregistry.net/skills/giacomosaccaggi-scomp-link  
JSON: https://api.skillsregistry.net/v1/skills/giacomosaccaggi-scomp-link

## Description

End-to-end ML toolkit automating the complete workflow — data profiling, preprocessing, feature engineering, model selection, training, validation, explainability, drift monitoring, fairness checks, and interactive HTML reporting. Includes a full CLI for zero-code ML pipelines. Python 3.10+.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-26

## Source

- **Source listing:** [GitHub](https://github.com/GiacomoSaccaggi/scomp_link)

## 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": "giacomosaccaggi-scomp-link"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/giacomosaccaggi-scomp-link` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/giacomosaccaggi-scomp-link/pull`

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