# data-cog

> Use this tool when you need to uncover hidden insights and patterns in your data, solving problems such as informed decision-making, trend analysis, and predictive modeling. Data-cog takes in raw data as input and outputs actionable intelligence, enabling users to make data-driven decisions. It is ideal for use cases where complex data analysis is required, such as business intelligence, market research, and scientific studies.

Canonical page: https://skillsregistry.net/skills/nitishgargiitd-data-cog  
JSON: https://api.skillsregistry.net/v1/skills/nitishgargiitd-data-cog

## Description

Your data has answers.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** other
- **Updated:** 2026-05-17

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/nitishgargiitd-data-cog)

## 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": "nitishgargiitd-data-cog"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/nitishgargiitd-data-cog` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/nitishgargiitd-data-cog/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