# datasentry

> datasentry — jackxiaozhiren-datasentry. Use this tool when you need to identify and correct errors in your data, ensuring its quality and integrity across various sources, including files, databases, and CI pipelines. Datasentry provides a local-first approach to data quality, allowing for safe and explainable fixes, and integrates with git for version control. It is ideal for use cases where data accuracy is crucial, such as AI model training and data-driven decision making.

Canonical page: https://skillsregistry.net/skills/jackxiaozhiren-datasentry  
JSON: https://api.skillsregistry.net/v1/skills/jackxiaozhiren-datasentry

## Description

Find, explain, and safely fix bad data. Local-first data quality for files, databases, CI pipelines, and AI agents.

## Trust

- **Trust score (0–1):** 0.52
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** Apache-2.0
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/Jackxiaozhiren/datasentry)

## 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": "jackxiaozhiren-datasentry"
    }
  }
}
```

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