# kanoniv

> kanoniv — kanoniv-kanoniv. Use this tool when you need to resolve identity data inconsistencies and master entity records across multiple sources. Kanoniv provides a declarative engine for matching, merging, and mastering entity data, solving problems of data duplication and inconsistency. It takes in entity data as input and outputs unified, accurate records, ideal for use cases requiring data integration and reconciliation, with version control via git.

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

## Description

Identity resolution as code - declarative engine for matching, merging, and mastering entity data

## Trust

- **Trust score (0–1):** 0.57
- **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/kanoniv/kanoniv)

## 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": "kanoniv-kanoniv"
    }
  }
}
```

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

---
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