# knowledge-layer

> knowledge-layer — mihaelamaciuca-knowledge-layer. Use this tool when you need to unify your team's knowledge and make it accessible to both humans and AI agents. It solves the problem of fragmented information and enables querying of collective memory, streamlining collaboration and decision-making. With git integration, it accepts code repositories as input and provides a queryable interface for outputs.

Canonical page: https://skillsregistry.net/skills/mihaelamaciuca-knowledge-layer  
JSON: https://api.skillsregistry.net/v1/skills/mihaelamaciuca-knowledge-layer

## Description

Knowledge layer for AI-native teams

## Trust

- **Trust score (0–1):** 0.63
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** other
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/mihaelamaciuca/knowledge-layer)

## 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": "mihaelamaciuca-knowledge-layer"
    }
  }
}
```

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