# LLM-Wiki

> LLM-Wiki — oshayr-llm-wiki. Use this tool when you need to organize and connect your research, ideas, and decisions into a cohesive knowledge base. LLM-Wiki solves the problem of information fragmentation by providing a semantic search and Wikipedia-style web UI, allowing you to easily access and build upon your existing knowledge. It integrates with git, capturing new information and linking it to existing content, and is ideal for use cases where research and idea management are crucial.

Canonical page: https://skillsregistry.net/skills/oshayr-llm-wiki  
JSON: https://api.skillsregistry.net/v1/skills/oshayr-llm-wiki

## Description

Autonomous knowledge base plugin for Claude Code - captures reserch, ideas, and decisions into an interlinked wiki with reserch-on-miss, semantic search, and a Wikipedia-style web UI. Knowledge compounds as you work.

## Trust

- **Trust score (0–1):** 0.12
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-25

## Source

- **Source listing:** [GitHub](https://github.com/Oshayr/LLM-Wiki)

## 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": "oshayr-llm-wiki"
    }
  }
}
```

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