# frigg

> frigg — bnomei-frigg. Use this tool when you need to quickly analyze and understand local codebases with fast and accurate code intelligence. It solves problems such as code navigation, semantic search, and code completion by leveraging AST Treesitter, SCIP, and reranking algorithms. Ideal for use cases involving git repositories, providing inputs such as code snippets and outputs like relevant code suggestions and explanations.

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

## Description

Fast local code intelligence for AI agents powered by AST Treesitter, SCIP, semantic search and a reranker

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-22

## Source

- **Source listing:** [GitHub](https://github.com/bnomei/frigg)

## 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": "bnomei-frigg"
    }
  }
}
```

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