# floop

> floop — nvandessel-floop. Use this tool when you need to generate context-aware code corrections and behaviors for AI coding agents, taking in code errors and corrections as input and producing corrected, functional code as output. It solves problems of inefficient coding and debugging, enabling agents to learn from corrections and adapt to new contexts. Ideal for use in AI-powered coding environments, particularly those utilizing git version control.

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

## Description

Spreading activation memory for AI coding agents - corrections in, context-aware behaviors out.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-06-18

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** other
- **Updated:** 2026-09-20

## Source

- **Source listing:** [GitHub](https://github.com/nvandessel/floop)

## 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": "nvandessel-floop"
    }
  }
}
```

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