# pingfusi

> pingfusi — alex-durango-pingfusi. Use this tool when you need to inject human oversight into automated coding tasks, enabling real-time review and feedback to improve agent accuracy and efficiency. It solves problems of subpar code quality and agent bias by allowing human reviewers to intervene and correct errors mid-task. The pingfusi tool accepts code inputs from agents, outputs reviewed and approved code, and integrates with git for seamless version control.

Canonical page: https://skillsregistry.net/skills/alex-durango-pingfusi  
JSON: https://api.skillsregistry.net/v1/skills/alex-durango-pingfusi

## Description

MCP server + CLI that puts a real human in your coding agent's loop. It publishes work mid-task, a reviewer pins what's wrong and returns a verdict, and the agent iterates until approved.

## Trust

- **Trust score (0–1):** 0.00
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/alex-durango/pingfusi)

## 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": "alex-durango-pingfusi"
    }
  }
}
```

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