# agent-prod

> agent-prod — fangzheng698-lang-agent-prod. Use this tool when you need to ensure the quality and reliability of AI agents in production, solving problems such as regression detection and risk control. It provides a framework for evaluation, gray release, audit, and observability, taking in AI agent models and outputting quality gate assessments. Ideal for use in LLMOps pipelines, particularly when integrating with git version control systems.

Canonical page: https://skillsregistry.net/skills/fangzheng698-lang-agent-prod  
JSON: https://api.skillsregistry.net/v1/skills/fangzheng698-lang-agent-prod

## Description

Production AI agent quality gate and risk control framework for LLMOps, agent evaluation, regression detection, gray release, audit, and observability

## Trust

- **Trust score (0–1):** 0.38
- **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/fangzheng698-lang/agent-prod)

## 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": "fangzheng698-lang-agent-prod"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/fangzheng698-lang-agent-prod` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/fangzheng698-lang-agent-prod/pull`

---
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