风险评分

100/100 (Very Low)

OpenClaw: benign
VirusTotal: benign
StaticScan: clean

RAG Production Engineering

作者: afrexai-cto
Slug:afrexai-rag-production
版本:1.0.0
更新时间:2026-03-24 12:46:47
风险信息

OpenClaw: benign

查看 OpenClaw 分析摘要(前 200 字预览)
This is an instruction-only RAG methodology skill that is internally consistent with its stated purpose and does not request credentials or install code, but verify the publisher and external links be...

[内容已截断]

VirusTotal: benign VT 报告

静态扫描: clean

No suspicious patterns detected.
README

README 未提供

文件列表

无文件信息

下载
下载官方 ZIP
原始 JSON 数据
{
    "latestVersion": {
        "_creationTime": 1774326653245,
        "_id": "k970zgqjht2fchatn5swc4tf2s83gd16",
        "changelog": "Initial release of RAG Production Engineering methodology.\n\n- Provides a comprehensive framework for building, optimizing, and operating Retrieval-Augmented Generation (RAG) systems in production environments.\n- Includes health check scoring, architecture decision guides, detailed document processing and chunking strategies, and chunk metadata standards.\n- Outlines phases: Architecture Decision, Document Processing & Chunking, and Embedding Model Selection.\n- Features best practices for chunking, embedding selection, retrieval evaluation, and monitoring.\n- Designed for teams implementing robust, production-ready RAG solutions.",
        "changelogSource": "auto",
        "createdAt": 1774326653245,
        "version": "1.0.0"
    },
    "owner": {
        "_creationTime": 0,
        "_id": "s176d3cp92hzph7jd2dtka26md83h078",
        "displayName": "afrexai-cto",
        "handle": "afrexai-cto",
        "image": "https:\/\/avatars.githubusercontent.com\/u\/261321054?v=4",
        "kind": "user",
        "linkedUserId": "kn70egcef3wt8dk456reqyxe05812fwr"
    },
    "ownerHandle": "afrexai-cto",
    "skill": {
        "_creationTime": 1774326653245,
        "_id": "kd73bhe7jad5agvxaykhfzcs5983gj4v",
        "badges": [],
        "createdAt": 1774326653245,
        "displayName": "RAG Production Engineering",
        "latestVersionId": "k970zgqjht2fchatn5swc4tf2s83gd16",
        "ownerPublisherId": "s176d3cp92hzph7jd2dtka26md83h078",
        "ownerUserId": "kn70egcef3wt8dk456reqyxe05812fwr",
        "slug": "afrexai-rag-production",
        "stats": {
            "comments": 0,
            "downloads": 13,
            "installsAllTime": 0,
            "installsCurrent": 0,
            "stars": 0,
            "versions": 1
        },
        "summary": "Build, optimize, and operate production-ready Retrieval-Augmented Generation systems with best practices in architecture, chunking, embedding, retrieval, eva...",
        "tags": {
            "ai": "k970zgqjht2fchatn5swc4tf2s83gd16",
            "chunking": "k970zgqjht2fchatn5swc4tf2s83gd16",
            "embeddings": "k970zgqjht2fchatn5swc4tf2s83gd16",
            "evaluation": "k970zgqjht2fchatn5swc4tf2s83gd16",
            "latest": "k970zgqjht2fchatn5swc4tf2s83gd16",
            "llm": "k970zgqjht2fchatn5swc4tf2s83gd16",
            "production": "k970zgqjht2fchatn5swc4tf2s83gd16",
            "rag": "k970zgqjht2fchatn5swc4tf2s83gd16",
            "retrieval": "k970zgqjht2fchatn5swc4tf2s83gd16",
            "vector": "k970zgqjht2fchatn5swc4tf2s83gd16"
        },
        "updatedAt": 1774327607873
    }
}