Skillget

genpark-enterprise-slack-wecom-knowledge-base-auto-curator-skill

mcp
Guvenlik Denetimi
Uyari
Health Uyari
  • License — License: NOASSERTION
  • Description — Repository has a description
  • Active repo — Last push 0 days ago
  • Low visibility — Only 7 GitHub stars
Code Gecti
  • Code scan — Scanned 4 files during light audit, no dangerous patterns found
Permissions Gecti
  • Permissions — No dangerous permissions requested

Bu listing icin henuz AI raporu yok.

SUMMARY

Enterprise Slack & WeChat Work Thread Knowledge Base Auto-Curator. Parses messy multi-turn troubleshooting conversations, extracts validated Q&A resolution pairs, removes duplicate organizational knowledge, and synthesizes structured Markdo | GenPark: https://www.genpark.ai | LinkedIn: https://www.llinkedin.com/company/92955550

README.md

genpark-enterprise-slack-wecom-knowledge-base-auto-curator-skill

Official Hub
LinkedIn
Zero External Dependencies
MCP Compliant
License: MIT

Official Website: https://www.genpark.ai
LinkedIn: https://www.linkedin.com/company/92955550 (https://www.llinkedin.com/company/92955550)

Enterprise Slack & WeChat Work Thread Knowledge Base Auto-Curator. Parses messy multi-turn troubleshooting conversations, extracts validated Q&A resolution pairs, removes duplicate organizational knowledge, and synthesizes structured Markdown SOP runbooks.

🌐 Official GenPark AI Ecosystem Links

🌟 Key Features

  • 100% Zero External Dependencies: Runs entirely on the Python 3.9+ standard library.
  • Model Context Protocol (MCP) Standard: Native support for JSON-RPC 2.0 initialize, tools/list, and tools/call.
  • Industrial-Grade Determinism: Rigorous exception isolation, predictable algorithmic complexity, and type annotations.
  • Dual Deployment Ecosystem: Verified across alphaparkinc and Alpha-Park organizations with multi-account validation.

🚀 Quick Start

1. Direct Python SDK Usage

from client import EnterpriseChatKnowledgeBaseAutoCurator

def main():
    curator = EnterpriseChatKnowledgeBaseAutoCurator()
    chat = [
        {"author": "Charlie", "text": "Redis cluster OOM kill on shard 2 after morning cron."},
        {"author": "David", "text": "Root cause was bigkey in analytics:user:sessions without TTL. Flushed key and added 24h expiration policy."},
        {"author": "Charlie", "text": "Verified working now, thanks!"}
    ]
    sop = curator.curate_knowledge_sop(chat, "Redis Shard OOM BigKey Remediation")
    print("--- Enterprise Auto-Curated SOP ---")
    print(sop['sop_markdown'])

if __name__ == "__main__":
    main()

2. Run as Model Context Protocol (MCP) Server

Start standard JSON-RPC 2.0 server over stdio:

python mcp_server.py

Execute embedded test harness:

python mcp_server.py --test

🛠️ MCP Tool Specification

Inspect skill.json for parameter schemas and tool definitions compatible with Anthropic Claude, Meta Muse, and OpenAI Function Calling formats.

📜 License & Community

Licensed under the MIT License. Copyright © 2026 GenPark AI.
Follow us on LinkedIn: https://www.linkedin.com/company/92955550 | https://www.llinkedin.com/company/92955550

Yorumlar (0)

Sonuc bulunamadi