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genpark-enterprise-incident-postmortem-root-cause-synthesizer-skill

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SUMMARY

Enterprise SRE Incident Postmortem & Root Cause Synthesizer. Correlates distributed telemetry alarms across microservice dependency DAGs, isolates the First Bad Event root cause, traces downstream cascading blast radius, and generates autom | GenPark: https://www.genpark.ai | LinkedIn: https://www.llinkedin.com/company/92955550

README.md

genpark-enterprise-incident-postmortem-root-cause-synthesizer-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 SRE Incident Postmortem & Root Cause Synthesizer. Correlates distributed telemetry alarms across microservice dependency DAGs, isolates the First Bad Event root cause, traces downstream cascading blast radius, and generates automated 5-Whys causal chains with actionable preventative remediation tasks.

🌐 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 EnterpriseIncidentPostmortemRootCauseSynthesizer

def main():
    synth = EnterpriseIncidentPostmortemRootCauseSynthesizer()
    payload = {
        "incident_id": "INC-7741",
        "title": "WeChat Work Integration Webhook Cascade Drop",
        "severity": "P1",
        "alarms": [
            {"timestamp_epoch": 1760000000, "service": "token-verifier", "metric": "memory_leak_oom"},
            {"timestamp_epoch": 1760000020, "service": "msg-router", "metric": "queue_overflow"}
        ],
        "service_dependencies": {
            "token-verifier": ["msg-router", "audit-logger"],
            "msg-router": ["bot-dispatcher"]
        },
        "suspected_trigger": "Cert Renewal Script"
    }
    report = synth.synthesize_postmortem(payload)
    print(f"=== Postmortem Report: {report['incident_id']} ({report['severity']}) ===")
    print(f"Root Cause Service: {report['root_service']}")
    print(f"Blast Radius ({report['blast_radius_service_count']} svcs): {', '.join(report['cascading_blast_radius'])}")
    print("\nFive Whys:")
    for why in report['five_whys_analysis']:
        print(f"  {why}")

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

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