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AWS Systems Manager Runbook-Engine

Führt automatisierte Diagnosen mit der AWS Systems Manager Automation API und SSM-Dokumenten aus. Sammelt Systemmetriken über die CloudWatch GetMetricData API und korreliert sie mit AWS Health-Ereignissen.

Was ist AWS Systems Manager Runbook-Engine?

Die AWS Systems Manager Runbook-Engine ist ein Skill für KI-Agenten, der automatisierte Diagnose-Workflows auf AWS-Infrastruktur ermöglicht. Er nutzt die AWS Systems Manager Automation API und SSM-Dokumente, um standardisierte Reparatur- und Diagnosevorgänge (Runbooks) auszuführen. Zusätzlich werden Systemmetriken wie CPU-Auslastung oder Speicherverbrauch über die CloudWatch GetMetricData API erfasst und mit AWS Health-Ereignissen (z.B. Serviceausfälle, geplante Wartungen) korreliert, um eine umfassende Ursachenanalyse zu unterstützen. Der Skill ist ideal für DevOps-Teams und Plattformingenieure, die Fehlerbehebungsprozesse automatisieren und die Betriebsstabilität ihrer AWS-Umgebungen verbessern möchten. Er ist mit führenden KI-Agenten-Plattformen wie Claude Code, Cursor und Codex kompatibel und wird direkt aus dem AWS SDK für JavaScript (v3) bezogen. Die Konfiguration erfolgt über Umgebungsvariablen wie AWS_REGION und AWS_PROFILE, die typischen AWS-Credential-Chain folgen. Durch die Integration mit dem Agent Skill Exchange können Benutzer den Skill einfach in ihre Workflows einbinden und von einer aktiven Community profitieren.

Funktioniert mit~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/agentskillexchange/skills/tree/main/skills/aws-ssm-runbook-engine
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Dokumentation

Was macht AWS Systems Manager Runbook-Engine?

Führt automatisierte Diagnosen mit der AWS Systems Manager Automation API und SSM-Dokumenten aus. Sammelt Systemmetriken über die CloudWatch GetMetricData API und korreliert sie mit AWS Health-Ereignissen.

Installation

Verwende den upstream-Installations- oder Einrichtungspfad, der zu deiner Umgebung passt:

  • Lass uns gemeinsam ein Projekt einrichten, das von DynamoDB aus dem SDK abhängt und einen einfachen Service-Aufruf durchführt. Die folgenden Schritte verwenden yarn als Beispiel. Diese Schritte setzen voraus, dass Node.js und yarn bereits installiert sind.
  • git clone https://github.com/aws/aws-sdk-js-v3.git
  • yarn && yarn test:all
  • yarn pack .

Anforderungen und Hinweise aus dem Upstream:

Grundlegende Verwendung oder erste Schritte:

Quelle

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

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act Local GitHub Actions Runner

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Add a browser review checkpoint before risky agent actions with

Use AgentClick when an agent should pause before risky commands, plans, drafts, or code changes so a human can inspect, edit, approve, or reject them in a purpose-built browser UI.

Add Claude design-system and accessibility workflows with UX/UI

Use UX/UI Agent Skills when Claude should generate tokens, component specs, accessibility audits, and framework-specific UI code from a repeatable design workflow.

Add executable smoke tests for shell scripts and CLIs before ref

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Add graph-backed memory and context retrieval to agent workflows

Use Cognee to ingest project knowledge into graph and vector memory so agents can retrieve durable context across sessions and workflows.

Add IDE-style semantic code navigation and symbol-safe refactors

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Add multimodal lifelong memory to MCP and Python agents with Sim

Use SimpleMem to store, compress, index, and retrieve text or multimodal memories for agents through MCP or Python integrations.

Add persistent project memory and hook-driven synthesis with Cla

Keep Claude Code sessions grounded in prior decisions, project context, and daily handoff notes instead of starting from zero every time.

Add Postgres-native vector retrieval to agent and RAG workflows

Store embeddings beside application data in Postgres, create vector indexes, and query nearest neighbors for semantic search, RAG, recommendations, or agent memory retrieval.

Address GitHub PR review comments from the current branch with g

Find the open PR for the current branch, gather unresolved review comments, and drive a focused comment-resolution workflow with gh-authenticated context.

Add runtime guardrails to TypeScript agents with VoltAgent

Use VoltAgent to intercept, validate, and enforce input/output policies in TypeScript agent workflows.

Add temporal context memory to agent workflows with Zep

Use Zep as an external context layer for agents that need to store events, assemble temporal graph context, and retrieve relevant memory before model calls.

Adobe Firefly API Batch Image Generator

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