使用 AWS SDK 的 DetectStackDrift 和 DescribeStackResourceDrifts API 监控 AWS CloudFormation 堆栈的配置漂移。生成修复模板，并与 AWS Config 规则集成以实现持续合规。
该技能旨在监控 AWS CloudFormation 堆栈的配置漂移，这是基础设施即代码 (IaC) 环境中确保环境一致性的关键功能。通过调用 AWS SDK 的 DetectStackDrift 和 DescribeStackResourceDrifts API，它能够检测堆栈实际状态与模板定义之间的差异，并生成修复模板以纠正漂移。该技能支持与 AWS Config 规则集成，实现持续合规监控，并适用于支持漂移检测的 AWS 资源。其主要功能包括自动化漂移检测、生成差异报告以及提供修复指导，适用于 Cursor 或 Claude Code 等 AI 代理平台。用户需具备 AWS 凭证和权限，使用前需确保资源支持漂移检测。该技能来自 Agent Skill Exchange，有助于简化云基础设施的运维和审计流程。
npx skills add https://github.com/agentskillexchange/skills/tree/main/skills/aws-cloudformation-drift-detector-4使用 AWS SDK 的 DetectStackDrift 和 DescribeStackResourceDrifts API 监控 AWS CloudFormation 堆栈的配置漂移。生成修复模板，并与 AWS Config 规则集成以实现持续合规。
上游的要求和注意事项：
基本用法或入门说明：
创建该资源的基础服务。例如，您可以使用 Amazon EC2 控制台
堆栈。例如，如果堆栈包含 AWS::EC2::Instance
例如，AWS::EC2::SecurityGroupIngress 和
来源：https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/using-cfn-stack-drift.html
This repo contains 20 individual skills — each has its own dedicated page.
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An ASE skill built around ACF Extended, the WordPress enhancement suite for Advanced Custom Fields that adds field types, admin improvements, front-end forms, options pages, and developer tooling. It is a practical fit for agents working inside complex WordPress content models and custom field workflows.
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Activepieces is an open-source, self-hostable workflow automation platform with 200+ integrations. It provides a visual builder for creating automated workflows and exposes all its connectors as MCP servers for AI agent use.
ActivityWatch is a privacy-first, open-source automated time tracker that records application usage, browser activity, and AFK status across Windows, macOS, and Linux. With 16k+ GitHub stars, it provides detailed productivity analytics without sending data to external servers.
act is an open-source CLI tool that runs GitHub Actions workflows locally using Docker, enabling fast feedback on workflow changes without pushing to GitHub. It is a standard tool for local Actions development and testing.
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Use Bats-core when an agent needs to turn fragile shell scripts or command-line workflows into something it can verify repeatedly after edits. The agent writes focused Bash tests for success paths, failure paths, and output contracts, then runs them locally or in CI before a refactor, release, or incident fix goes out.
Use Cognee to ingest project knowledge into graph and vector memory so agents can retrieve durable context across sessions and workflows.
Give a coding agent symbol-aware lookup, cross-file rename, and structural edit tools before it starts making brittle text-only changes.
Give LangGraph agents memory management and search tools so they can store, retrieve, and update durable facts across sessions.
Use SimpleMem to store, compress, index, and retrieve text or multimodal memories for agents through MCP or Python integrations.
Keep Claude Code sessions grounded in prior decisions, project context, and daily handoff notes instead of starting from zero every time.
Store embeddings beside application data in Postgres, create vector indexes, and query nearest neighbors for semantic search, RAG, recommendations, or agent memory retrieval.
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Use VoltAgent to intercept, validate, and enforce input/output policies in TypeScript agent workflows.
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Calls Adobe Firefly
Extract frames or short clips from videos using ffmpeg.
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Obra superpowers agent skills.
See, Understand, Act on video and audio. See- ingest from local files, URLs, RTSP/live feeds, or live record desktop; return realtime context and playable stream links. Understand- extract frames, build visual/semantic/temporal indexes, and search moments with timestamps and auto-clips. Act- transcode and normalize (codec, fps, resolution, aspect ratio), perform timeline edits (subtitles, text/image overlays, branding, audio overlays, dubbing, translation), generate media assets (image, audio...
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