CloudWatch Logs Insights 쿼리와 이상 감지 API를 사용하여 AWS CloudWatch Logs에서 비정상적인 패턴을 감지합니다. 컨텍스트 로그 샘플과 함께 오류율 급증 및 지연 시간 회귀를 표면화합니다.
CloudWatch Log Anomaly Detector는 AWS CloudWatch Logs 내에서 비정상적인 패턴을 자동으로 감지하는 AI 에이전트 스킬입니다. CloudWatch Logs Insights 쿼리와 Anomaly Detection API를 활용하여 오류율 급증, 지연 시간 회귀, 비정상적인 토큰 변동과 같은 이상 징후를 실시간으로 식별합니다. 이 스킬은 개발자와 운영 팀이 인시던트를 사전에 탐지하고, 로그 샘플과 함께 컨텍스트를 제공하여 근본 원인 분석을 가속화하도록 돕습니다. AWS CloudWatch 환경에서 동작하며, 로그 이벤트의 패턴 변화를 분석하여 성능 저하나 오류 급증이 발생할 때 이를 표면화합니다.
npx skills add https://github.com/agentskillexchange/skills/tree/main/skills/cloudwatch-log-anomaly-detectorAWS CloudWatch Logs에서 CloudWatch Logs Insights 쿼리와 이상 감지 API를 사용하여 비정상적인 패턴을 감지합니다. 컨텍스트 로그 샘플과 함께 오류율 급증 및 지연 시간 회귀를 표면화합니다.
기본 사용법 또는 시작 참고 사항:
예를 들어, 다음 세 가지 로그 이벤트 샘플을 참조하세요.
값. 예를 들어, 특정 토큰 값이 갑자기 500% 증가하면
애플리케이션 성능이 저하되고 있습니다. 예를 들어, 평소보다 훨씬 많은 수의
출처: https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/LogsAnomalyDetection.html
This repo contains 20 individual skills — each has its own dedicated page.
Builds citation networks from Semantic Scholar API and CrossRef DOI metadata. Visualizes paper influence graphs using NetworkX, identifies seminal works, and tracks research lineage across fields.
Exposes Advanced Custom Fields data through the WordPress REST API using register_rest_field and acf_format_value. Handles repeater fields, flexible content layouts, and gallery fields with proper serialization.
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.
Converts Advanced Custom Fields field groups into native Gutenberg blocks using the ACF Block API v2 and @wordpress/scripts build pipeline. Maps ACF repeaters, groups, and flexible content to InnerBlocks and block attributes with server-side rendering via acf_register_block_type().
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.
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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 UX/UI Agent Skills when Claude should generate tokens, component specs, accessibility audits, and framework-specific UI code from a repeatable design workflow.
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.
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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.
Find the open PR for the current branch, gather unresolved review comments, and drive a focused comment-resolution workflow with gh-authenticated context.
Use VoltAgent to intercept, validate, and enforce input/output policies in TypeScript agent workflows.
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.
Calls Adobe Firefly
Extract frames or short clips from videos using ffmpeg.
Summarize or transcribe URLs, YouTube/videos, podcasts, articles, transcripts, PDFs, and local files.
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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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