비디오와 오디오를 보고(Sees), 이해하고(Understands), 조치합니다(Acts). 로컬 파일, URL, RTSP/라이브 피드, 데스크톱 녹화 등 다양한 소스에서 미디어를 처리하고, 프레임 추출, 인덱싱, 검색, 트랜스코딩, 타임라인 편집 및 미디어 자산 생성을 수행합니다.
ECC(Enhanced Cognitive Clip)는 개발자와 AI 에이전트가 비디오 및 오디오 미디어를 정교하게 제어할 수 있도록 설계된 강력한 스킬입니다. '보기(See)' 단계에서는 로컬 파일, 웹 URL, RTSP 스트림, 데스크톱 실시간 녹화 등 다양한 입력 소스를 지원하며, 재생 가능한 스트림 링크와 실시간 컨텍스트를 반환합니다. '이해하기(Understand)' 단계에서는 프레임을 추출하고, 시각적, 의미론적, 시간적 인덱스를 구축하여 타임스탬프와 자동 클립 기능으로 특정 장면을 검색할 수 있게 해줍니다. '조치하기(Act)' 단계에서는 코덱, FPS, 해상도, 종횡비를 조정하는 트랜스코딩 및 정규화, 자막, 텍스트/이미지 오버레이, 브랜딩, 오디오 오버레이, 더빙, 번역을 포함한 타임라인 편집, 그리고 이미지 및 오디오 파일과 같은 미디어 자산 생성을 지원합니다. 이 스킬은 Claude Code, Cursor, Codex와 같은 주요 AI 에이전트 플랫폼과 호환되며, 미디어 처리 워크플로우를 자동화하여 개발 시간을 크게 단축시킵니다. SKILL.md 문서에 정의된 대로, ECC는 미디어 파이프라인을 구축하고, 라이브 스트림을 분석하며, 콘텐츠 제작을 간소화하려는 모든 개발자에게 필수적인 도구입니다.
npx skills add affaan-m/ECC비디오와 오디오를 보고(Sees), 이해하고(Understands), 조치합니다(Acts). 보기 - 로컬 파일, URL, RTSP/라이브 피드 또는 데스크톱 실시간 녹화에서 미디어를 수집하고, 실시간 컨텍스트와 재생 가능한 스트림 링크를 반환합니다. 이해하기 - 프레임을 추출하고, 시각적/의미론적/시간적 인덱스를 구축하며, 타임스탬프와 자동 클립으로 특정 순간을 검색합니다. 조치하기 - 트랜스코딩 및 정규화(코덱, FPS, 해상도, 종횡비), 타임라인 편집(자막, 텍스트/이미지 오버레이, 브랜딩, 오디오 오버레이, 더빙, 번역), 미디어 자산 생성(이미지, 오디오...)을 수행합니다.
This repo contains 20 individual skills — each has its own dedicated page.
Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.
Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.
Multi-platform content distribution across X, LinkedIn, Threads, and Bluesky. Adapts content per platform using content-engine patterns. Never posts identical content cross-platform. Use when the user wants to distribute content across social platforms.
Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.
日本語翻訳：このファイルは manim-video 用の日本語翻訳が必要です
Remotion のベストプラクティス - React で動画を作成する。3D、アニメーション、音声、字幕、チャート、トランジションなどをカバーするドメイン固有の29のルール。
AI-assisted video editing workflows for cutting, structuring, and augmenting real footage. Covers the full pipeline from raw capture through FFmpeg, Remotion, ElevenLabs, fal.ai, and final polish in Descript or CapCut. Use when the user wants to edit video, cut footage, create vlogs, or build video content.
Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.
Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent
Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.
Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.
Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.
Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.
Use after completing any non-trivial task. The agent self-rates its output on 5 axes — accuracy, completeness, clarity, actionability, conciseness — with concrete evidence per criterion. Produces a structured 1-5 scorecard with specific improvement suggestions.
Build an evidence-backed ECC install plan for a specific repo by sorting skills, commands, rules, hooks, and extras into DAILY vs LIBRARY buckets using parallel repo-aware review passes. Use when ECC should be trimmed to what a project actually needs instead of loading the full bundle.
Engineering operating model for teams where AI agents generate a large share of implementation output. Use when setting team process, review gates, or ownership rules for a codebase largely written by agents.
Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code. Use when adding regression coverage to AI-assisted code, or when the same model both wrote and reviewed a change.
Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns. Use when structuring modules, layers, or data flow in an Android or KMP project.
Generates Angular code and provides architectural guidance. Trigger when creating projects, components, or services, or for best practices on reactivity (signals, linkedSignal, resource), forms, dependency injection, routing, SSR, accessibility (ARIA), animations, styling (component styles, Tailwind CSS), testing, or CLI tooling.
Extract frames or short clips from videos using ffmpeg.
Summarize or transcribe URLs, YouTube/videos, podcasts, articles, transcripts, PDFs, and local files.
Use when testing, fixing, or extending the OpenClaw Control UI GUI with Vitest + Playwright end-to-end checks, mocked Gateway WebSocket flows, mocked dashboard runs, screenshots/videos, or agent-verifiable browser proof.
Obra superpowers agent skills.
End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.
Prevent silent decimal mismatch bugs across EVM chains. Covers runtime decimal lookup, chain-aware caching, bridged-token precision drift, and safe normalization for bots, dashboards, and DeFi tools. Use when handling token amounts across EVM chains, or when a balance, price, or transfer amount is off by orders of magnitude.