모든-클로드-코드 마케팅 캠페인은(는) 무엇을 하나요?
엔드투엔드 마케팅 캠페인 기획 및 실행. 잠재고객 조사, 포지셔닝, 캠페인 각도 정의, 랜딩 페이지 카피, 이메일 시퀀스, 소셜 게시물, 광고 카피, 숏폼 비디오 스크립트 및 콘텐츠 캘린더를 다룹니다. 다채널 제품 출시를 위한 오케스트레이션 계층으로 사용하세요. 다채널 제품 출시를 기획하거나 실행할 때, 또는 랜딩 페이지, 이메일, 소셜, 광고 카피를 제작할 때 사용하세요.
엔드투엔드 마케팅 캠페인 기획 및 실행. 잠재고객 조사, 포지셔닝, 캠페인 각도 정의, 랜딩 페이지 카피, 이메일 시퀀스, 소셜 게시물, 광고 카피, 숏폼 비디오 스크립트 및 콘텐츠 캘린더를 다룹니다. 다채널 제품 출시를 위한 오케스트레이션 계층으로 사용하세요.
이 스킬은 개발자와 AI 에이전트 사용자가 마케팅 캠페인의 전체 생애주기를 단일 프롬프트로 기획하고 실행할 수 있도록 설계되었습니다. 잠재고객 조사부터 콘텐츠 캘린더 생성까지 마케팅 파이프라인의 모든 단계를 포괄합니다. Claude Code, Cursor, Codex 등의 AI 어시스턴트와 호환되며, 사용자는 자연어로 캠페인 목표를 설명하기만 하면 됩니다. 내부적으로는 구조화된 프롬프트 체인을 사용하여 브랜드 전략과 일치하는 일관된 마케팅 자산을 생성합니다. 랜딩 페이지 카피, 이메일 시퀀스, 소셜 미디어 게시물, 광고 카피, 숏폼 비디오 스크립트를 자동으로 생성하여 수작업을 최소화하고 다채널 출시 속도를 높입니다.
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/manim-video엔드투엔드 마케팅 캠페인 기획 및 실행. 잠재고객 조사, 포지셔닝, 캠페인 각도 정의, 랜딩 페이지 카피, 이메일 시퀀스, 소셜 게시물, 광고 카피, 숏폼 비디오 스크립트 및 콘텐츠 캘린더를 다룹니다. 다채널 제품 출시를 위한 오케스트레이션 계층으로 사용하세요. 다채널 제품 출시를 기획하거나 실행할 때, 또는 랜딩 페이지, 이메일, 소셜, 광고 카피를 제작할 때 사용하세요.
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.
Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.
Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.
Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.
Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.
gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.
Example project-specific skill template based on a real production application.
Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
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.
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.
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...
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.