everything-claude-code 是做什么的？
端到端的营销活动规划与执行。涵盖受众研究、定位、活动角度定义、落地页文案、邮件序列、社交媒体帖子、广告文案、短视频脚本和内容日历。用作多渠道产品发布的中枢协调层。在规划或执行多渠道产品发布，或制作落地页、邮件、社交媒体、广告文案时使用。
端到端的营销活动规划与执行，涵盖受众研究、定位、活动角度定义、落地页文案、邮件序列、社交媒体帖子、广告文案、短视频脚本和内容日历。用作多渠道产品发布的中枢协调层。
该技能为端到端的营销活动规划与执行工具，旨在帮助开发者或AI代理用户高效完成多渠道产品发布的全流程营销工作。其核心价值在于提供一个统一的协调层，将受众研究、品牌定位、活动策略、内容创作（如落地页、邮件、社交媒体、广告、短视频脚本）以及内容日历管理整合到单一工作流中。支持Claude Code等AI代理平台，通过结构化文档（SKILL.md）指导代理按步骤执行营销任务，减少手动切换工具或重复劳动。使用时，用户只需输入产品/活动的基本信息，代理即可自动生成从策略到执行层的完整营销资产，并支持根据反馈迭代优化。该技能特别适用于需要快速启动营销活动、确保跨渠道内容一致性或缺乏专职营销人员的技术团队。
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/manim-video端到端的营销活动规划与执行。涵盖受众研究、定位、活动角度定义、落地页文案、邮件序列、社交媒体帖子、广告文案、短视频脚本和内容日历。用作多渠道产品发布的中枢协调层。在规划或执行多渠道产品发布，或制作落地页、邮件、社交媒体、广告文案时使用。
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.