Skills directory · page 17

SHA-256コンテンツハッシュを使用して、高コストなファイル処理結果をキャッシュします — パス非依存、自動無効化、サービスレイヤーの分離。

Cache expensive file processing results using SHA-256 content hashes — path-independent, auto-invalidating, with service layer separation. Use when repeated file processing is slow and results should be cached and invalidated by content rather than path.

Make a draft sound less like AI: fix generic, robotic text with rhythm, specifics, personality and brand voice. Use whenever the user says copy sounds like ChatGPT, bland or stiff, or not like them.

Write a blog post, article or guide end to end: research, outline, draft, SEO pass and quality gates. Use whenever the user asks to write a blog post, draft an article on a topic, or turn notes into a full piece.

Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section. Transforms your writing process from solo effort to collaborative partnership.

Use when deciding what content to create (topics, clusters, a blog or content plan), before listing ideas. Maps topic clusters with topic_cluster_mapper.py and ties each piece to a funnel stage and search demand.

Govern stable domain context with a narrowly scoped CONTEXT.md when needed, and route hard-to-reverse decisions to ECC's existing architecture-decision-records skill. Use when domain terms require repeated explanation, one term has multiple meanings, unclear language causes module-boundary mistakes, or domain semantics must remain separate from architecture decisions.

Routes live context checks to the native Codex or Claude Code meter without scanning files, and performs a bounded static component audit only when explicitly requested. Use for context-budget requests about remaining capacity or installed context overhead.

Audits Claude Code context window consumption across agents, skills, MCP servers, and rules. Identifies bloat and redundant components and provides prioritized token-saving recommendations.

エージェント、スキル、MCPサーバー、ルールにわたってClaude Codeのコンテキストウィンドウ消費を監査します。肥大化、冗長なコンポーネントを特定し、優先順位付けされたトークン節約の推奨事項を生成します。

Create, audit, and maintain project context documents for continuity across AI sessions. Use when establishing a context-docs convention, refreshing project state after work, or consolidating stale or growing context files. Adapt to existing layouts and preserve decisions and evidence. Not for general copyediting or storing conversation transcripts.

Create, audit, and maintain project context documents and Markdown progress views for continuity across AI sessions. Use when establishing context conventions, refreshing project state, visualizing progress toward a documented goal, or consolidating stale context. Adapt to existing layouts and preserve decisions and evidence. Not for general copyediting or storing conversation transcripts.

Create, audit, and maintain project context documents for continuity across AI sessions. Use when establishing a context-docs convention, refreshing project state after work, or consolidating stale or growing context files. Adapt to existing layouts and preserve decisions and evidence. Not for general copyediting or storing conversation transcripts.

Create, audit, and maintain project context documents for continuity across AI sessions. Use when establishing a context-docs convention, refreshing project state after work, or consolidating stale or growing context files. Adapt to existing layouts and preserve decisions and evidence. Not for general copyediting or storing conversation transcripts.

Use when starting a C-suite advisor session, when company context is missing or older than 90 days, or before company data goes to an external service. Loads and enriches ~/.claude/company-context.md and applies anonymization rules.

Generate a map of all files relevant to a task before making changes

Strategies for managing LLM context windows including summarization, trimming, routing, and avoiding context rot Use when: context window, token limit, context management, context engineering, long context.

Automatically fetch latest library/framework documentation for Claude Code via Context7 API

Guide for implementing continual learning in AI coding agents — hooks, memory scoping, reflection patterns. Use when setting up learning infrastructure for agents.

Patterns for continuous autonomous agent loops with quality gates, evals, and recovery controls. Use when running an agent loop that must self-check, gate on evals, and recover from failures.

[DEPRECATED - use continuous-learning-v2] Legacy v1 stop-hook skill extractor. v2 is a strict superset with instinct-based, project-scoped, hook-reliable learning. Do not invoke v1: when continuous learning, session learning, or pattern extraction is requested, route to continuous-learning-v2 instead.

Claude Code oturumlarından yeniden kullanılabilir kalıpları otomatik olarak çıkarın ve gelecekte kullanmak üzere öğrenilmiş skill'ler olarak kaydedin.

Claude Codeセッションから再利用可能なパターンを自動的に抽出し、将来の使用のために学習済みスキルとして保存します。

Automatically extract reusable patterns from Claude Code sessions and save them as learned skills for future use.

[OBSOLETO - usar continuous-learning-v2] Extractor de skill por hook Stop v1 heredado. v2 es un superconjunto estricto con aprendizaje basado en instintos, con alcance de proyecto y hooks confiables. No invocar v1; dirigir solicitudes de aprendizaje continuo, aprendizaje de sesión y extracción de patrones a continuous-learning-v2.

Claude Code 세션에서 재사용 가능한 패턴을 자동으로 추출하여 향후 사용을 위한 학습된 스킬로 저장합니다.

Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents. v2.1 adds project-scoped instincts to prevent cross-project contamination.

フックを介してセッションを観察し、信頼度スコアリング付きのアトミックなインスティンクトを作成し、スキル/コマンド/エージェントに進化させるインスティンクトベースの学習システム。

Hook'lar aracılığıyla oturumları gözlemleyen, güven skorlaması ile atomik instinct'ler oluşturan ve bunları skill/command/agent'lara evriltiren instinct tabanlı öğrenme sistemi. v2.1 çapraz proje kontaminasyonunu önlemek için proje kapsamlı instinct'ler ekler.

Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents. v2.1 adds project-scoped instincts to prevent cross-project contamination. Use when capturing lessons from a session, managing instincts, or promoting them into skills, commands, or agents.

Sistema de aprendizaje basado en instintos que observa sesiones mediante hooks, crea instintos atómicos con puntuación de confianza y los evoluciona en skills/comandos/agentes. v2.1 agrega instintos con alcance de proyecto para prevenir contaminación entre proyectos.

Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents.

훅을 통해 세션을 관찰하고, 신뢰도 점수가 있는 원자적 본능을 생성하며, 이를 스킬/명령어/에이전트로 진화시키는 본능 기반 학습 시스템. v2.1에서는 프로젝트 간 오염을 방지하기 위한 프로젝트 범위 본능이 추가되었습니다.

Use when drafting a freelance contract, proposal, SOW, NDA or MSA for US, EU, UK or DACH jurisdictions. Writes structured Markdown with docx conversion steps; not legal advice.

Produce a deliverable against an explicit, measurable contract — a length budget, citation discipline, required section numbering. Freeze the evidence packet first, draft in parallel against it, assemble to the number instead of re-prompting, verify with the contract's own measuring rule, then publish the artifact and its evidence. Use when acceptance is countable. Not for open-ended prose whose quality is the only gate, and not for auditing a report already delivered.

Coordinate frontend/backend or service-to-service work through one authoritative machine-checkable contract (OpenAPI, AsyncAPI, Protocol Buffers, or JSON Schema), with generated consumer types and contract-verified integration. Use when parallel consumer and provider work must evolve an API or event schema without field drift, mock/production shape mismatch, or one side silently redefining the interface.

Reviews staged changes and drafts a Conventional Commits-compliant commit message with the right type, scope, and length. Use before committing, or when the user asks to write, fix, or review a commit message.

Persistent memory systems for LLM conversations including short-term, long-term, and entity-based memory Use when: conversation memory, remember, memory persistence, long-term memory, chat history.

Convex reactive backend expert: schema design, TypeScript functions, real-time subscriptions, auth, file storage, scheduling, and deployment.

Use for operations leadership: process design, OKR execution, operating cadence, bottlenecks or scaling playbooks. Tracks OKRs with okr_tracker.py and analyzes efficiency with ops_efficiency_analyzer.py.

Technology-agnostic blueprint generator for creating comprehensive copilot-instructions.md files that guide GitHub Copilot to produce code consistent with project standards, architecture patterns, and exact technology versions by analyzing existing codebase patterns and avoiding assumptions.

Build applications powered by GitHub Copilot using the Copilot SDK. Use when creating programmatic integrations with Copilot across Node.js/TypeScript, Python, Go, or .NET. Covers session management, custom tools, streaming, hooks, MCP servers, BYOK providers, session persistence, custom agents, skills, and deployment patterns. Requires GitHub Copilot CLI installed and a GitHub Copilot subscription (unless using BYOK).

When the user wants to edit, review, or improve existing marketing copy. Also use when the user mentions 'edit this copy,' 'review my copy,' 'copy feedback,' 'proofread,' 'polish this,' 'make this better,' or 'copy sweep.' This skill provides a systematic approach to editing marketing copy through multiple focused passes.

Edit, proofread and tighten existing marketing copy in focused passes: clarity, voice, proofreading, specificity, readability and AI tells. Use whenever the user asks to polish, clean up, shorten or fix the wording of a page, email or ad.

Ative esta skill quando o usuário precisar de estratégia de copy, criar persona/avatar de cliente, mapear a jornada do lead (use case map, UCM, mapa de consciência, funil), entender o avatar, construir perfil de cliente ideal (ICP), identificar dores e desejos, escrever copy persuasiva com base estratégica, criar landing page, VSL, anúncio, e-mail, sequência de funil, ou qualquer entregável de conversão que precise de fundamentação estratégica antes de escrever. Acione também quando o usuário mencionar JTBD (jobs to be done), nível de consciência de mercado, sofisticação de mercado, Big Idea, mecanismo único, narrativa de venda, posicionamento, objeções do avatar, ou quando quiser criar copy mas ainda não tem persona definida. Esta skill é o passo ANTES e DURANTE a escrita de copy — ela engenheira a estratégia que torna a copy inevitável.

Copy the active Claude Code or Codex CLI chat transcript path to the macOS clipboard.

When the user wants to write, rewrite, or improve marketing copy for any page — including homepage, landing pages, pricing pages, feature pages, about pages, or product pages. Also use when the user says "write copy for," "improve this copy," "rewrite this page," "marketing copy," "headline help," or "CTA copy." For email copy, see email-sequence. For popup copy, see popup-cro.

Use for any headline, tagline, CTA, landing, pricing or about-page copy request, before drafting. Scores candidate headlines with headline_scorer.py and applies a page-section framework, so the first draft is tested rather than guessed.

Core component library and design system patterns. Use when building UI, using design tokens, or working with the component library.

Optimize Core Web Vitals (LCP, INP, CLS) for better page experience and search ranking. Use when asked to "improve Core Web Vitals", "fix LCP", "reduce CLS", "optimize INP", "page experience optimization", or "fix layout shifts".