Agent Workflow Claude Skills
4 121 agent workflow skills from 665 authors. They configure the agents themselves: memory, prompts, context and other skills. Half of them fit into 1 845 tokens or less — that is what one costs your context window when the agent loads it. 778 ship runnable scripts rather than instructions alone. 5 of them cannot work without an MCP server, most often task. We also found 541 copies of these same skills sitting in other people's repositories — counted once here, not 541 times.
4 121 unique 665 authors 2 764 updated this month 506 from vendors
Transform legacy codebases into AI-ready projects with Claude Code configurations. Use when (1) analyzing old projects to generate AI coding configurations, (2) creating CLAUDE.md, skills, subagents, slash commands, hooks, or rules for existing projects, (3) user wants to enable vibe coding for a codebase, (4) onboarding new team members with AI-assisted development, (5) user mentions "make project AI-ready", "generate Claude config", or "create coding standards for AI".
Guide for removing skills from an existing workflow and updating all related documentation. Use when user wants to remove skills from a workflow (e.g., "remove skill", "delete skill", "移除技能", "删除技能").
Search and discover Claude Code skills and MCP servers from marketplaces, GitHub repositories, and registries. Use when (1) user asks to find skills for a specific task, (2) looking for MCP servers to connect external tools, (3) user mentions "find skill", "search MCP", "discover tools", or "what skills exist for X", (4) before creating a custom skill to check if one already exists.
Download and install Claude Code skills from various sources. Supports GitHub repositories, compressed archives (.zip, .tar.gz, .skill), and direct URLs. Use when user wants to download, install, or add a skill from GitHub, URL, or archive file. Triggers on "download skill", "install skill", "add skill from", "get skill".
Create complete Claude Code workflow directories with curated skills. Use when user wants to (1) create a new workflow for specific use case (media creator, developer, marketer, etc.), (2) set up a Claude Code project with pre-configured skills, (3) download and organize skills from GitHub repositories, or (4) generate README.md and AGENTS.md documentation for workflows. Triggers on phrases like "create workflow", "new workflow", "set up workflow", "build a xxx-workflow".
Use when designing organizational structure (team topologies, Conway's Law alignment), mapping stakeholders by power-interest for change initiatives, defining team interface contracts (APIs, SLAs, decision rights, handoffs), assessing capability maturity (DORA, CMMC, agile maturity models), planning org restructures (functional to product teams, platform teams, shared services), or when user mentions "org design", "team structure", "stakeholder map", "team interfaces", "capability maturity", "Conway's Law", or "RACI".
Instagram Graph API integration via curl. Use this skill to fetch and publish Instagram media.
n8n workflow automation knowledge base. Provides n8n node information, node functionality details, workflow patterns, and configuration examples. Covers triggers, data transformation, data input/output, AI integration, covering 10 nodes. Keywords: n8n, workflow, automation, node, trigger, webhook, http request, database, ai agent.
> Jetpack Compose and Compose Multiplatform (KMP/CMP) architecture skill. Only use when the user explicitly mentions "compose-skill", "@compose-skill", or "use compose skill" in their message. Do NOT auto-activate based on keyword matching — this skill should only be triggered by direct user request.
Guides Claude in creating well-structured SKILL.md files following best practices. Provides clear guidelines for naming, structure, and content organization to make skills easy to discover and execute.
Use when monitoring stocks/ETFs/indices across pre-market, open, intraday, or close — especially when the user is reading session action live and may revise their take as it unfolds. Triggers include 盘前/盘中/收盘 sessions, multi-symbol watchlists (e.g. MU/TSM/SMH semi tracking), user observations like "突破"/"冲高"/"回调"/"假突破", capital flow checks, market temperature checks, semi/AI/memory plays, and any request that bundles a position context with a live read.
> Short-term multi-timeframe (5m/15m/1h) technical read for a single symbol — pulls K-line across three timeframes, reads MACD + swing structure, writes a direction call (long/short/neutral) with an explicit anchor price, a 2–4 scenario forward read, a range-bound playbook (long tactic + short tactic; a neutral call carries a numeric low/high zone instead of an entry plan and is scored on whether the zone held), an entry/stop/target plan with dual-basis R/R (T1 + T2) for directional calls only, position sizing with a nominal cap from the live broker account, an event-risk gate (earnings / FOMC / CPI), and market/sector alignment + relvol volume checks — MACD divergence/背驰, candle patterns like Pin Bar, and 123 structures are auto-detected and drawn server-side — then renders it via the `chart` skill (type `intraday`, POST preview → PATCH prediction) and logs a journal entry. US-only, single-symbol, short horizon (intraday to a few sessions) — a companion to `market-session-tracker`, not a replacement. Pin Bar、入场点、盈亏比、short-term call, intraday prediction, entry point, risk reward ratio, multi-timeframe MACD.
Drive a complete DSPy 3.2.x project end-to-end — spec → program → metric → baseline → GEPA optimize → export → deploy. Orchestrates the other four DSPy skills (dspy-fundamentals, dspy-evaluation-harness, dspy-gepa-optimizer, dspy-rlm-module) in the correct order. Use this for any non-trivial DSPy build from scratch.
Analyzes and improves prompts using 31 frameworks across 7 intent categories. Use when a user wants to improve, rewrite, structure, or engineer a prompt — including requests like "help me write a better prompt", "improve this prompt", "what framework should I use", "make this prompt more effective", or any prompt engineering task. Recommends the right framework based on intent (create, transform, reason, critique, recover, clarify, agentic), asks targeted questions, and delivers a structured, high-quality result.
| 6-Phase 스킬 생성 워크플로우. revfactory/harness 방법론을 기반으로 체계적으로 새 스킬을 생성합니다. 요구사항 분석부터 최종 검증까지 전체 생명주기를 관리합니다.
| 스킬 품질 자동 검증 도구. 생성된 스킬의 테스트 케이스를 실행하고 baseline 대비 개선을 측정합니다. A/B 테스트, 회귀 테스트, 체인 테스트 + 4차원 스코어링 루브릭을 단일 스킬에 내장하여 self-contained로 동작합니다.
| Claude Design용 시니어 UX 프롬프트를 10가지 전문 패턴(정보 구조·디자인 시스템·카피·온보딩·접근성·대시보드·폼·테스트·휴리스틱·리서치) 중 적합한 것을 골라 완성해 줍니다.
| Claude Code 핸드오프 번들(README + design-tokens.json + components.json + layout-hierarchy.json + chat-history.md)을 분석해 요약 보고서와 Claude Code에 넘길 짧은 지시 1줄을 자동 생성합니다. 핸드오프 번들 구조를 한눈에 파악하고, 컴포넌트 트리·토큰·디자인 결정 맥락을 정리합니다.
| 강연·강의·세미나 본문 마크다운을 입력받아 (1) NotebookLM Studio에 그대로 붙여 넣을 슬라이드 데크 생성 프롬프트와 (2) 슬라이드별 나노바나나(Gemini 3 Pro Image, a.k.a. Nano Banana Pro) 5-Component 이미지 프롬프트를 동시 산출하는 prompt-builder 스킬. NotebookLM Studio의 공식 4축(Format/Length/Output language/Prompt)을 정확히 매핑하고, 슬라이드별 시각 자료는 Google DeepMind 공식 가이드의 5-Component 구조(Style·Subject·Setting·Action·Composition)에 따라 작성한다.
Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics
Build MCP servers with Node/TypeScript SDK — tools, resources, prompts, Zod validation, stdio vs Streamable HTTP. Use Context7 or official MCP docs for latest API.
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
Engineering operating model for teams where AI agents generate a large share of implementation output.
Patterns and architectures for autonomous Claude Code loops — from simple sequential pipelines to RFC-driven multi-agent DAG systems.
Orchestrate multi-agent coding tasks via Claude DevFleet — plan projects, dispatch parallel agents in isolated worktrees, monitor progress, and read structured reports.
Audits Claude Code context window consumption across agents, skills, MCP servers, and rules. Identifies bloat, redundant components, and produces prioritized token-savings recommendations.
Patterns for continuous autonomous agent loops with quality gates, evals, and recovery controls.
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。
Multi-agent orchestration using dmux (tmux pane manager for AI agents). Patterns for parallel agent workflows across Claude Code, Codex, OpenCode, and other harnesses. Use when running multiple agent sessions in parallel or coordinating multi-agent development workflows.
Operate long-lived agent workloads with observability, security boundaries, and lifecycle management.
Claude Codeセッションの正式な評価フレームワークで、評価駆動開発（EDD）の原則を実装します
Operate and extend NanoClaw v2, ECC's zero-dependency session-aware REPL built on claude -p.
>-
RFC-driven multi-agent DAG execution pattern with quality gates, merge queues, and work unit orchestration.
Scan skills to extract cross-cutting principles and distill them into rules — append, revise, or create new rule files
Use when auditing Claude skills and commands for quality. Supports Quick Scan (changed skills only) and Full Stocktake modes with sequential subagent batch evaluation.
AgentShield を使用して、Claude Code の設定（.claude/ ディレクトリ）のセキュリティ脆弱性、設定ミス、インジェクションリスクをスキャンします。CLAUDE.md、settings.json、MCP サーバー、フック、エージェント定義をチェックします。
Interactive agent picker for composing and dispatching parallel teams
A comprehensive verification system for Claude Code sessions.
Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics
Engineering operating model for teams where AI agents generate a large share of implementation output.
Patterns and architectures for autonomous Claude Code loops — from simple sequential pipelines to RFC-driven multi-agent DAG systems.
>- Turn a one-line objective into a step-by-step construction plan for multi-session, multi-agent engineering projects. Each step has a self-contained context brief so a fresh agent can execute it cold. Includes adversarial review gate, dependency graph, parallel step detection, anti-pattern catalog, and plan mutation protocol. complex multi-PR task, or describes work that needs multiple sessions. than 3 tool calls, or user says "just do it".
Orchestrate multi-agent coding tasks via Claude DevFleet — plan projects, dispatch parallel agents in isolated worktrees, monitor progress, and read structured reports.
Interactive installer for awesome claude notes — guides users through selecting and installing skills and rules to user-level or project-level directories, verifies paths, and optionally optimizes installed files.
Audits Claude Code context window consumption across agents, skills, MCP servers, and rules. Identifies bloat, redundant components, and produces prioritized token-savings recommendations.
Patterns for continuous autonomous agent loops with quality gates, evals, and recovery controls.
Automatically extract reusable patterns from Claude Code sessions and save them as learned skills for future use.