Agent Workflow Claude Skills
4 122 agent workflow skills from 665 authors. They configure the agents themselves: memory, prompts, context and other skills. Half of them fit into 1 844 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 589 copies of these same skills sitting in other people's repositories — counted once here, not 589 times.
4 122 unique 665 authors 4 updated this month 506 from vendors
Generate cinematic film-style video prompts for Seedance 2.0 on Higgsfield. Use whenever the user wants cinematic, film-like, movie-quality, Hollywood-style, dramatic, or professional film-quality AI video. Triggers on: cinematic, film look, movie scene, dramatic lighting, depth of field, lens flare, anamorphic, letterbox, noir, epic, Steadicam, dolly, crane shot, or any cinematic video generation request. Always use this skill even if the user doesn't explicitly say "cinematic" but describes a film-like aesthetic.
Generate brand storytelling and narrative video prompts for Seedance 2.0 on Higgsfield. Use whenever the user wants to create a brand story video, company origin story, mission video, about us video, brand film, corporate narrative, founder story, brand anthem, company culture video, or emotional brand content. Triggers on: brand story, brand video, company story, origin story, about us, mission video, brand film, brand anthem, corporate video, company culture, founder story, brand narrative, or any request for brand/company storytelling video. Use even for "tell our company story" or "make a video about our mission.
Use when writing, completing, improving, or adapting SKILL.md and agents/*.md in a bundle-plugin — integrating external skills, filling scaffolded stubs, or rewriting for better triggering and token efficiency
Use when reviewing a bundle-plugin for structural issues, version drift, skill quality, workflow integration, or security risks — before releasing, after changes, or after adding skills. Auto-detects scope (full project vs skill vs workflow)
Use when optimizing a bundle-plugin or single skill — improving descriptions, reducing tokens, fixing audit findings, restructuring workflows, adding skills to fill gaps, or iterating on user feedback
>- Use when writing, testing, or preparing ANY contribution or pull request to the JSONbored/awesome-claude (HeyClaude) repo — adding a community content entry (agent/MCP server/skill/hook/command/rule/guide/collection/statusline), or making a platform/code change (website, registry package, MCP package, scripts). The repo has single-file content PRs, and the shared gittensory-orb bot that posts an advisory readiness/linked-issue comment on platform/code PRs but does not itself merge or close content PRs. Unlike JSONbored/gittensory and JSONbored/metagraphed, a linked issue is OPTIONAL here — do not import their mandatory-linked-issue rule into this repo. Invoke for any "contribute to / open a PR against / submit an entry to / fix a bug in awesome-claude (HeyClaude)" task.
Transform user requests into detailed, precise prompts for AI models. Use when users say "promptify", "promptify this", or explicitly request prompt engineering or improvement of their request for better AI responses.
Use when you have a pre-registered analysis plan to execute inline in this session with review checkpoints, on a platform without subagents
Use when executing a pre-registered analysis plan with mostly independent steps in the current session
Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
Add new skills to an existing workflow and update all related documentation. Use when user wants to add skills from GitHub URLs to a workflow (e.g., "add this skill to the workflow", "为工作流添加技能"). Triggers on adding skills to workflows, updating workflow documentation after skill additions.
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.
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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.