Claude Code, Cursor, Windsurf용 tooling work AI Agent Skills 모음입니다. 개발자 워크플로 자동화에 초점을 둡니다.
이 페이지는 실제 제품에서 AI Agent Skills를 개발하는 팀을 위해 실용적인 개발 도구를 선별했습니다. 핵심은 빠른 구현, 테스트 기반 검증, 통합 이슈 디버깅, IDE 중심의 안정적 릴리스 같은 실무 워크플로입니다. MCP 지원은 통합 기능 중 하나일 뿐, 주된 관점은 개발 생산성과 품질입니다.
Primary Install Bridge
Pick One Skill, Then Take the Install Path
This collection should not trap users in comparison mode or pretend to install the whole collection. Its job is to narrow the shortlist to one skill, then send the next click into installation, validation, and rollout. Installation happens on the skill path.
The Next Click Should Keep Narrowing, Not Reset Back To A Generic Directory
Once the install path is clear, move into the solution, CLI, or editorial surface that best matches this collection. That keeps platform, framework, and operations demand narrowing into a more verifiable high-intent journey.
Reviewed on 2026-04-17 against coding workflow fit, installation clarity, review and testing value, and release guardrails. This page is now positioned as an install-first developer workflow entry point instead of a vague tooling roundup.
We prioritize this page because developer-intent users usually need one toolchain they can install, validate, and prove inside a real coding loop before they standardize it across the team.
Trust Signals
- Entries are chosen for practical build, test, debug, review, and release value inside real developer workflows.
- Selection favors tools with public docs and setup paths that teams can validate before rolling them into team defaults.
- The page is curated for repeatable engineering execution, not for vague AI developer branding or generic repo popularity.
Grouping Logic
- Lead with tools that improve delivery quality inside coding loops instead of broad curiosity-driven exploration.
- Keep the shortlist compact enough for quick comparison while still covering coding, testing, debugging, review, and release support.
- Use installation as the bridge from developer tooling discovery into validated day-to-day execution.
Maintenance & Review
Last Reviewed
2026-04-17
Cadence
Re-check when install flow, maintainer posture, or developer workflow relevance changes upstream; otherwise review monthly.
Maintained By
Killer-Skills editorial review within the recovery-focused authority queue.
Verification
Validate installability, workflow fit, operator clarity, and maintainer trust before retaining or adding an entry.
Execution Examples
How These Skills Work Together In Practice
Tighten one code-review loop first
Use this page when you need one developer workflow tool that can improve build, test, review, or release quality without expanding evaluation into another endless tool search.
1. Open the installation docs before opening more developer-tool repositories.
2. Choose one tool that best supports coding, testing, debugging, review, or release guardrails.
3. Install it and verify the CLI write path, sync behavior, and first operator checkpoint.
4. Only after the base path works, expand the setup across the wider team workflow.
Stabilize the test-and-release path
Treat the collection as an editorial filter when you need tools that improve developer output quality without piling another vague platform layer onto the stack.
1. Check whether the tool has stable ownership and visible install guidance.
2. Review CLI behavior so operators know what will be written, synced, and verified.
3. Use one validated coding path before scaling it to more repos or teammates.
4. Document the chosen developer workflow baseline after the first clean rollout.
This AI agent skill provides expert guidance on designing consistent, developer-friendly REST APIs, including resource naming, status codes, and pagination.
Build a fully automated AI-powered data collection agent for any public source — job boards, prices, news, GitHub, sports, anything. Scrapes on a schedule, enriches data with a free LLM (Gemini Flash), stores results in Notion/Sheets/Supabase, and learns from user feedback. Runs 100% free on GitH...
The django-verification skill automates testing, linting, and security scans for Django projects, ensuring quality and security before release or PR. It benefits developers by saving time and reducing errors.
The foundation-models-on-device skill enables developers to build AI-powered features using Apple Intelligence on-device, generating or summarizing text without cloud dependency. It helps developers create privacy-preserving AI features with custom tool calling and snapshot streaming.
This AI agent skill processes documents using the Nutrient DWS API, benefiting developers by automating tasks such as format conversion, text extraction, and data redaction. It helps with AI coding by streamlining document workflows.
This AI agent skill provides comprehensive Perl security guidelines, helping developers ensure secure coding practices and prevent common vulnerabilities.
The santa-method AI agent skill provides multi-agent adversarial verification, helping developers ensure code accuracy and compliance by utilizing two independent review agents.
The search-first AI agent skill systematizes the research-before-coding workflow, assisting developers in finding existing tools and libraries before implementing custom code. This skill benefits developers by saving time and reducing redundant code.
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, video), and create real time alerts for events from live streams or desktop capture.
Orchestrate multi-agent coding tasks via Claude DevFleet — plan projects, dispatch parallel agents in isolated worktrees, monitor progress, and read structured reports.
This AI agent skill streamlines C++ testing with GoogleTest and CMake, helping developers write and maintain robust tests. It automates test workflows for efficient code validation.
This AI agent skill provides a thorough Flutter/Dart code review, covering widget best practices, state management patterns, and clean architecture. Developers can improve their code quality and productivity with this skill.
The laravel-patterns skill provides production-grade Laravel architecture patterns for scalable and maintainable applications, benefiting developers with improved workflow and app performance.
Rules-distill is an AI agent skill that extracts cross-cutting principles from skills and distills them into rules, enhancing coding productivity. It benefits developers by automating rules maintenance and providing a deterministic collection of principles.
Use this skill when adding authentication, handling user input, working with secrets, creating API endpoints, or implementing payment/sensitive features. Provides comprehensive security checklist and patterns.
The energy-procurement skill helps senior energy managers optimize energy spend across multiple facilities. It analyzes tariff structures, identifies optimization opportunities, and evaluates demand charge mitigation strategies, leveraging AI coding for improved procurement decisions.
This AI agent skill enables retailers to optimize inventory levels through data-driven demand forecasting and automated replenishment planning, benefiting developers and retailers alike by minimizing stockouts and excess inventory.
The production-scheduling AI agent skill helps senior production schedulers optimize job sequencing, line balancing, and changeover optimization, benefiting production management, planning, quality, and maintenance teams by maximizing throughput and meeting customer delivery commitments.
# Browser QA — Automated Visual Testing & Interaction ## When to Use - After deploying a feature to staging/preview - When you need to verify UI behavior across pages - Before shipping — confirm layouts, forms, interactions actually work - When reviewing PRs that touch frontend code - Accessibili...
This AI agent skill provides universal coding standards, best practices, and patterns for TypeScript, JavaScript, React, and Node.js development, helping developers maintain high-quality codebases. It assists in enforcing naming conventions, formatting, and structural consistency.
exa-search is a neural search skill for AI coding assistants, helping developers find relevant information and code examples efficiently. It benefits developers by providing quick access to web content, company research, and people lookup.
Next.js Turbopack accelerates development with incremental bundling and file-system caching. Ideal for Next.js 16+ developers seeking faster startup and hot updates.
Plankton-code-quality enforces code quality at write-time, benefiting developers with auto-formatting, linting, and fixes via Claude subprocesses, enhancing overall coding efficiency.
Idiomatic Kotlin patterns, best practices, and conventions for building robust, efficient, and maintainable Kotlin applications with coroutines, null safety, and DSL builders.
# Product Lens — Think Before You Build ## When to Use - Before starting any feature — validate the "why" - Weekly product review — are we building the right thing? - When stuck choosing between features - Before a launch — sanity check the user journey - When converting a vague idea into a spec ...
Spring Security best practices for authn/authz, validation, CSRF, secrets, headers, rate limiting, and dependency security in Java Spring Boot services.
This AI agent skill enables developers to adopt Swift 6.2's concurrency model, ensuring single-threaded code by default and explicit background offloading. It helps resolve data-race safety compiler errors and optimizes app architecture.
This AI agent skill enables Swift developers to write testable code by abstracting external dependencies behind small, focused protocols, leveraging Swift Testing for deterministic results.
Continuous-learning-v2 is an advanced learning system that evolves Claude Code sessions into reusable knowledge, helping developers automate coding tasks through instinct-based behavior extraction and confidence scoring.
# Design System — Generate & Audit Visual Systems ## When to Use - Starting a new project that needs a design system - Auditing an existing codebase for visual consistency - Before a redesign — understand what you have - When the UI looks "off" but you can't pinpoint why - Reviewing PRs that touc...
Visualize whether skills, rules, and agent definitions are actually followed — auto-generates scenarios at 3 prompt strictness levels, runs agents, classifies behavioral sequences, and reports compliance rates with full tool call timelines
The deployment-patterns skill enables developers to optimize web application deployment workflows using CI/CD pipelines, Docker, and health checks, ensuring production readiness and zero downtime.
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.
This AI agent skill provides comprehensive Python testing strategies using pytest, TDD methodology, and best practices, helping developers write robust and maintainable code.
The continuous-learning skill automates pattern extraction from Claude Code sessions, saving developers time and effort. It identifies and saves useful patterns for future use, enhancing AI coding workflows.
This AI agent skill provides best practices for safe and reversible database migrations, benefiting developers working with PostgreSQL, MySQL, and common ORMs. It helps with schema changes, data migrations, and zero-downtime deployments.
This skill provides Nuxt 4 app patterns for hydration safety, performance, and SSR-safe data fetching, benefiting developers with optimized routing and rendering decisions.
The Architecture Decision Records skill helps developers capture and manage architectural decisions made during coding sessions. It auto-detects decision moments, records context, alternatives considered, and rationale, maintaining an ADR log for future reference.
Spring Boot architecture patterns, REST API design, layered services, data access, caching, async processing, and logging. Use for Java Spring Boot backend work.
X/Twitter API integration for posting tweets, threads, reading timelines, search, and analytics. Covers OAuth auth patterns, rate limits, and platform-native content posting. Use when the user wants to interact with X programmatically.
The agent-harness-construction skill enhances AI coding by optimizing action spaces, tool definitions, and observation formatting, benefiting developers with higher completion rates.
The iterative-retrieval skill refines context retrieval for subagents, solving the context problem in multi-agent workflows. It benefits developers by progressively refining context.
SwiftUI architecture patterns, state management with @Observable, view composition, navigation, performance optimization, and modern iOS/macOS UI best practices.
The investor-materials AI agent skill helps developers create and update investor-facing documents, ensuring consistency and credibility across pitch decks, one-pagers, and financial models. This skill benefits developers and founders by automating the process of generating investor materials.
AI-first engineering is a skill that helps developers design efficient processes, architectures, and code reviews for AI-assisted code generation, improving overall team productivity and code quality.
Use when we want to turn a just-finished Formax workflow (e.g. commands, overlays, tools, hooks, permissions, UI parity) into a reusable Codex Skill under .codex/skills, including scaffolding, guardrails, and the minimum test checklist.
Use when preparing a Formax code handoff: selecting files, generating repomix bundles, and writing a high-quality prompt for WebGPT or another coding agent with clear constraints and validation scope.
Use when adding or modifying generator scripts that write files; keeps generated artifacts out of docs/ and aligns script defaults with ownership paths plus CI gate updates.
Start here for all API mocking in tests. Covers auto-generation, fixtures, and when to use other skills. Required reading before creating, refactoring, or modifying any test involving API calls.
Test that components send correct query parameters or request arguments. Use when testing filtering, sorting, pagination, or any read operation where request parameters matter. Use for test-scoped mock customization.
Enter explore mode - a thinking partner for exploring ideas, investigating problems, and clarifying requirements. Use when the user wants to think through something before or during a change.
Manage git worktrees for parallel AI agent development. Use this when asked to create, list, open, close, or merge worktrees, or when working with wt-* commands.
If This Page Is Close, Keep Narrowing With Adjacent Authority Pages
Do not reset back to the generic directory. Move sideways through these adjacent high-intent collections to narrow the shortlist toward the install path that best matches your team.
This collection should not keep users browsing forever. These three questions explain how to shortlist, install, and validate the next step.
이 컬렉션들은 어떤 워크플로를 위해 만들어졌나요?
워크플로 자동화, 프로세스 자동화, 문서 작업, 데이터 워크플로 및 재사용 가능한 스킬 스택을 중심으로 구성되어 있습니다.
컬렉션과 메인 스킬 디렉터리의 차이점은?
스킬 디렉터리는 직접 검색과 필터링에 적합하고, 컬렉션은 완전한 워크플로를 위한 보완적 스킬 묶음을 찾는 데 적합합니다.
이 컬렉션들을 Claude Code나 Cursor에 설치할 수 있나요?
네. 이 컬렉션의 스킬들은 일반적으로 Claude Code, Cursor, Windsurf 및 기타 지원 환경에서 통합 설치 흐름으로 작동합니다.
Additional Recovery Paths
Use These Additional Paths If You Need One More Step To Narrow The Decision
These are the supporting surfaces for this collection after the install direction is clear and the primary next paths have already narrowed the decision.
