CodeAppsStarter のデザインシステムを利用して Code Apps の UI を構築する。Use when: Code Apps デザイン, UI 設計, コンポーネント選定, 画面レイアウト, ギャラリー, テーブル, カンバン, ガントチャート, ダッシュボード, フォーム, shadcn, Tailwind, デザイン例, StatsCards, KanbanBoard, ListTable, InlineEditTable, SearchFilterGallery, GanttChart, TreeStructure
Opinionated, autonomous PR review for AGENTVIZ. Hunts for duplicate code, dead code, UI/UX style violations, missing tests, architecture drift, and slop. Run before opening a PR or to self-review your branch.
The basics of how to program GPUs using Mojo. Use this skill in addition to mojo-syntax when writing Mojo code that targets GPUs or other accelerators. Use targeting code to NVIDIA, AMD, Apple silicon GPUs, or others. Use this skill to overcome misconceptions about how Mojo GPU code is written.
Code file content generation guide. Use this skill when you need to create code files that can be previewed via `frago view`. Covers supported languages, theme selection, and best practices.
Assesses code comprehensibility and maintainability risk. Use when the user asks about code confidence, risk, maintainability, tech debt, code health, or whether code is safe to change. Also use when the user asks to analyze code quality, scan for risks, check if code is messy or complex, audit code, do a code checkup, find weak spots, assess what needs refactoring, or asks about code trust, hidden risks, gotchas, or onboarding to a codebase.
Write JavaScript code in n8n Code nodes. Use when writing JavaScript in n8n, using $input/$json/$node syntax, making HTTP requests with $helpers, working with dates using DateTime, troubleshooting Code node errors, or choosing between Code node modes.
Multi-agent orchestration framework for Claude Code. Automatically delegates tasks to cheaper, faster sub-agents (Haiku 4.5, Sonnet 4.6) while maintaining Opus-level quality through verification. Use when working on any coding task — Hydra activates automatically to route file exploration, test running, documentation, code writing, debugging, security scanning, and git operations to the optimal agent. Saves ~50% on API costs. --- # 🐉 Hydra — Multi-Headed Speculative Execution > *"Cut off one head, two more shall take its place."* > Except here — every head is doing your work faster and cheaper. ## ⛔ MANDATORY PROTOCOLS — NEVER SKIP These protocols are NON-NEGOTIABLE. Skipping them is a framework violation. ### Protocol 1: Sentinel Scan After Code Changes When ANY agent returns output containing `⚠️ HYDRA_SENTINEL_REQUIRED`, you MUST — before doing ANYTHING else, before presenting results to the user, before running any other agents — dispatch hydra-sentinel-scan with the files and changes listed in the trigger block. **This is blocking.** The user does NOT see the code changes until sentinel completes. If you present code changes to the user without running sentinel first, you have violated the framework's core safety guarantee.
Use after implementing features, before claiming a phase is complete, when reviewing AI-generated code, or when code feels overly complex. Also use when you notice repeated patterns across files, a function exceeds 40 lines, nesting exceeds 3 levels, or an abstraction has only one implementation. Covers duplication, dead code, over-engineering, and AI-specific bloat patterns like verbose error handling and redundant type checks.
Deploy code to Cloudflare Pages (static) or Azure Container Apps (dynamic). Use when the user says "/deploy", "배포해줘", "이거 올려줘", "publish this", "사이트 배포", "앱 배포", or wants to deploy code from a project to production.
Analyze code and LLM practices against Claude Code's production-grade engineering patterns. Use when the user asks to 'assess my code against Claude Code', 'how would Claude Code do this', 'what patterns does CC use for X', 'review my LLM approach', or invokes /what-would-cc-do:assess or /what-would-cc-do:claudecodefy.
Perform comprehensive code reviews with best practices, security checks, and constructive feedback. Use when reviewing pull requests, analyzing code quality, checking for security vulnerabilities, or providing code improvement suggestions. --- # Code Review Analysis ## Table of Contents - [Overview](#overview) - [When to Use](#when-to-use) - [Quick Start](#quick-start) - [Reference Guides](#reference-guides) - [Best Practices](#best-practices) ## Overview Systematic code review process covering code quality, security, performance, maintainability, and best practices following industry standards. ## When to Use - Reviewing pull requests and merge requests - Analyzing code quality before merging - Identifying security vulnerabilities - Providing constructive feedback to developers - Ensuring coding standards compliance - Mentoring through code review ## Quick Start
Detects code smells, anti-patterns, and debugging issues. Use when: fixing bugs, reviewing code quality, or refactoring.
skill-sample/ ├─ SKILL.md ⭐ Required: skill entry doc (purpose / usage / examples / deps) ├─ manifest.sample.json ⭐ Recommended: machine-readable metadata (index / validation / autofill) ├─ LICENSE.sample ⭐ Recommended: license & scope (open source / restriction / commercial) ├─ scripts/ │ └─ example-run.py ✅ Runnable example script for quick verification ├─ assets/ │ ├─ example-formatting-guide.md 🧩 Output conventions: layout / structure / style │ └─ example-template.tex 🧩 Templates: quickly generate standardized output └─ references/ 🧩 Knowledge base: methods / guides / best practices ├─ example-ref-structure.md 🧩 Structure reference ├─ example-ref-analysis.md 🧩 Analysis reference └─ example-ref-visuals.md 🧩 Visual reference
More Agent Skills specs Anthropic docs: https://agentskills.io/home
├─ ⭐ Required: YAML Frontmatter (must be at top) │ ├─ ⭐ name : unique skill name, follow naming convention │ └─ ⭐ description : include trigger keywords for matching │ ├─ ✅ Optional: Frontmatter extension fields │ ├─ ✅ license : license identifier │ ├─ ✅ compatibility : runtime constraints when needed │ ├─ ✅ metadata : key-value fields (author/version/source_url...) │ └─ 🧩 allowed-tools : tool whitelist (experimental) │ └─ ✅ Recommended: Markdown body (progressive disclosure) ├─ ✅ Overview / Purpose ├─ ✅ When to use ├─ ✅ Step-by-step ├─ ✅ Inputs / Outputs ├─ ✅ Examples ├─ 🧩 Files & References ├─ 🧩 Edge cases ├─ 🧩 Troubleshooting └─ 🧩 Safety notes
Skill files are scattered across GitHub and communities, difficult to search, and hard to evaluate. SkillWink organizes open-source skills into a searchable, filterable library you can directly download and use.
We provide keyword search, version updates, multi-metric ranking (downloads / likes / comments / updates), and open SKILL.md standards. You can also discuss usage and improvements on skill detail pages.
Quick Start:
Import/download skills (.zip/.skill), then place locally:
~/.claude/skills/ (Claude Code)
~/.codex/skills/ (Codex CLI)
One SKILL.md can be reused across tools.
Everything you need to know: what skills are, how they work, how to find/import them, and how to contribute.
A skill is a reusable capability package, usually including SKILL.md (purpose/IO/how-to) and optional scripts/templates/examples.
Think of it as a plugin playbook + resource bundle for AI assistants/toolchains.
Skills use progressive disclosure: load brief metadata first, load full docs only when needed, then execute by guidance.
This keeps agents lightweight while preserving enough context for complex tasks.
Use these three together:
Note: file size for all methods should be within 10MB.
Typical paths (may vary by local setup):
One SKILL.md can usually be reused across tools.
Yes. Most skills are standardized docs + assets, so they can be reused where format is supported.
Example: retrieval + writing + automation scripts as one workflow.
Some skills come from public GitHub repositories and some are uploaded by SkillWink creators. Always review code before installing and own your security decisions.
Most common reasons:
We try to avoid that. Use ranking + comments to surface better skills:
