Adversarial AI code/plan review. Codex reviews, Claude fixes, iterative loop until approved. Auto-detects plan/code/code-vs-plan mode.
Use when implementing any feature, adding code, or modifying existing code in this Kotlin/Spring project. Triggers on write operations like adding entities, services, facades, controllers, or any domain logic.
Analyzes code for bugs, security vulnerabilities, performance problems, and style issues. Use when reviewing a PR, reading a diff, auditing a file, or asked to check, critique, inspect, or audit code. Outputs a structured markdown report with severity ratings.
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
Use this skill for any request to create, update, review, or improve files that guide AI coding tools—like AGENTS.md, Copilot context files, or agent instructions. Trigger when users want to help AI generate code that matches project conventions, avoids common mistakes, or understands non-obvious rules—whether for a whole repo, a subdirectory, or a specific component. Also use for queries about setting up Copilot or Cursor context, onboarding AI to team practices, or keeping agent guidance up to date—even if AGENTS.md isn't mentioned by name. --- # AGENTS.md Skill `AGENTS.md` is the README for AI coding agents — it gives tools like GitHub Copilot, Cursor, and Claude Code the context they need to produce code that fits your project, without constant back-and-forth correction. ## The Golden Rule: Only Include Non-Obvious Things This is the most important principle. Before adding any line, ask: **"Could an agent figure this out by reading the code or config files?"** If yes — skip it. Agents can read `package.json`, `pyproject.toml`, `*.csproj`, directory structures, imports, and existing code. AGENTS.md is for the things that *aren't* visible there: - Project-specific conventions not enforced by any linter or analyzer - "Never do X" patterns that *look* reasonable but are wrong in this codebase - Commands that are non-standard or require project-specific flags - Domain terminology or architectural choices that need explanation - Common mistakes agents actually make here (discovered from experience) - Security constraints and rules that must never be violated **Redundant content actively degrades quality** — it wastes the agent's context window and dilutes real signal with noise it already has. ## Two Shapes of AGENTS.md ### Root-level `AGENTS.md` (repo root)
Run a code quality review on changed files after code modifications. Triggers when application logic, architecture, data flow, or reusable components are affected.
Local-first code graph builder with 5-signal hybrid search. Use when analyzing codebases, searching for code architecture, exploring dependencies, or building code graphs from source code and documents.
Codebase health scanner and technical debt tracker. Use when the user asks about code quality, technical debt, dead code, large files, god classes, duplicate functions, code smells, naming issues, import cycles, or coupling problems. Also use when asked for a health score, what to fix next, or to create a cleanup plan. Supports 28 languages.
MoonBit code generation best practices. Use when writing MoonBit code to avoid common AI mistakes with syntax, tests, and benchmarks.
or non-idiomatic Go code in their project. Also when asked "how good is this code?" or "audit my code."
Generate synthetic code context for LLM coding tasks. Automatically use this before making code changes, fixing bugs, refactoring, or answering questions about the codebase. Provides execution paths, relevant files, symbols, tests, and code snippets.
Codebase analyzer for JavaScript/TypeScript projects. Finds unused code (files, exports, types, dependencies), code duplication, circular dependencies, complexity hotspots, architecture boundary violations, and feature flag patterns. 85 framework plugins, zero configuration, sub-second performance. Use when asked to analyze code health, find unused code, detect duplicates, check circular dependencies, audit complexity, check architecture boundaries, detect feature flags, clean up the codebase, auto-fix issues, or run fallow.
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:
