REST 및 GraphQL API 설계 원칙 가이드. 새로운 API 설계, API 스펙 리뷰, API 설계 표준 수립 시 활용. 트리거: "API 설계", "REST", "GraphQL", "엔드포인트 설계", "API versioning", "API 패턴" 안티-트리거: "프론트엔드 UI", "데이터베이스 스키마만", "CSS/스타일링", "배포/인프라"
Build and package Claude Inspector as a distributable Electron app (.dmg / .exe)
(project) Use when editing any file under plugins/hal-voice/ to bump the plugin version before committing
GitHub repository access in containerized environments using REST API and credential detection. Use when git clone fails, or when accessing private repos/writing files via API.
Apply frontend UI aesthetics judgment for web interface generation, review, and refactor tasks. Use when working on hierarchy, composition, responsiveness, accessibility, or visual polish in frontend code.
Use when working in a Ruby project - provides authoritative sources for documentation, typing, and tooling
Build, refactor, and review apps with Jetpack Compose and Compose Multiplatform (KMP/CMP) using MVI architecture. Covers coroutines, StateFlow, SharedFlow, Channel, ViewModels, state modeling, recomposition, Navigation 3/2, Koin/Hilt DI, Ktor networking, Paging 3, Room, DataStore, animations, Coil, accessibility, multiplatform resources, iOS/Swift interop, Gradle/AGP configuration, CI/CD, and desktop distribution. Use when working with @Composable, ViewModel, StateFlow, Flow, KMP, Ktor, Koin, Hilt, DataStore, Room, PagingData, recomposition, Xcode/iOS interop, Gradle build config, performance, testing, cross-platform, or code review. --- # Jetpack Compose & Compose Multiplatform This skill covers the full Compose app development lifecycle — from architecture and state management through UI, networking, persistence, performance, accessibility, cross-platform sharing, build configuration, and distribution. Jetpack Compose and Compose Multiplatform share the same core APIs and mental model. **Not all Jetpack libraries work in `commonMain`** — many remain Android-only. A subset of AndroidX libraries now publish multiplatform artifacts (e.g., `lifecycle-viewmodel`, `lifecycle-runtime-compose`, `datastore-preferences`), but availability and API surface vary by version. **Before adding any Jetpack/AndroidX dependency to `commonMain`, verify the artifact is published for all required targets by checking Maven Central or the library's official documentation.** CMP uses `expect/actual` or interfaces for platform-specific code. MVI (Model-View-Intent) is the recommended architecture, but the skill adapts to existing project conventions. ## Existing Project Policy **Do not force migration.** If a project already follows MVI with its own conventions (different base class, different naming, different file layout), respect that. Adapt to the project's existing patterns. The architecture pattern — unidirectional data flow with Event, State, and Effect — is what matters, not a speci
Add an `Assisted-by: <agent-name>/<model-id>` git trailer to commits made during an AI-assisted coding session. Trigger on any `git commit` activity visible in the session — either commits you make yourself, or commits the user makes outside your tool calls that surface in the conversation — even without an explicit request. Also trigger when the user explicitly asks to tag existing commits in a branch (e.g. "add assisted-by to commits in this branch").
Règle 05 : Aggregates et Aggregate Roots. Use when implementing DDD patterns.
Capability contract (COMPLETE/BOOTSTRAP) for ClawMobile Android runtime.
Adversarial research analysis framework that uses structured Bull/Bear/Arbiter debates to help users make better research judgments. Maintains a belief graph as backend engine, applies statistical calibration discipline, tracks phase transitions, and detects biases.
Use when the user wants cross-disciplinary research ideas generated as concise research cards with Title, Abstract, Design, Distinctiveness, and Significance rather than one-shot prompting.
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:
