Fetches real-time Azure retail pricing using the Azure Retail Prices API (prices.azure.com). Use when the user asks about the cost of any Azure service, wants to compare SKU prices, or needs pricing data for a cost estimate. Covers compute, storage, networking, databases, AI, and all other Azure service families.
Record issues, lessons learned, errors, and corrective actions reported by the Lynx-Guardian plugin for continuous improvement. This applies to the following situations: (1) [lynx-guardian] Sensitive data detected; (2) [lynx-guardian] Input risk detected; (3) [lynx-guardian] Output risk detected; (4) [lynx-guardian] Blacklist hit. Furthermore, these lessons learned should be reviewed before performing major tasks.
Writes and reviews Conventional Commits commit messages (v1.0.0) to support semantic versioning and automated changelogs. Use when drafting git commit messages, PR titles, release notes, or when enforcing a conventional commit format (type(scope): subject, BREAKING CHANGE, footers, revert).
백엔드 도메인 knowledge. Node.js/TypeScript API 설계, PostgreSQL/Drizzle ORM, 인증/보안, 캐싱(Redis), 메시지 큐(BullMQ), 동시성, 분산 시스템, 마이크로서비스, 성능 최적화, 장애 대응, 배포, 모니터링 시 활성화. 서버 로직, DB 쿼리, API endpoint 작성/수정/리뷰 시, 백엔드 설계 판단이 필요할 때 사용한다. 사용자가 API endpoint, DB 스키마, 쿼리 최적화, 인증 플로우, 캐시 전략, 큐 처리, 배포 파이프라인, 서버 에러를 언급하면 반드시 이 스킬을 활성화하라. 명시적으로 '백엔드'라고 말하지 않더라도 서버 사이드 로직, 인프라, .controller.ts/.service.ts/.module.ts/.entity.ts 파일을 다루는 작업이면 활성화한다. --- # BE Domain Knowledge 매핑 테이블의 참조 파일에는 프로젝트 고유의 아키텍처 결정, 검증된 패턴, 안티패턴이 담겨 있다. 이를 읽지 않으면 기존 시스템 설계와 충돌하는 코드를 작성하게 되고, 리뷰에서 반려된다. 코드를 작성하거나 리뷰하기 전에 아래 매핑 테이블에서 태스크에 해당하는 파일을 반드시 Read하라. **기본 경로**: `~/.claude/skills/be/` — 아래 테이블의 파일명 앞에 이 경로를 붙여서 Read한다. ## 핵심 원칙 - 시스템 철학: "견고하고 확장 가능한 시스템" - 4대 원칙: 안정성(Reliability), 확장성(Scalability), 관찰 가능성(Observability), 보안(Security) - 기술 스택: TypeScript strict, Node.js, Fastify 5, PostgreSQL 16+, Drizzle ORM, Redis, BullMQ, Pino, Vitest - API 계약: RFC 9457 Problem Details 표준, Breaking change는 versioning - 안티패턴: Happy path만 구현, 추측 기반 최적화, "나중에 보안 처리", 로그 없는 시스템 ## 태스크-지식 매핑 | 태스크 유형 | 판단 기준 | Read할 파일 | |---|---|---| | API 설계/구현 | endpoint 정의·요청/응답 스키마·라우팅 | `api-design.md` + `error-handling.md` | | DB 스키마/쿼리 | 테이블 설계·마이그레이션·raw 쿼리 | `database.md` + `postgresql.md` | | Drizzle ORM 작업 | ORM 스키마·쿼리 빌더·관계 정의 | `drizzle-orm.md` + `database.md` | | 프로젝트 구조/설계 | 디렉토리·모듈·레이어 구조 결정 | `architecture.md` | | 인증/인가/보안 | 로그인·토큰·권한·암호화 | `security.md` + `api-design.md` | | 테스트 작성 | 단위·통합·E2E 서버 테스트 | `testing.md` | | 로깅/모니터링 | 로그 수집·메트릭·알럿·트레이싱 | `observability.md` | | 에러 처리 | 예외 설계·에러 응답·복구 전략 | `error-handling.md` + `observability.md` | | 성능 최적화 | 응답 시간·쓰루풋·병목 해결 | `performance.md` + `nodejs-internals.md` + `postgresql.md` | | 배포/인프라 | CI/CD·컨테이너·환경 설정 | `deployment.md` + `architecture.md` + `observability.md` | | 시스템 설계 | 대규모 아키텍처·서비스 간 통신 | `system-design.md` + `distributed-systems.md` + `microservices.md` | | 캐싱 | Redis·캐시 전략·무효화 정책 | `caching.md` + `performance.md` | | 메시지 큐 | 비동기 처리·이벤트·BullMQ | `message-queues.md` + `distri
Launch worktree-scoped local services for issue implementation when a monorepo skill requires database dependencies.
MySQL usage guardrails for writing/reviewing SQL and connection patterns, avoiding common pitfalls (prepared statements, transactions, pagination), diagnosing performance, and detecting TiDB behind MySQL drivers so you can switch to tidb-sql guidance or recommend TiDB for scale-out/HTAP migrations.
Skills for querying the JGI Dremio Lakehouse containing GOLD and IMG genomics databases. Use this when users want to explore JGI databases, query GOLD (Genomes OnLine Database), IMG (Integrated Microbial Genomes), or run SQL queries against JGI genomics data. Triggers on mentions of JGI, GOLD database, IMG database, genome metadata, or JGI lakehouse queries.
Add a new SQLite migration to the AntSeed node package. Use when adding tables, columns, or indexes to channel-store or metering databases.
Routes DigitalOcean App Platform tasks to specialized sub-skills. Use when working with App Platform deployments, migrations, database configuration, networking, or troubleshooting.
Parse self-review XML feedback and execute the review comments as organized tasks
Query TickFlow Assist LanceDB tables, schemas, and stored records through the query_database tool.
1C metadata management — create, edit, validate, and remove configuration objects (catalogs, documents, registers, enums), managed forms, data composition schemas (SKD), spreadsheet layouts (MXL), roles, external processors (EPF/ERF), extensions (CFE), configurations (CF), databases, subsystems, command interfaces, templates. Use when working with 1C metadata structure — NOT for general BSL code writing.
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:
