LexGuard MCP (한국 법률 MCP 서버) 개발 가이드. 새로운 MCP 툴 추가, Repository/Service 작성, MCP JSON-RPC 엔드포인트 수정, 법령 API 연동, 테스트 작성 시 사용. 아키텍처 패턴, 국가법령정보센터 API 규칙, 응답 형식을 자동으로 준수.
Solve problems using knowledge base insights - extracts search terms, runs parallel KB queries, synthesizes advice grounded in your own frameworks
Record implementation pitfalls, debugging insights, and lessons learned into structured devlog documents. Triggers on completing any implementation task that encountered issues, after debugging sessions, after E2E testing, or when user says "record this", "document this pitfall", "add to devlog", "踩坑记录". MUST be invoked after any implementation phase that involved non-trivial bug fixes or workarounds.
Review and analyze devnet run results. Use when users want to (1) Analyze devnet logs for errors and warnings, (2) Generate a summary of a devnet run, (3) Identify interoperability issues between clients, (4) Understand consensus progress and block production, (5) Debug forks and finalization issues.
Comprehensive guide for developing Letta agents, including architecture selection, memory design, model selection, and tool configuration. Use when building or troubleshooting Letta agents.
HyperDbg Rust 驱动开发完整指南。包含 C++ 代码复刻、Rust 驱动开发、类型同步、编译验证等。在需要开发或维护 HyperDbg_rust 驱动时调用。
Generate synthetic training data variations using image transforms. Increases dataset diversity with flips, brightness jitter, and noise. Use after labeling.
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.
Use for DataLion workflows such as listing, reading, creating, or editing projects, inspecting data sources, importing Excel or CSV data, working with reports and report tabs and codebooks, reading chart tables, or coordinating dashboard and export work through a configured datalion MCP server and related API or UI paths.
Adapt designs to work across different screen sizes, devices, contexts, or platforms. Ensures consistent experience across varied environments.
Provides comprehensive guidance for Electron framework including main process, renderer process, IPC communication, window management, and desktop app development. Use when the user asks about Electron, needs to create desktop applications, implement Electron features, or build cross-platform desktop apps.
Manage Grid bots (spot/contract/coin-margined) and DCA Martingale bots (Spot DCA 现货马丁 / Contract DCA 合约马丁) on OKX. Covers create, stop, amend, monitor P&L, TP/SL, margin/investment adjustment, and AI-recommended parameters. Requires API credentials. Not for regular orders (okx-cex-trade), market data (okx-cex-market), or account info (okx-cex-portfolio).
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:
