MoAI — 100개 자기진화 도메인 하네스 AI 전문가. '/moai init'으로 개인화된 하네스를 설치하고, '/moai catalog'로 카탈로그를 조회하고, '/moai status'로 상태를 확인한다. '유튜브 영상 기획', '시장 조사', '계약서 검토', '사업계획서', '여행 계획', '뉴스레터 작성', '세무 상담', '채용 파이프라인', 'ESG 보고서', '데이터 분석' 등 100가지 도메인의 전문가 하네스를 제공한다. 자연어로 도메인 요청 시 자동 감지하여 해당 하네스 레퍼런스를 로딩한다. MoAI, 모아이, harness, 하네스, 전문가 모드, expert mode.
🇺🇸 Open Source Launch Marketing Playbook — Complete SOP from strategy to execution. GitHub star growth tactics, KOL partnership lists, Reddit marketing, community distribution across global channels. 🇨🇳 开源项目发布整合营销手册 — 从战略到执行的完整 SOP。GitHub Star 增长策略、KOL 合作清单、Reddit 运营、海外群组分发。 🇯🇵 オープンソースローンチマーケティングガイド — 戦略から実行までの完全SOP。GitHub Star成長戦略、KOLパートナーシップ、Redditマーケティング、グローバルコミュニティ配信。 🇰🇷 오픈소스 런칭 마케팅 플레이북 — 전략부터 실행까지 완벽한 SOP. GitHub 스타 성장 전략, KOL 파트너십, Reddit 마케팅, 글로벌 커뮤니티 배포.
法律文件脱敏/还原工具 - 将法律文档中的敏感信息进行智能替换和脱敏处理，或将脱敏稿还原为原文 <examples> - 帮我把这份合同脱敏处理 - 我需要脱敏这个法律文件 - 生成脱敏版本的合同文档 - 将这份法律文书中的敏感信息替换掉 - 创建合同的脱敏版本 - 帮我把脱敏稿还原成原文 - 使用比对词还原审核稿 </examples> --- # 法律文件脱敏处理 将法律文档中的敏感信息进行智能替换和脱敏处理，生成可对外分享的脱敏版本。支持将脱敏稿交由外部审核后，使用比对词还原为原文。 ## 核心功能 ### 脱敏功能 - **多种脱敏类型**：名称、日期、价格、文件名、项目名、银行账号、案号等 - **自定义脱敏类型**：创建自定义类型（如"合同名称"、"产品型号"），批量输入精准匹配内容 - **批量模式**：多文件上传自动进入批量模式，统一编号确保跨文件一致性 - **规则设置**：可自主开启/关闭16种内置脱敏类别，灵活控制识别范围 - **智能替换**：根据上下文识别角色（买方/卖方公司） - **实时预览**：黄色高亮显示脱敏内容 - **格式保留**：完整保留原文格式（段落、表格、字体） - **白名单/黑名单管理**：精确控制特定内容的脱敏行为；黑名单支持记录项目类型 - **优先级机制**：黑名单 > 白名单 > 脱敏类别（内置+自定义） - **冲突检测**：添加到列表时自动检测是否已存在于其他列表 - **调试模式**：详细日志输出，便于排查问题 ### 还原功能 - **自动化还原**：根据比对词自动将【X】标记还原为原文 - **批量还原**：支持多文件同时还原，自动匹配文件配对，ZIP打包下载 - **保留审核痕迹**：还原时保留文档中的修订、批注等审核痕迹 - **runs级别替换**：精确替换，不影响其他内容的格式 ## 使用方式 ### HTML离线工具（推荐） #### 脱敏模式 **单文件脱敏：** 1. 打开 `assets/index.html`，选择"脱敏模式" 2. 拖拽或选择单个 docx 文件上传 3. 自动识别并预览脱敏效果 4. 手动编辑脱敏项 5. 导出脱敏文件和比对.md文档 **批量脱敏：** 1. 上传多个 docx 文件，自动进入批量模式 2. 统一识别：相同内容使用相同替换文本 3. 文件切换：通过列表栏切换查看各文件 4. 同步编辑：删除/添加脱敏项会同步到所有文件 5. 导出结果：每个文件生成独立的 `{文件名}_比对.md` #### 还原模式 **单文件还原：** 1. 打开 `assets/index.html`，选择"还原模式" 2. 上传脱敏稿（带审核痕迹的docx） 3. 上传对应的比对.md文件 4. 点击"执行还原"，自动下载还原后的文件 **批量还原（4步流程）：** 1. **上传文件**：上传多个脱敏稿 + 多个比对.md文件 2. **确认配对**：系统自动匹配文件名，支持手动调整 3. **执行还原**：批量处理，显示进度条 4. **下载结果**：ZIP打包下载 ### Python脚本 ```bash # 安装依赖 pip install python-docx # 执行脱敏 python scripts/redact.py input.docx data/rules.json -o output.docx # 执行还原（保留修订、批注） python scripts/restore.py redacted.docx mapping.md -o restored.docx ``` ## 详细文档 - **工作流程**: [references/workflow.md](references/workflow.md) - **规则模式库**: [references/patterns.md](references/patterns.md) - **数据格式**: [references/data-formats.md](references/data-formats.md) - **脚本使用**: [scripts/README.md](scripts/README.md) - **HTML使用**: [assets/README.md](assets/README.md) ## 版本历史 - **v1.5.0（2026-03-29）右键菜单集成 + Python/HTML识别统一**： - **Windows 右键菜单**：右键 .docx 文件可直接"用脱敏工具打开"、"一键脱敏"或"一键还原"，通过注册表集成，无需管理员权限 - **macOS 右键菜单**：通过 Automator Quick Action 实现，Fi
Tests and scores any Agent Skill against the official anthropics/skills specification. Use this skill when you need to check if a skill repository or SKILL.md file is compliant with the Agent Skills standard, audit skill quality, get a compliance score, or receive specific improvement suggestions. Trigger when users say things like "check my skill", "test this skill", "does my skill follow the spec", "score my skill", "review my SKILL.md", "is my skill correct", "检查我的skill", "测试这个skill", "这个skill符合规范吗", "给我的skill打分", or when they provide a path to a skill directory or SKILL.md file and want it reviewed.
Advanced GitHub automation skill untuk OpenClaw — auto-sync, PR review, issue triage, release management, dan backup.
Create Claude Code agents (autonomous workers with isolated context and restricted tools). Use when the user wants to create an agent, autonomous worker, isolated task runner, or custom subagent. NOT for skills - agents have tool restrictions and run in isolation.
Fill out the implementation of effects of different attacks, abilities, and trainer cards in this Pokemon TCG Pocket engine codebase.
Draft, critique, or rewrite PRDs (product requirements / product specs) and adjacent artifacts (PR/FAQ, acceptance criteria, rollout plan). For AI/LLM features, also draft eval specs (LLM-as-judge) and prompt sets. Output must be in English. Use when the user asks for a PRD/spec/requirements/PRFAQ/evals/prompt sets, or needs help clarifying scope, success metrics, non-goals, user stories, or stakeholder alignment.
Write missing unit tests for a makeup-js module based on coverage gaps
从零构建机构级三表模型（IS/BS/CF）— 完整公式联动、季度/半年/年频自适应、IFRS/US GAAP/中国准则。 触发词：三表模型、financial model、3-statement、建模、从零建模、收入预测。 ❌ 填写已有模板请用 financial-analysis:3-statements --- # 3-Statement Model — IPO / Equity Research Quality (v4.8 · Public Edition) --- ## 🚀 Quick Start — New Users **This skill builds:** A complete institutional-grade 3-statement financial model (IS / BS / CF) in Excel, with full formula linkage, zero hardcoded forecast cells, and 9-step QC validation. **Prerequisites — install before starting:** ```bash pip install openpyxl yfinance pandas pip install notebooklm # optional — only needed if you have a NotebookLM notebook ``` **How to trigger:** Just say `"建个三表模型"` / `"build a 3-statement model for [Company]"` and the skill guides you step by step. **What to prepare:** - Company ticker (e.g. `BABA`, `0700.HK`, `600519.SS`) - A data source — see recommendations below - ~1–2 hours across 5 sessions (each session is independent — pause and resume anytime) **⚠️ Data Source Guide — Read Before Starting** | Option | Setup | Token Cost | Recommended? | |--------|-------|-----------|--------------| | **NotebookLM notebook** (annual reports / prospectus pre-loaded) | One-time OAuth auth setup | Very low — NLM handles the PDF; Claude only receives answers | ✅ Best path | | **Excel upload** (historical IS/BS/CF already structured) + short PDF excerpts | None | Low | ✅ Good | | **Direct PDF upload** (full annual report, prospectus) | None | 🔴 Very high — a single A-share annual report can be 200+ pages | ⚠️ Pro users: avoid | | **Web only** (Sina / Yahoo Finance fallback) | None | Low | ✅ Fallback | **Strongly recommended for new users: set up NotebookLM first.** The one-time auth flow takes ~5 minutes and saves significant token consumption for every future model: ```bash pip install notebooklm # Run once interactively — browser will open for Google OAuth python3 -c " import asyncio from notebooklm import NotebookLMClient async def auth(): async with await NotebookLMClient.
Scan a release on VirusTotal and generate false positive submission instructions for flagged AV vendors.
Merge reference implementation changes from the official Copilot SDK into this Java SDK.
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:
