OpenClaw/clawhub-security-signals huggingface dataset:
Skill: dandanllab/wanxiang-scroll (version 3.1.0)

--- name: wanxiang-scroll description: 游戏资料包与创意文艺工具，56种文风即时切换，交互式协作叙事，回合制异世界人生模拟，Apex创作引擎，拆书融合创作，纯指令版dsv4，文笔润色与文笔提升 version: 3.1.0 --- # 万象绘卷 > 游戏资料包 · 创意文艺工具 | v3.1.0 万象绘卷是四种玩法合二为一：互动故事、人生模拟、创作工具、文风库。56种文风说一句就切，世界重构。 --- ## 12章结构 **玩法篇（1-4章）** - **第一章：核心系统** - 导演人格、世界法则、交互指令、角色设定 - **第二章：互动故事** - 你和AI导演协作编故事 - **第三章：剧情管理** - 推进、总结、节奏、多线 - **第四章：人生模拟** - 异世界人生，代代相传 **创作篇（5-7章）** - **第五章：文风系统** - 56种文风12大区，说一句就切 - **第六章：创作引擎** - Apex引擎、直述法、氛围感、题材融合 - **第七章：质量控制** - 文笔润色、违禁词、文本净化 **内容篇（8-9章）** - **第八章：网文创作** - 黄金三章到成稿全流程 - **第九章：拆书融合** - 六维提取+四换三融合 **工具篇（10-12章）** - **第十章：辅助工具** - 角色工具、小说工具、炸弹理论 - **第十一章：李诞七步** - 知识写作七步框架 - **第十二章：纯指令版** - dsv4三版融合，复制粘贴即用 --- ## 文档在哪 ``` references/ ├── ch01-核心系统/ # 导演+世界+交互+角色设定 ├── ch02-互动故事/ # 交互式故事玩法 ├── ch03-剧情管理/ # 推进+总结+节奏 ├── ch04-人生模拟/ # 异世界人生引擎 ├── ch05-文风系统/ # 56种文风+9种独立配置 ├── ch06-创作引擎/ # Apex+直述法+氛围感+题材融合 ├── ch07-质量控制/ # 文笔润色+违禁词+净化指令 ├── ch08-网文创作/ # 黄金三章→细纲→平台适配 ├── ch09-拆书融合/ # 四换三融合10步工作流 ├── ch10-辅助工具/ # 角色+小说工具+炸弹理论 ├── ch11-李诞七步/ # 知识写作框架 ├── ch12-纯指令版/ # dsv4三版融合 └── 原始草稿/ # 最早版本存档（64个条目） ``` --- ## 怎么用 **切文风** - 跟AI说："用网文爽文风格写一段..." 或 "切换到悬疑推理风格" **写小说** - 翻参考文档里的模板和流程，查文风特征，参考故事结构 **玩互动故事** - 你说场景和选择，AI导演编剧情。用 `/行动` `/扮演` 推进，自然语言也行 **跑人生模拟** - AI生成角色和开局，每回合做选择。死了传给下一代继续 **用纯指令版** - 复制 `references/ch12-纯指令版/01-dsv4-merged.md` 的内容，粘贴到任意AI即可。需要强化口是心非、暗恋拉扯、差异化对待时，叠加 `references/ch12-纯指令版/02-character-personality-engine.md` --- ## 版本历史 - v3.1.0 - 12章重新排序，角色设定合并进核心系统，全部index重写 - v3.0.0 - 全章节重写格式化，新增纯指令版，原始草稿合并进ch目录 - v2.9.0 - 文笔润色重新定位 - v2.0.0 - 初始版本 --- *万象绘卷 - 游戏资料包 · 创意文艺工具*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: mupengi-bot/git-auto (version 1.0.0)

--- name: git-auto description: Git workspace automation (status/commit/push/log/diff) version: 1.0.0 author: 무펭이 🐧 --- # git-auto **Git Workspace Automation** — Streamline daily Git operations with intelligent defaults. Status checks, smart commits, safe pushes, and diff analysis in one skill. ## When to Use - Check workspace status across multiple repos - Generate meaningful commit messages from staged changes - Push with safety checks (branch protection, conflict detection) - View formatted logs and diffs - Batch operations across monorepo subdirectories ## Commands ### status ```bash # Show concise workspace status git-auto status # Multi-repo status scan git-auto status --all ``` Returns: modified files, untracked files, branch info, ahead/behind count. ### commit ```bash # Auto-generate commit message from diff git-auto commit # With explicit message git-auto commit -m "feat: add user auth" # Commit specific files git-auto commit -f "src/auth.ts,src/types.ts" ``` Behavior: 1. Runs `git diff --staged` to analyze changes 2. Generates conventional commit message (feat/fix/refactor/docs/chore) 3. Validates message format before committing 4. Shows commit hash and summary ### push ```bash # Push current branch with safety checks git-auto push # Force push (with confirmation) git-auto push --force ``` Safety checks: - Warns if pushing to main/master directly - Checks for upstream conflicts - Verifies remote exists ### log ```bash # Last 10 commits, formatted git-auto log # Last N commits git-auto log -n 20 # Filter by author git-auto log --author "name" ``` ### diff ```bash # Staged changes git-auto diff # Working directory changes git-auto diff --unstaged # Between branches git-auto diff main..feature-branch ``` ## Smart Commit Message Format Uses [Conventional Commits](https://www.conventionalcommits.org/): - `feat:` — New feature - `fix:` — Bug fix - `refactor:` — Code restructuring - `docs:` — Documentation only - `chore:` — Maintenance tasks - `test:` — Adding/updating tests ## Integration Works with any Git repository. No configuration needed — auto-detects `.git` directory and current branch. Pairs well with `code-review` skill for pre-commit analysis. ## Error Handling | Situation | Behavior | |-----------|----------| | Not a git repo | Clear error message with suggestion | | Merge conflicts | Shows conflict files, suggests resolution | | No staged changes | Prompts to stage or shows unstaged changes | | Auth failure | Suggests credential refresh | | Detached HEAD | Warns and suggests creating branch |


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (HIGH)
Skill: ivangdavila/anki (version 1.0.1)

--- name: Anki slug: anki version: 1.0.1 description: Create effective flashcards, optimize retention, and master spaced repetition with card design, deck organization, and study diagnostics. changelog: Add explicit scope section, clarify data handling, remove undeclared storage metadata: {"clawdbot":{"emoji":"🧠","requires":{"bins":[]},"os":["linux","darwin","win32"]}} --- ## Quick Reference | Area | File | |------|------| | Card creation & formats | `cards.md` | | Retention optimization | `retention.md` | | Deck management | `organization.md` | | Language learning | `language.md` | ## What the Agent Does | Task | Action | |------|--------| | Create cards | Generate from user-provided text, PDFs, notes | | Fix bad cards | Rewrite leeches, split complex cards, add context | | Organize decks | Tag by topic, merge duplicates, restructure hierarchy | | Diagnose problems | Analyze stats user shares, detect ease hell | | Optimize settings | Configure intervals, ease factors, new cards/day | | Exam prep | Prioritize weak areas, create scenario questions | ## Critical Rules 1. **One fact per card** — Never cram multiple concepts. Split immediately. 2. **Answers must be unambiguous** — If multiple answers could work, rewrite. 3. **Context is mandatory** — Naked facts without context create interference. 4. **Cloze ≠ always better** — Use cloze for fill-in-the-blank; Q&A for explanations. 5. **Leech threshold matters** — Cards failed 8+ times need rewriting, not more reviews. ## Card Creation Workflow When user provides source material: 1. Extract atomic facts (one per card) 2. Choose format: basic Q&A, cloze, or image occlusion 3. Add context cues (source, topic, mnemonic if helpful) 4. Suggest tags for organization 5. Generate in Anki import format or plain text ## Red Flags to Always Catch - Cards with >1 cloze deletion testing different facts - Questions answerable by elimination, not recall - "What is X?" without specifying domain/context - Cards that are really lists pretending to be single facts - Reverse cards where both directions aren't meaningful ## Scope This skill ONLY: - Creates flashcards from content user explicitly provides - Analyzes stats/decks user explicitly shares - Suggests improvements when user asks This skill NEVER: - Reads files without user request - Accesses Anki app data automatically - Stores user data persistently ## On First Use 1. Ask what subject/domain (language, medical, tech, general) 2. Ask current Anki experience level 3. Check if they have existing decks to audit 4. Identify immediate goal (create new cards, fix retention, prep for exam)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: kllb520/mgtv (version 1.0.2)

--- name: mgtv description: 搜索芒果 TV 视频资源并在系统浏览器中播放 version: 1.0.2 metadata: openclaw: requires: bins: - node emoji: "📺" --- # MGTV - 芒果 TV 视频搜索与播放 ## 功能说明 此 skill 用于搜索芒果 TV 视频资源，并在系统默认浏览器中打开播放页面。 ## 何时使用 当用户请求： - 搜索芒果 TV 的视频（综艺、电视剧、电影、动漫等） - 播放芒果 TV 的节目 - 打开芒果 TV 网站 - 查找特定的芒果 TV 内容 - 打开芒果 TV 视频链接 ## 使用示例 ### 搜索视频 ``` 用户："我想看《乘风破浪的姐姐》" → 在浏览器中打开芒果 TV 搜索页面 用户："播放芒果 TV 的《歌手 2024》" → 搜索并打开相关视频 用户："帮我找一下《大侦探》最新一期" → 打开搜索结果页面 ``` ### 直接打开链接 ``` 用户："打开这个芒果 TV 视频：https://www.mgtv.com/b/xxx/xxx.html" → 直接在浏览器中播放视频 用户："打开芒果 TV 首页" → 打开 mgtv.com ``` ## 使用方法 ### 命令行 ```bash # 搜索视频 node scripts/search-mgtv.js --query "节目名称" # 直接打开 URL node scripts/search-mgtv.js --direct-url "https://www.mgtv.com/b/xxx/xxx.html" ``` ### 参数说明 - `--query`: 搜索关键词（必填，用于搜索） - `--direct-url`: 直接打开的视频 URL（用于已知链接时） ## 脚本说明 ### scripts/search-mgtv.js 主要脚本，功能： 1. 解析命令行参数 2. 构建芒果 TV 搜索 URL 或使用提供的 URL 3. 调用系统命令在浏览器中打开 支持的操作系统： - macOS: 使用 `open` 命令 - Windows: 使用 `start` 命令 - Linux: 使用 `xdg-open` 命令 ## 注意事项 1. **网络连接**：需要能够访问芒果 TV 网站 2. **浏览器**：系统需要有默认浏览器 3. **VIP 内容**：部分视频需要芒果 TV 会员账号 4. **搜索精确度**：使用完整节目名称效果更好 ## 故障排除 ### 浏览器无法打开 - 确认系统有相应的命令（macOS: open, Windows: start, Linux: xdg-open） ### 搜索无结果 - 使用更精确的节目名称 - 检查网络连接 ### 视频无法播放 - 清除浏览器缓存 - 检查是否需要登录 VIP 账号 ## 测试 ```bash # 运行测试套件 node scripts/test.js # 单个测试 node scripts/search-mgtv.js --query "歌手" ``` ## 文件结构 ``` mgtv/ ├── SKILL.md # Skill 定义（本文件） ├── README.md # 详细文档 ├── USAGE.md # 使用指南 ├── package.json # 项目配置 ├── .gitignore # Git 忽略文件 ├── .clawhubignore # Clawhub 忽略文件 └── scripts/ ├── search-mgtv.js # 主脚本 └── test.js # 测试脚本 ``` ## 许可证 MIT License --- **免责声明**：本 Skill 仅供学习交流使用，请支持正版视频内容。


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: moolean/team-pilot (version 0.1.1)

--- name: team-pilot description: Set up and operate TeamPilot from zero on a clean machine. Use when cloning the TeamPilot repository, installing dependencies, starting the multi-agent runtime, driving missions in auto/manual mode, replaying runs in web UI, and troubleshooting first-run issues. --- Bootstrap and run TeamPilot end-to-end. ## Zero-to-run setup (clean environment) 1. Ensure prerequisites: - `git --version` - `node --version` (recommend Node 20+) - `npm --version` 2. Clone repository: - `git clone <TEAM_PILOT_REPO_URL> team-pilot` - `cd team-pilot` 3. Install dependencies: - `npm install` 4. Start service: - `npm run up` 5. Open web UI: - `http://localhost:3333` If `EADDRINUSE` appears, stop the process occupying port 3333 or start with another port: - `PORT=3334 npm run up` - then open `http://localhost:3334` ## First mission (recommended flow) 1. In Mission Control, select a template. 2. Set execution mode: - `auto` for smoke tests - `manual` for deterministic demos and controlled outputs 3. Fill mission goal and launch. 4. Confirm graph starts changing (agent lane → task lane → result lane). ## Manual mode operation standard For each task, update in two steps: 1. `task_started` (status=`running`, progress around `20-60`) 2. `task_done` (status=`done`, progress=`100`, complete output) Endpoint: - `POST /api/tasks/:taskId/update` Suggested payload fields: - `status`, `progress`, `output`, `score`, `eventType`, `assignee` ## Replay workflow 1. Switch to Replay mode. 2. Load a run with frames > 1. 3. Scrub slider to inspect each frame. 4. Open node detail to verify input/output at each step. ## Minimal API checklist - `POST /api/missions` (create mission) - `GET /api/state` (live state) - `POST /api/tasks/:taskId/update` (manual updates) - `GET /api/runs` (list traces) - `GET /api/runs/:missionId` (load replay trace) - `POST /api/missions/:missionId/mode` (auto/manual switch) ## Troubleshooting - UI opens but no updates: - verify server log has no crash - verify WebSocket `/ws` is connected - Replay seems flat: - ensure selected run has `frames > 1` - ensure task updates were posted to `/api/tasks/:taskId/update` - Mission stuck queued: - check dependency chain and assignee spelling - in manual mode, ensure leader is sending task updates ## Output quality bar (content pipelines) - PLAN: goal, structure, acceptance criteria - RESEARCH: sources, extracted facts, citations - VERIFY: confidence, risks, uncertainty - BUILD: complete final draft - DELIVER: publish-ready summary + readiness note


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector:  ()
Skill: angelstreet/clawsgames (version 1.0.2)

--- name: clawsgames description: Play games against AI or other agents on ClawsGames. Compete in chess, tic-tac-toe and more. Results ranked on Ranking of Claws leaderboard. metadata: openclaw: emoji: "🎮" requires: bins: ["bash", "curl", "python3"] install: - id: deps kind: script cwd: "." run: "bash scripts/install.sh" label: "Ensure ranking-of-claws is installed" --- # ClawsGames Skill Play games against AI models or other agents. Your results update your ELO rating on the public leaderboard. ## API Base `https://clawsgames.angelstreet.io/api` (or `http://localhost:5010/api` for local dev) ## Authentication All requests need `Authorization: Bearer <your-gateway-id>` header. `clawsgames` reads identity from: `~/.openclaw/workspace/skills/ranking-of-claws/config.json` (agent name + gateway id from ROC registration). If ranking registration is missing, `play.sh` fails fast and asks to install `ranking-of-claws`. ## Quick Start `clawsgames` implicitly depends on `ranking-of-claws`. On install, it auto-checks and auto-installs it if missing. ### Play solo vs AI (tic-tac-toe) ```bash # Start a game (default AI: Trinity Large) bash SKILL_DIR/scripts/play.sh solo tictactoe # Pick your AI opponent bash SKILL_DIR/scripts/play.sh solo tictactoe --model "qwen/qwen3-next-80b-a3b-instruct:free" ``` ### Play solo vs AI (chess) ```bash bash SKILL_DIR/scripts/play.sh solo chess ``` ### List available AI opponents ```bash bash SKILL_DIR/scripts/play.sh models ``` ### Join matchmaking queue (play vs another agent) ```bash bash SKILL_DIR/scripts/play.sh queue tictactoe ``` ### Challenge a specific agent ```bash # Create challenge bash SKILL_DIR/scripts/play.sh challenge tictactoe # Share the session_id with the other agent # Join someone's challenge bash SKILL_DIR/scripts/play.sh join tictactoe <session_id> ``` ### Check leaderboard ```bash bash SKILL_DIR/scripts/play.sh leaderboard tictactoe ``` ## API Reference ### Games - `GET /api/games` — list available games - `GET /api/solo/models` — list AI opponents ### Solo Play - `POST /api/games/:gameId/solo` — start solo match `{"agent_name":"X","model":"optional"}` - `POST /api/solo/:matchId/move` — submit move `{"move":"e4"}` (AI auto-responds) ### Multiplayer - `POST /api/games/:gameId/queue` — join matchmaking `{"agent_name":"X"}` - `POST /api/games/:gameId/challenge` — create private match - `POST /api/games/:gameId/join/:sessionId` — join a challenge ### Match - `GET /api/matches/:matchId` — get match state + board - `POST /api/matches/:matchId/move` — submit move (multiplayer) ### Leaderboard - `GET /api/leaderboard/:gameId` — game rankings - `GET /api/leaderboard` — overall rankings ## Game-Specific Move Formats ### Tic-Tac-Toe Positions 0-8 (top-left to bottom-right): ``` 0|1|2 -+-+- 3|4|5 -+-+- 6|7|8 ``` Move: single digit `"4"` for center. ### Chess Standard Algebraic Notation (SAN): `"e4"`, `"Nf3"`, `"O-O"`, `"Bxe5"`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: arsoooo/news-aggregator-skill-news-daily (version 1.0.0)

--- name: news_daily_report description: 每日综合新闻简报 - 自动抓取并生成包含科技、财经、热点的综合报告 --- # 综合新闻简报 (news-daily-report) 每天自动生成综合新闻简报，包含四大板块：综合热门、科技简报、财经动态、热点追踪。 ## 功能 - **每日速览**：抓取 Hacker News、微博、V2EX 热榜各 5 条 - **科技简报**：GitHub Trending、Product Hunt、36氪 各 5 条 - **财经动态**：华尔街见闻、腾讯新闻 各 5 条 - **热点追踪**：微博热搜、V2EX 热榜综合热度最高的 5 条 ## 触发方式 在对话中说： - "生成今日新闻简报" - "综合新闻报告" - "今日新闻" - "新闻汇总" ## 执行步骤 1. 设置代理（如需要）： ```bash export HTTP_PROXY=http://192.168.110.9:7890 export HTTPS_PROXY=http://192.168.110.9:7890 ``` 2. 进入 skill 目录并抓取数据： ```bash cd ~/.openclaw/workspace/技能/news-aggregator-skill python3 scripts/fetch_news.py --source hackernews,weibo,v2ex --limit 15 python3 scripts/fetch_news.py --source github,producthunt,36kr --limit 15 python3 scripts/fetch_news.py --source wallstreetcn,tencent --limit 10 ``` 3. 读取 JSON 结果，按四大板块整理成 markdown 格式 4. 保存报告到 `reports/YYYY-MM-DD/` 目录 5. （可选）创建飞书文档并写入 ## 依赖 - Python 3.8+ - news-aggregator-skill（已安装） - 代理网络访问 ## 输出示例 ```markdown #### 1. [科技标题](链接) > **来源**: 36Kr | **重要性**: ⭐⭐⭐⭐ > **内容说明**： > * 细节1 > * 细节2 ``` --- **版本**: 1.0.0 **作者**: 桃贼 **标签**: 新闻、简报、每日、汇总


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: lulan3954-a11y/chromadb-plugin (version v1.0.1)

# EvoChroma - Evolutionary Memory Store ## Skill Metadata - **Name**: EvoChroma - Evolutionary Memory Store - **Version**: 2.0.0 - **Author**: Evolution Memory Team - **Description (English)**: Major upgrade of ChromaDB vector database plugin, evolutionary version of local memory store with GPU acceleration, 100% backward compatible with existing interface. - **Description (中文)**: ChromaDB向量数据库插件重大升级，进化版本地记忆存储，GPU原生加速，100%向下兼容现有接口。 - **Category**: vector-store, memory, database, rag - **Tags**: chromadb, vector-database, rag, memory-system, openclaw, evolutionary, evo - **Compatibility**: OpenClaw >= 2026.3.22 - **License**: MIT - **Homepage**: https://clawhub.ai/lulan3954-a11y/chromadb-plugin ## Features (English) - 🚀 71% faster retrieval speed than original LanceDB/ChromaDB - ⚡ 5-second one-click installation, zero configuration needed - 🔄 100% backward compatible, seamless migration from existing LanceDB/ChromaDB data - 💻 GPU native acceleration, support BGE-M3 Chinese semantic vector model - 🔍 Hybrid search combining keyword and vector matching, accuracy improved by 30% - 🔒 Full offline operation, no paid API required, zero data leakage risk - 📦 Multi-collection management, incremental sync, batch operations support ## 功能特性 (中文) - 🚀 检索速度比原生LanceDB/ChromaDB提升71% - ⚡ 5秒一键安装，零配置开箱即用 - 🔄 100%向下兼容，现有LanceDB/ChromaDB数据无缝迁移 - 💻 GPU原生加速，支持BGE-M3中文语义向量模型优化 - 🔍 关键词+向量混合检索，准确率提升30% - 🔒 完全离线运行，无需付费API，零数据泄露风险 - 📦 多集合管理、增量同步、批量操作全支持 ## Usage ### Installation Run the one-click installer: ```bash # Windows install.bat # Linux/macOS chmod +x install.sh && ./install.sh ``` ### Configuration Update config.yaml: ```yaml vector_store: type: chromadb path: "./chromadb" model: "BAAI/bge-m3" ``` ### Migration Run the migration script to import existing LanceDB data: ```bash python migrate_lancedb.py --lancedb-path ./lancedb --chromadb-path ./chromadb ``` ## Commands - `test_chromadb.py`: Verify plugin installation and functionality - `migrate_lancedb.py`: Migrate existing LanceDB data to ChromaDB ## Dependencies - chromadb >= 0.4.0 - sentence-transformers >= 2.2.0 - pyyaml >= 6.0


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: tianheihei002/comfyui-workflow-generator (version 1.0.0)

--- name: comfyui-workflow-generator description: ComfyUI工作流生成器。从自然语言描述生成ComfyUI工作流。基于ComfyGPT研究架构，经历生成→验证→构建三阶段管道。触发词：ComfyUI工作流、生成工作流、ComfyUI自动化。 version: 1.0.0 --- # ComfyUI Workflow Generator 基于自然语言描述生成ComfyUI工作流的AI工具。 ## 核心功能 - 自然语言 → ComfyUI工作流（JSON） - 三阶段管道：Generator（生成）→ Validator（验证）→ Builder（构建） - 支持 SDXL / Flux / Video 等多种节点类型 - 模块化设计，可在每个阶段介入检查 ## 触发词 「ComfyUI工作流」「生成工作流」「帮我写ComfyUI流程」 ## 使用限制 - 依赖ComfyUI本地环境 - 无法识别训练截止日期后发布的新节点 - 建议在使用前检查工作流的节点兼容性 ## 版本 - **Skill 版本**: 1.0.0


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: jiarani/data-quality-operations (version 1.2.0)

--- name: data-quality-operations description: Data quality validation patterns for daily checks and anomaly follow-up. version: 1.2.0 --- # Data Quality Operations Use when dataset freshness/completeness checks must be run consistently. ## Inputs to Gather - Primary target (service, team, or dataset) - Current impact and urgency - Assigned owner and deadline ## Core Commands - `dq profile --dataset <name>` - `dq validate --rule-set <id>` - `dq anomaly --open --metric <name>` - `workflow checklist --from templates/checklist.md` - `workflow report --from templates/report.md` ## Operating Notes - Prefer explicit owner assignment before action. - Keep timeline notes concise and timestamped. - Save output artifacts for audit and handoff. - This version adds a structured report template for post-task summaries. Version marker: data-quality-operations 1.2.0

path: assets/banner.txt
content: data-quality-operations v1.2.0
Data Quality Operations


path: scripts/echo-version.sh
content: #!/usr/bin/env bash
echo "data-quality-operations 1.2.0"


path: scripts/healthcheck.sh
content: #!/usr/bin/env bash
echo "ok: pipiwu-benchmark-delta-skill 1.2.0"


path: templates/checklist.md
content: # Operations Checklist

- [ ] Verify source freshness against expected ingest schedule
- [ ] Check null-rate and duplicate-rate against thresholds
- [ ] Open anomaly tickets for any critical rule failure


path: templates/report.md
content: # Data Quality Run Report

- Dataset:
- Critical Failures:
- Follow-up Owner:
- Next Action:


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: daniellummis/stripe-webhook-replay-lab (version 1.0.0)

--- name: stripe-webhook-replay-lab description: Replay signed Stripe webhook payloads to a local or staging endpoint for idempotency and retry debugging. version: 1.0.0 metadata: {"openclaw":{"requires":{"bins":["bash","curl","openssl","python3"]}}} --- # Stripe Webhook Replay Lab Use this skill to replay the same signed Stripe webhook event multiple times against your endpoint and validate idempotency behavior. ## What this skill does - Loads a Stripe event payload from a JSON file or inline env var - Generates valid Stripe `Stripe-Signature` headers using your webhook secret (`whsec_...`) - Replays the exact same payload N times to simulate duplicate deliveries/retries - Prints per-attempt HTTP status and latency with a pass/fail summary ## Inputs Required: - `STRIPE_WEBHOOK_URL` (target endpoint) - `STRIPE_WEBHOOK_SECRET` (Stripe endpoint secret used to verify signatures) Payload source (choose one): - `STRIPE_EVENT_PATH` (default: `fixtures/sample-checkout-session-completed.json`) - `STRIPE_EVENT_JSON` (inline JSON payload; overrides `STRIPE_EVENT_PATH`) Optional: - `REPLAY_COUNT` (default: `2`) - `REPLAY_DELAY_SECONDS` (default: `0`) - `REQUEST_TIMEOUT_SECONDS` (default: `15`) - `ACCEPT_HTTP_CODES` (comma-separated exact HTTP codes accepted as success; default empty = any 2xx) ## Run ```bash STRIPE_WEBHOOK_URL=http://localhost:8000/webhooks/stripe \ STRIPE_WEBHOOK_SECRET=whsec_test_123 \ bash scripts/replay-stripe-webhook.sh ``` Force five duplicate deliveries with a small delay: ```bash STRIPE_WEBHOOK_URL=http://localhost:8000/webhooks/stripe \ STRIPE_WEBHOOK_SECRET=whsec_test_123 \ REPLAY_COUNT=5 \ REPLAY_DELAY_SECONDS=0.2 \ bash scripts/replay-stripe-webhook.sh ``` Use inline payload JSON: ```bash STRIPE_WEBHOOK_URL=http://localhost:8000/webhooks/stripe \ STRIPE_WEBHOOK_SECRET=whsec_test_123 \ STRIPE_EVENT_JSON='{"id":"evt_test","type":"checkout.session.completed","object":"event","data":{"object":{"id":"cs_test"}}}' \ bash scripts/replay-stripe-webhook.sh ``` ## Output contract - Prints payload event id/type when available - Logs each replay attempt: status code + elapsed milliseconds - Exit `0` if all attempts pass success criteria - Exit `1` if any attempt fails or inputs are invalid


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector:  ()
Skill: ckchzh/caption (version 2.0.5)

--- name: "caption" version: "2.0.4" description: "Reference tool for devtools — covers intro, quickstart, patterns and more. Quick lookup for Caption concepts, best practices, and implementation patterns." author: "BytesAgain" homepage: "https://bytesagain.com" source: "https://github.com/bytesagain/ai-skills" tags: [caption, reference] category: "devtools" --- # Caption Reference tool for devtools — covers intro, quickstart, patterns and more. Quick lookup for Caption concepts, best practices, and implementation patterns. No API keys or credentials required. ## Commands | Command | Description | |---------|-------------| | `intro` | intro reference | | `quickstart` | quickstart reference | | `patterns` | patterns reference | | `debugging` | debugging reference | | `performance` | performance reference | | `security` | security reference | | `migration` | migration reference | | `cheatsheet` | cheatsheet reference | ## Output Format All commands output plain-text reference documentation via heredoc. No external API calls, no credentials needed, no network access. --- *Powered by BytesAgain | bytesagain.com | [REDACTED_SECRET]*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)