OpenClaw/clawhub-security-signals huggingface dataset:
Skill: daniellummis/github-actions-incident-timeline-audit (version 1.0.0)

--- name: github-actions-incident-timeline-audit description: Cluster failed GitHub Actions runs into incident windows by repo to expose outage duration, impact scope, and escalation severity. version: 1.0.0 metadata: {"openclaw":{"requires":{"bins":["bash","python3"]}}} --- # GitHub Actions Incident Timeline Audit Use this skill to convert noisy failed run exports into incident windows you can triage quickly during CI reliability reviews. ## What this skill does - Reads GitHub Actions run JSON exports - Keeps only failed/cancelled/timed-out style outcomes - Groups failures by repository into incident windows using a configurable gap threshold - Scores each incident using failed-run and duration thresholds - Emits text or JSON output for review docs, ops dashboards, and CI fail gates ## Inputs Optional: - `RUN_GLOB` (default: `artifacts/github-actions/*.json`) - `TOP_N` (default: `20`) - `OUTPUT_FORMAT` (`text` or `json`, default: `text`) - `INCIDENT_GAP_MINUTES` (default: `45`) - `WARN_FAILED_RUNS` (default: `2`) - `CRITICAL_FAILED_RUNS` (default: `4`) - `WARN_DURATION_MINUTES` (default: `20`) - `CRITICAL_DURATION_MINUTES` (default: `60`) - `WORKFLOW_MATCH` (regex, optional) - `WORKFLOW_EXCLUDE` (regex, optional) - `REPO_MATCH` (regex, optional) - `REPO_EXCLUDE` (regex, optional) - `FAIL_ON_CRITICAL` (`0` or `1`, default: `0`) ## Collect run JSON ```bash gh run view <run-id> --json databaseId,workflowName,event,conclusion,headBranch,createdAt,updatedAt,startedAt,url,repository \ > artifacts/github-actions/run-<run-id>.json ``` ## Run Text report: ```bash RUN_GLOB='artifacts/github-actions/*.json' \ INCIDENT_GAP_MINUTES=45 \ bash skills/github-actions-incident-timeline-audit/scripts/incident-timeline-audit.sh ``` JSON output with fail gate: ```bash RUN_GLOB='artifacts/github-actions/*.json' \ OUTPUT_FORMAT=json \ FAIL_ON_CRITICAL=1 \ bash skills/github-actions-incident-timeline-audit/scripts/incident-timeline-audit.sh ``` Run with bundled fixtures: ```bash RUN_GLOB='skills/github-actions-incident-timeline-audit/fixtures/*.json' \ bash skills/github-actions-incident-timeline-audit/scripts/incident-timeline-audit.sh ``` ## Output contract - Exit `0` in report mode (default) - Exit `1` when `FAIL_ON_CRITICAL=1` and one or more incidents are critical - Text mode prints summary + ranked incident windows - JSON mode prints summary + incidents + critical incident details


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: leon2023happy/openclaw-cfg-safe-edit (version 1.0.0)

--- name: openclaw-cfg-safe-edit description: OpenClaw 配置文件修改前的验证规则。用于在修改 openclaw.json 或任何配置文件之前查询文档确认配置项可用性，避免因 OpenClaw 版本更新导致配置不兼容的问题。 --- # 配置验证规则 ## 触发条件 当用户请求修改以下内容时自动触发： - `openclaw.json` - `config/*.json` - 任何 OpenClaw 配置文件 ## 验证流程 ### 1. 查询本地文档 在修改配置前，先查询文档目录： ```bash # 列出文档结构 ls /home/root1/.npm-global/lib/node_modules/openclaw/docs # 搜索相关配置项 grep -r "<配置项名称>" /home/root1/.npm-global/lib/node_modules/openclaw/docs/ --include="*.md" ``` ### 2. 查阅配置 schema 查询配置 schema 确认字段定义： ```bash # 查看配置 schema 目录 ls /home/root1/.npm-global/lib/node_modules/openclaw/docs/cli/ # 或使用 gateway 工具查询 schema openclaw gateway config.schema.lookup <dot-path> ``` ### 3. 验证后再修改 确认配置项： - 存在于当前版本的文档中 - 用法正确 - 类型匹配 如果文档中没有该配置项： - 查看在线文档: https://docs.openclaw.ai - 或检查 OpenClaw 更新日志 ## 常见配置项参考 - `gateway.*` - 网关配置 - `plugins.*` - 插件配置 - `channels.*` - 通道配置 - `models.*` - 模型配置 - `storage.*` - 存储配置


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: careytian-ai/automation-workflow-builder (version 1.0.0)

--- name: automation-workflow-builder description: 自动化工作流构建器，设计并执行跨平台自动化流程，支持触发器、条件判断、多步骤操作。 metadata: openclaw: requires: bins: - exec - read - write - web_fetch --- # 自动化工作流构建器 v1.0.0 设计并执行自动化工作流，替代重复性人工操作。 ## 功能特性 ### 1. 触发器系统 - 定时触发（Cron） - 文件变化触发 - API webhook 触发 - 手动触发 ### 2. 条件判断 - IF/ELSE 逻辑 - 多条件组合 - 数据过滤 ### 3. 操作节点 - 文件操作（读/写/移动/复制） - 网络请求（GET/POST） - 数据处理（转换/格式化） - 命令执行 - 通知发送 ### 4. 工作流模板 - 数据同步 - 内容发布 - 报告生成 - 监控告警 ## 快速使用示例 ```javascript // 示例 1：定时抓取 + 处理 + 保存 const workflow = { trigger: { type: "cron", schedule: "0 */6 * * *" }, steps: [ { action: "fetch", url: "https://api.example.com/data" }, { action: "transform", script: "process(data)" }, { action: "save", path: "./output/data.json" } ] } // 示例 2：文件监控 + 自动处理 const workflow = { trigger: { type: "watch", path: "./inbox" }, steps: [ { action: "read", file: "${trigger.file}" }, { action: "process", type: "convert" }, { action: "move", to: "./processed" } ] } // 示例 3：多步骤数据同步 const workflow = { trigger: { type: "manual" }, steps: [ { action: "fetch", url: "source-api", output: "data1" }, { action: "fetch", url: "another-api", output: "data2" }, { action: "merge", inputs: ["data1", "data2"] }, { action: "upload", destination: "cloud-storage" } ] } ``` ## 预置工作流模板 ### 模板 1：竞品价格监控 ``` 触发：每天 9:00 步骤： 1. 抓取竞品网站价格 2. 与本地数据对比 3. 如有变化，发送通知 4. 保存历史记录 ``` ### 模板 2：内容自动发布 ``` 触发：新文件添加到./drafts 步骤： 1. 读取草稿内容 2. 格式化/优化 3. 发布到目标平台 4. 记录发布日志 ``` ### 模板 3：数据报告生成 ``` 触发：每周一 8:00 步骤： 1. 从多个 API 拉取数据 2. 合并、计算指标 3. 生成图表/表格 4. 导出 PDF/Excel 5. 发送邮件/消息 ``` ## 使用场景 1. **电商运营** - 价格监控、库存同步、订单处理 2. **内容创作** - 素材收集、格式转换、多平台发布 3. **数据分析** - 数据抓取、清洗、报告生成 4. **客户服务** - 自动回复、工单处理、反馈收集 5. **项目管理** - 进度跟踪、状态同步、提醒通知 ## 定制开发 需要定制化自动化工作流、企业级集成方案？ 📧 联系：careytian-ai@github --- ## 许可证 MIT-0


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: pyjhhh/book-writer (version 1.0.0)

--- name: book-writer description: 使用AI辅助写作的OpenClaw技能，可以根据提示词生成书籍大纲并逐级扩写内容，支持添加公式、图表、代码等元素。适用于学术著作、技术书籍、小说等多种类型的创作。 --- # OpenClaw 智能写书技能 这是一个功能完整的AI辅助写作技能，能够根据用户提供的提示词生成书籍大纲，并逐级扩写各章节内容，支持在内容中插入公式、图表、表格和代码等元素。 ## 功能特性 ### 📚 大纲生成能力 - **智能大纲生成**: 根据提示词自动生成结构化书籍大纲 - **多层级结构**: 支持章节、小节、子小节等多级结构 - **内容规划**: 为每个章节提供内容概要和要点 - **风格适配**: 根据书籍类型调整大纲结构 ### ✍️ 内容扩写能力 - **逐级扩写**: 从章节标题逐步扩展到具体内容 - **内容丰富**: 自动添加公式、图表、表格、代码等元素 - **引用管理**: 自动生成并管理文献引用 - **格式规范**: 遵循学术或出版格式规范 ### 🧩 多媒体支持 - **数学公式**: LaTeX格式的数学公式插入 - **图表生成**: 根据内容需求生成图表描述 - **代码片段**: 支持多种编程语言的代码插入 - **表格设计**: 结构化表格的创建和填充 ### 📖 类型适配 - **学术著作**: 符合学术写作规范 - **技术书籍**: 包含代码示例和技术图表 - **小说创作**: 支持情节发展和人物描写 - **教科书**: 包含练习题和知识点总结 ## 快速开始 ### 1. 安装技能 ```bash # 进入技能目录 cd book-writer # 安装依赖 python scripts/install_dependencies.py ``` ### 2. 设置API密钥 ```bash # 设置环境变量 export OPENAI_API_KEY="your_openai_api_key" export GOOGLE_CSE_ID="your_google_cse_id" # 用于搜索素材 export GOOGLE_API_KEY="your_google_api_key" # 用于搜索素材 ``` ### 3. 生成第一本书 ```bash # 生成大纲 python scripts/book_writer.py --action outline --prompt "机器学习入门教程" # 扩写前三章 python scripts/book_writer.py --action expand --book-path "ml_intro_tutorial" --chapters 1,2,3 ``` ## 核心组件 ### 书籍生成器 (`scripts/book_writer.py`) 主生成模块，负责协调整个书籍生成流程。 **主要功能:** - 解析用户提示词 - 生成书籍大纲 - 逐级扩写内容 - 管理多媒体元素 **使用方法:** ```python from scripts.book_writer import BookWriter writer = BookWriter() # 生成大纲 outline = writer.generate_outline("深度学习理论与实践") # 扩写内容 book = writer.expand_book(outline, max_chapters=3) # 保存书籍 writer.save_book(book, "deep_learning_book") ``` ### 内容优化器 (`scripts/content_optimizer.py`) 优化生成的内容质量。 **主要功能:** - 语法和风格优化 - 引用和参考文献管理 - 公式和代码验证 - 图表描述生成 ### 素材搜索器 (`scripts/material_searcher.py`) 从网络搜索相关素材。 **主要功能:** - 根据内容需求搜索图片 - 查找相关数据和统计信息 - 搜索代码示例 - 获取引用文献 ## 配置说明 ### 配置文件 (`config.yaml`) ```yaml # API配置 openai: [REDACTED_SECRET] model: gpt-4o max_tokens: 4000 temperature: 0.7 # 搜索API配置 google: cse_id: ${GOOGLE_CSE_ID} [REDACTED_SECRET] # 书籍生成默认参数 defaults: max_chapters: 10 max_sections_per_chapter: 5 content_length: "medium" # short, medium, long include_formulas: true include_code: true include_figures: true include_tables: true # 存储设置 storage: output_dir: "generated_books" temp_dir: "temp_files" max_storage_gb: 10 ``` ## 使用示例 ### 示例1：生成技术书籍大纲 ```bash python scripts/book_writer.py --action outline --prompt "Python Web开发实战指南" --output my_web_dev_book ``` ### 示例2：扩写指定章节 ```bash python scripts/book_writer.py --action expand --book-path my_web_dev_book --chapters 1,2,3 --include-code true ``` ### 示例3：生成学术著作 ```bash python scripts/book_writer.py --action full --prompt "量子计算基础理论" --chapters 3 --include-formulas true --citation-style "apa" ``` ## 部署到OpenClaw 将整个 `book-writer` 目录复制到 OpenClaw 的技能目录中即可使用。 ## 许可证 本技能使用MIT许可证。详见项目根目录的LICENSE文件。


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (CRITICAL)
Skill: kenera/a-share-short-decision (version 1.2.0)

--- name: A股短线交易决策 A-Share Short-Term Decision slug: a-share-short-decision description: A-share short-term trading decision skill for 1-5 day horizon. Use when you need real-data market sentiment, sector rotation, strong stock scanning, capital flow confirmation, date-based short-term signal scoring, prediction logging, and next-day market comparison for CN A-share momentum trading. --- # A-Share Short-Term Decision Skill Implement in sequence: 1. Run `short_term_signal_engine(analysis_date)` for target date. 2. If needed, persist prediction with `run_prediction_for_date(analysis_date)`. 3. Compare prediction vs actual market with `compare_prediction_with_market(prediction_date, actual_date)`. 4. Output report with `generate_daily_report(analysis_date)`. ## Tool Contracts ### `short_term_signal_engine(analysis_date=None)` - `analysis_date`: `YYYY-MM-DD` or `YYYYMMDD` - Returns weighted short-term score and recommendation status. - Always returns friendly `no_recommendation_message` when no tradable candidate exists. ### `run_prediction_for_date(analysis_date)` - Runs signal engine for the specified date. - Appends decision snapshot into `data/decision_log.jsonl`. ### `compare_prediction_with_market(prediction_date, actual_date=None)` - Loads prediction from log (or auto-generates if missing). - Compares predicted candidates against real market closes on `actual_date`. - Returns per-stock return and summary statistics. ## No-Recommendation Behavior Required behavior: - Never return empty output. - If `candidates` is empty or signal is `NO_TRADE`, explicitly say: `当前暂无可执行短线买入标的`. - Include reason and next action. ## Runtime ```bash python3 main.py short_term_signal_engine --date 2026-02-12 python3 main.py run_prediction_for_date --date 2026-02-12 python3 main.py compare_prediction_with_market --prediction-date 2026-02-12 --actual-date 2026-02-13 python3 main.py generate_daily_report --date 2026-02-12 ``` ## Subskills Workflow For recurring optimize-then-recommend flow, run: ```bash python3 subskills/config-optimization/optimize_from_aggressive.py --analysis-period "2026-02-01 to 2026-02-12" python3 subskills/daily-recommendation/generate_daily_recommendation.py --date 2026-02-14 ``` All generated artifacts are stored under `data/`.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: know-hub/keep-fit (version 1.0.0)

--- name: keep_fit description: Generate sustainable fitness plans, daily workouts, and health routines based on user goals, time, and fitness level. version: 1.0.0 --- # Keep Fit Skill You are a fitness planning assistant focused on **sustainable, realistic, and safe fitness routines**. ## Core Principles - Sustainability > intensity - Consistency > perfection - Adapt to user's lifestyle - Prefer simple, effective routines - Default to home/bodyweight unless specified ## When user asks for fitness help: Always clarify or infer: - Goal (fat loss / strength / general fitness / posture / energy) - Time available - Equipment (none, home, gym) - Experience level (beginner/intermediate/advanced) ## Output Types ### 1. Weekly Plan Provide: - 5–7 day structured plan - Mix of cardio + strength + recovery - Duration per session - Clear instructions ### 2. Single Workout Provide: - Warm-up (3–5 min) - Main workout (10–30 min) - Optional finisher - Cool down ### 3. Habit Plan Provide: - Daily movement targets (steps, stretch) - Simple routines (e.g. morning mobility) - Lifestyle suggestions (sleep, hydration) ## Style - Clear, practical, actionable - Avoid overly technical jargon - No extreme diets or unsafe advice ## Constraints - Do NOT give medical advice - Avoid extreme calorie restriction - Avoid injury-risk exercises for beginners ## Example Requests - "Give me a 20 min workout at home" - "Create a weekly fitness plan" - "I sit a lot, help me stay active" - "Fat loss plan for beginners" ## Response Quality Always: - Be specific - Be realistic - Be easy to follow - Prioritize long-term adherence


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: abstract-sum/nutrition-tracker (version 0.1.0)

--- name: nutrition-tracker description: Track daily calories and macros in Obsidian, with profile initialization (sex/height/weight/goal) and goal-based target checks. Includes i18n (zh-CN/en-US). Use when user logs meals, asks if targets are met, or wants to set/remember nutrition profile. --- # Nutrition Tracker (Obsidian) This skill logs meals (kcal + P/C/F) into an Obsidian vault and maintains daily totals. It also stores a lightweight nutrition profile (sex/height/weight/activity/goal) and can evaluate whether today's intake meets targets. > i18n: scripts support `--lang zh-CN|en-US` (default: `zh-CN`). ## Storage - Vault (default): `~/Documents/obsidian/yzhai-daily` - Profile: `health/eat/profile.json` - Monthly log: `health/eat/YYYY-MM/YYYYMM_calories_macros.md` ## Quick start ### 1) Initialize / update profile ```bash bash ~/.openclaw/workspace/skills-public/nutrition-tracker/scripts/nutrition_init.sh \ --sex male \ --height 175 \ --weight 75 \ --activity office \ --goal cut \ --kcal 2200 \ --lang zh-CN ``` ### 2) Log a meal ```bash bash ~/.openclaw/workspace/skills-public/nutrition-tracker/scripts/nutrition_log.sh \ --date "2026-03-04" --time "19:54" --meal dinner \ --desc "rice 150g; potato 120g; meat+egg 200g; soup 200g" \ --kcal 830 --p 45 --c 69 --f 40 \ --lang zh-CN ``` ### 3) Check whether today's targets are met ```bash bash ~/.openclaw/workspace/skills-public/nutrition-tracker/scripts/nutrition_check_today.sh \ --date "2026-03-04" \ --lang zh-CN ``` ## Target logic (defaults) If profile has no explicit macro targets, defaults are computed by goal: - **cut** (fat loss): - Protein: `2.0 g/kg` - Fat: `0.8 g/kg` - Carbs: remaining calories (based on kcal target) You can override targets explicitly in profile (see `nutrition_init.sh --pTarget/--cTarget/--fTarget`). ## Notes - Keep meal macros as estimates; refine later by updating entries. - This skill is designed to be deterministic via scripts, not free-form editing.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: shuakami/uapi-get-game-epic-free (version 1.0.0)

--- name: uapi-get-game-epic-free description: "使用 UAPI 的“Epic 免费游戏”单接口 skill，处理 Epic 免费游戏、Epic免费游戏、游戏资料 等请求。 Use when the user wants get game epic free, game epic-free, epic-free, epic free games, or when you need to call GET /game/epic-free directly." --- # UAPI Epic 免费游戏 接口 这个 skill 只封装一个接口：`GET /game/epic-free`。当需求和“Epic 免费游戏”直接对应时，优先直接选它，再去接口页确认参数、鉴权和返回码。 ## 先用这个 skill 的场景 如果用户已经明确要拿「Epic 免费游戏」这类结果，就可以把 `GET /game/epic-free` 当成主入口，先收敛到这一条接口，再补参数、额度和返回码。 - 优先处理已经点名要查「Epic 免费游戏」的请求，这种场景一般不需要再绕回大分类重新挑接口。 - 优先处理已经给出核心查询条件的请求，这样可以更快转到参数确认和调用准备。 - 如果用户只是在确认“这个需求是不是该用这个接口”，也可以先用这个 skill 做命中判断，再决定是否继续发请求。 - 如果这次还要解释响应结构、错误分支或额度状态，可以在锁定接口之后再补说明，不要一开始就把信息摊得太散。 ## 把请求发出去前先过一遍 1. 先确认用户要的是结果摘要、完整字段，还是只要一个可以直接展示的值。 2. 再确认这次是否需要把返回码、失败提示和额度提醒一起说清楚。 3. 最后回到 operations 文档核对默认值、互斥参数和生效条件，避免误用字段。 4. 如果访客额度可能不够，就提前准备好 UAPI Key 的处理分支，别等到调用失败后再补救。 ## 这个 skill 封装的接口 - 方法：`GET` - 路径：`/game/epic-free` - 分类：`Game` - Operation ID：`get-game-epic-free` ## 什么时候直接选这个 skill - 当用户的目标和“Epic 免费游戏”完全对应时，优先直接选它。 - 这个 skill 只对应一个接口，所以不需要在大分类里二次挑选。 - 如果用户已经给了足够的参数，就可以直接进入接口页准备调用。 ## 常见关键词 - 中文：`Epic 免费游戏`、`Epic免费游戏`、`游戏资料` - English: `get game epic free`, `game epic-free`, `epic-free`, `epic free games` ## 使用步骤 1. 先读 `references/quick-start.md`，快速确认这个单接口是否就是当前要用的目标接口。 2. 再读 `references/operations/get-game-epic-free.md`，确认参数、请求体、默认值、生效条件和响应码。 3. 如果需要看同分类上下文，再读 `references/resources/Game.md`。 ## 鉴权与额度 - Base URL：`https://uapis.cn/api/v1` - 大部分游戏接口可以直接调用；如果是 Steam 用户相关能力，要额外留意 Steam Web API Key 这类第三方凭证。 - 如果这个接口返回 429，或者错误信息明确提示访客免费额度、免费积分或匿名配额已用完，可以建议用户到 https://uapis.cn 注册账号，并创建免费的 UAPI Key，再带上 Key 重试。 ## 常见返回码关注点 - 当前文档里能看到的状态码：`200`、`500` ## 代表性的用户说法 - 帮我用 UAPI 的“Epic 免费游戏”接口处理这个需求 - 这个需求是不是应该调用 Epic 免费游戏 这个接口 - use the UAPI get-game-epic-free endpoint for this task ## 导航文件 - `references/quick-start.md`：先快速判断这个单接口 skill 是否匹配当前需求。 - `references/operations/get-game-epic-free.md`：这里是调用前必须看的核心接口页。 - `references/resources/Game.md`：只在需要补充同分类背景时再看。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: cccarv82/openclaw-backup-optimized (version 1.0.1)

--- name: openclaw-backup-optimized description: "Optimized OpenClaw backup skill for creating full snapshots with workspace archive splitting, change summaries, restore instructions, and Discord notifications. Use when you need to set up or run automated backups, configure backup cron jobs, or document/restore OpenClaw state. Triggers on backup automation, backup scripts, snapshot/restore, or GitHub backup repos." --- # OpenClaw Backup (Optimized) ## What this skill does Use this skill to **install, configure, and run** the optimized OpenClaw backup workflow: - Full snapshot of `~/.openclaw` - Workspace archive split into ~90MB parts + SHA256 - Rich Discord notification (summary + restore steps) - Retention of last N reports ## Files - Script: `scripts/backup.js` (cross-platform) - Reference config: `references/CONFIG.md` ## Install / Setup 1) Copy the script into your tools folder: ```bash cp scripts/backup.js ~/.openclaw/workspace/tools/openclaw-backup.js ``` 2) Configure env vars (see references/CONFIG.md): **macOS/Linux (bash/zsh):** ```bash export OPENCLAW_HOME="$HOME/.openclaw" export OPENCLAW_BACKUP_DIR="$HOME/.openclaw-backup" export BACKUP_REPO_URL="https://github.com/your/repo.git" export BACKUP_CHANNEL_ID="1234567890" export BACKUP_TZ="America/Sao_Paulo" export BACKUP_MAX_HISTORY=7 ``` **Windows (PowerShell):** ```powershell $env:OPENCLAW_HOME="$env:USERPROFILE\.openclaw" $env:OPENCLAW_BACKUP_DIR="$env:USERPROFILE\.openclaw-backup" $env:BACKUP_REPO_URL="https://github.com/your/repo.git" $env:BACKUP_CHANNEL_ID="1234567890" $env:BACKUP_TZ="America/Sao_Paulo" $env:BACKUP_MAX_HISTORY="7" ``` 3) Run once: ```bash node ~/.openclaw/workspace/tools/openclaw-backup.js ``` 4) Create cron (OpenClaw cron runs in the gateway environment): ```bash openclaw cron add --name "openclaw-backup-daily" \ --cron "0 5,10,15,20 * * *" --tz "America/Sao_Paulo" \ --exec "node ~/.openclaw/workspace/tools/openclaw-backup.js" ``` ## Restore Use the restore instructions printed in the backup notification. ## Notes - Excludes noisy session lock/deleted files for smaller diffs. - Requires `git` and `node` (>=18). - Uses `openclaw message send` for notifications (no webhook). - `scripts/openclaw-backup.sh` is legacy (Linux/macOS) and will be removed; use `backup.js`.


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: suspicious | SkillSpector: suspicious (MEDIUM)
Skill: ckchzh/dev-utilities (version 2.0.4)

--- name: "dev-utilities" version: "2.0.3" description: "Reference tool for devtools — covers intro, quickstart, patterns and more. Quick lookup for Dev Utilities concepts, best practices, and implementation patterns." author: "BytesAgain" homepage: "https://bytesagain.com" source: "https://github.com/bytesagain/ai-skills" tags: [dev,utilities, reference] category: "devtools" --- # Dev Utilities Reference tool for devtools — covers intro, quickstart, patterns and more. Quick lookup for Dev Utilities 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)
Skill: afengzi/lark-cli-devhub-docs-wiki (version 0.1.1)

--- name: lark-cli-devhub-docs-wiki description: Use when organizing Feishu/Lark Wiki spaces or Docs through lark-cli or feishu-cli for a development knowledge hub, including project pages, design notes, runbooks, bug retrospectives, and long-form artifacts linked from Base. metadata: requires: bins: ["lark-cli"] --- # Lark CLI Dev Hub Docs And Wiki Use Docs/Wiki for long-form context that would make Base records too noisy. Base remains the index; Docs/Wiki are linked artifacts. Discovery aliases: `feishu-cli docs`, `feishu-cli wiki`, `飞书知识库`, `飞书文档`, `lark-cli docs`, `lark-cli wiki`. ## Wiki Structure Recommended first-level pages: - `00 Inbox`: temporary notes waiting to become structured records. - `10 Projects`: one page per project, linked from the `Projects` Base table. - `20 Bugfix Retros`: long bug narratives worth rereading. - `30 Playbooks`: expanded runbooks that do not fit in Base. - `40 Decisions`: architecture and product decisions. - `50 Maps`: whiteboard landing pages and visual summaries. - `90 Archive`: stale or superseded artifacts. ## Page Rules - Every useful page should have a matching `Artifacts` Base record. - Put summary, project, area, tags, and search keywords into Base. - Do not rely on Wiki hierarchy as the only retrieval mechanism. - Avoid dumping raw logs unless they are short and safe. ## Creation Pattern ```bash lark-cli docs +create --api-version v2 --as user \ --content '<title>Bugfix Retro: short title</title><p>Summary...</p>' ``` Move into Wiki when needed: ```bash lark-cli wiki +node-create --as user \ --space-id "$SPACE_ID" \ --title "Bugfix Retro: short title" \ --obj-type docx ``` When official `lark-doc` or `lark-wiki` skills are installed, use them for exact command syntax and permission handling.


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