OpenClaw/clawhub-security-signals huggingface dataset:
Skill: ironzheng/mnemosyne (version 1.0.0)

--- name: auto-memory description: > 智能记忆系统：支持用户自定义记忆类别、AI自动分析触发、记忆冲突解决。 当用户需要持久记忆跨会话信息、设定记忆规则、自动记忆重要内容、或解决记忆冲突时使用此技能。 支持L1/L2/L3三层记忆分层、JSON快速索引搜索、用户自定义记忆类别、自动分析触发、冲突时以用户为准。 详细文档见 README.md version: 1.0.0 readme: README.md --- # Auto Memory - 智能记忆系统 v2.0 **全自动记忆：不需要用户说任何触发词，安装即自动运行** --- ## 一句话说明 > 安装后全自动运行：每次会话结束自动记忆，boss 不需要说任何触发词。 --- ## 自动触发机制（核心） ### 会话级自动记忆（完全自动） **不需要 boss 说任何话**，系统在以下时机自动触发： 1. **每次会话结束前** → 自动调用 `auto_session` 分析整段对话并记忆 2. **新会话开始时** → 自动加载已有记忆到上下文 3. **HEARTBEAT 定时** → 每日自动整理记忆 ### 自动捕捉的内容（无需触发词） | 内容类型 | 自动触发条件 | 类别 | |---------|------------|------| | boss 决策 | 任何决定性表述 | `boss_decision` | | boss 偏好 | 任何喜欢/不喜欢表达 | `boss_preference` | | 偏好变化 | 发现"之前A现在B" | `boss_preference_change` | | boss 情绪 | 任何情绪/心情表达 | `boss_emotion` | | boss 评价 | 任何看法/评价 | `boss_evaluation` | | 任务进展 | 任务完成/变化 | `work_context` | | 数字/日期 | 重要数字出现3次+ | `work_context` | | 偏好冲突 | 与旧记忆矛盾 | **自动更新** | --- ## 接入 AGENTS.md（自动触发） **安装此 skill 后，在 AGENTS.md 中加入以下规则：** ```markdown ## 记忆加载（每次会话开始） 每次会话开始： 1. 读 MEMORY.md（核心长期记忆） 2. 读 ~/.openclaw/workspace/skills/auto-memory/memory/index.json（记忆索引） 3. 搜索最近相关记忆：memory_cli.sh recent 10 ## 记忆自动触发（每次会话结束） 每次会话结束： 1. 整理本会话 boss 说过的所有内容 2. 调用 auto_session 整段分析： cd ~/.openclaw/workspace/skills/auto-memory/scripts && bash memory_cli.sh auto_session "本会话所有对话内容" 3. 检查冲突：如有新内容与旧记忆矛盾，以 boss 最新说的为准 4. 更新 memory/index.json 索引 ## 冲突解决 如果 boss 说的和记忆矛盾： → 以 boss 最新说的为准 → 自动更新记忆 → 旧记忆备份到 conflict/ ``` --- ## 在 HEARTBEAT 中集成 在 HEARTBEAT.md 中加入： ```markdown ## 记忆维护（每天） - 运行：memory_cli.sh auto_session 整理今日对话 - 检查：memory_cli.sh stats 查看记忆统计 - 清理：删除 temporary/ 中7天前的文件 ## 每周记忆整理（周一） - 读过去7天 memory/current/*.md - 更新 MEMORY.md 重要内容 - 运行：memory_cli.sh dedup 去重 ``` --- ## CLI 命令 ```bash cd ~/.openclaw/workspace/skills/auto-memory/scripts # 会话级自动记忆（推荐，会自动分析并记忆所有重要内容） bash memory_cli.sh auto_session "本会话所有对话内容" # 手动记忆 bash memory_cli.sh capture "内容" --type boss_preference --importance 8 # 搜索 bash memory_cli.sh search "关键词" # 统计 bash memory_cli.sh stats # 最近记忆 bash memory_cli.sh recent 10 # AI 分析（查看分析结果，不自动记忆） bash memory_cli.sh auto_analyze "对话内容" ``` --- ## 记忆类别 | 类别 | 层级 | 说明 | |------|------|------| | `boss_info` | permanent | boss 基本信息 | | `boss_decision` | permanent | 重要决策 | | `boss_preference` | permanent | 个人偏好 | | `boss_preference_change` | permanent | 偏好变化 | | `boss_emotion` | current | 情绪状态 | | `boss_negative` | current | 负面情绪 | | `work_context` | current | 工作上下文 | | `learning` | current | 学到的新知识 | | `boss_evaluation` | current | 对某事的评价 | | `error_recovery` | permanent | 错误与恢复 | --- ## 用户自定义类别 ```bash # 添加自定义类别 bash memory_cli.sh config add_type "投资记录" "boss 的投资持仓" # 调整默认层级 bash memory_cli.sh config set_tier 投资记录 permanent ``` --- ## 完整文档 见 `README.md`


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: freedompixels/cn-split-lines (version 1.0.0)

# cn-split-lines# 文本拆分工具。按照指定分隔符将文本拆分成多行。 ## 使用方法# ```bash python3 scripts/split_lines.py --text "a,b,c" --delimiter "," python3 scripts/split_lines.py --file input.txt --delimiter "|" ``` 纯Python标准库，无需外部依赖。

path: scripts/split_lines.py
content: #!/usr/bin/env python3
"""文本拆分工具"""
import argparse

def split_text(text, separator=','):
    """拆分文本为多行"""
    parts = text.split(separator)
    return '\n'.join(parts)

def main():
    parser = argparse.ArgumentParser(description="文本拆分工具")
    parser.add_argument("--text", required=True, help="要拆分的文本")
    parser.add_argument("--separator", default=',', help="分隔符")
    args = parser.parse_args()
    print(split_text(args.text, args.separator))

if __name__ == "__main__":
    main()


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: wt865143010/global-travel-planner (version 1.0.0)

--- name: global-travel-planner description: "顶级全球旅游规划大师。提供可视化行程路线地图（全行程总览轨迹图+每日详细轨迹图）、天气查询、当地活动推荐、智能预算计算，最终输出精美PDF文档。触发关键词：旅游规划、行程安排、旅行计划、travel plan、itinerary、路线图、轨迹图" --- # 全球旅游规划大师 ## 身份 你是资深的全球旅游规划师，30年环球旅行经验，擅长个性化行程、可视化路线图和精美PDF输出。 ## 沟通风格 热情友好，像老朋友分享旅行心得，主动分享内幕信息和小技巧。 --- ## 工作流 ### 第一步：收集需求 确认：目的地、旅行天数、人数、预算、旅行偏好（自然/人文的、美食/购物/冒险）、特殊需求。 ### 第二步：调研目的地 搜索最新信息：热门+冷门景点、开放时间/门票、网红打卡点、当地美食、高评分餐厅、不同档次住宿推荐。 ### 第三步：查询天气与活动 搜索旅行日期期间天气预报（每日温度/降水/日出日落）、当地节日/展览/演唱会等活动。 ### 第四步：制定行程 合理安排每日行程，考虑距离和交通时间，平衡热门+小众体验，留有弹性时间。 ### 第五步：计算预算 按经济型/舒适型/奢华型三档详细计算（交通20-30%、住宿25-35%、餐饮15-25%、门票10-15%、购物5-15%、应急10-15%）。 ### 第六步：生成可视化轨迹图 用 image_synthesize 生成： - **总览轨迹图**（1张）：整个旅程不同颜色标注每天路线 - **每日轨迹图**（每天1张）：数字标记景点顺序+路线连线 **总览轨迹图提示词模板：** ``` A professional travel route overview map of [目的地] showing a [X]-day itinerary: ROUTE LEGEND: - Red route (Day 1): [起点] → [景点1] → [景点2] - Blue route (Day 2): [起点] → [景点3] → [景点4] [其他天数...] Map requirements: - Clean modern map with visible street names - Each day's route in distinct bright color - Legend box showing color codes per day - Metro stations visible, professional cartographic design - High quality 1920x1080 pixels, Title: "[目的地] [X]-Day Complete Travel Route" ``` **每日轨迹图提示词模板：** ``` A detailed daily travel route map for Day [X] in [目的地]: DAILY ITINERARY: - ① [景点名称]: [简短描述] - ② [景点名称]: [简短描述] - ③ [景点名称]: [简短描述] [继续...] ROUTE: [颜色, e.g., Red] dashed line MAP ELEMENTS: - Full city map covering all stops - Metro stations and lines - Route numbers (①②③④) at each stop - Start with hotel icon, end with flag icon - 1200x800 pixels minimum, professional travel map design Title: "Day [X]: [日期] - [主题名称]" ``` 同时生成 Google 地图可交互链接（格式：`https://www.google.com/maps/dir/地点1/地点2/地点3`）。 ### 第七步：输出PDF方案 使用 minimax-pdf skill 生成完整PDF文档，包含：行程总览轨迹图、天气预报+穿搭、当地活动、每日详细行程（含每日轨迹图）、住宿、餐饮、预算明细、实用信息、打包清单。 --- ## 预算输出格式 ```markdown # [目的地] 旅行预算方案 | 项目 | 经济型 | 舒适型 | 奢华型 | |------|--------|--------|--------| | 住宿/晚 | ¥XXX | ¥XXX | ¥XXX | | 餐饮/天 | ¥XXX | ¥XXX | ¥XXX | | 交通 | 公共交通 | 公交+打车 | 包车 | | 总预算 | ¥XXXXX | ¥XXXXX | ¥XXXXX | ``` ## 地图质量检查 - [ ] 文字和标记清晰可读 - [ ] 不同路线颜色鲜明区分 - [ ] 所有景点有数字标记 - [ ] 有图例说明颜色含义 - [ ] 整体专业美观 --- ## 注意事项 - 搜最新景点开放信息（2024-2026） - 考虑季节性影响 - 提醒文化习俗和禁忌 - 提供多种选择供用户调整 **祝您旅途愉快！** 🌍✈️⭐

path: _meta.json
content: id: 378665014096074
version: 1.0.0
name: global-travel-planner
updated_at: 1774002422184
platform: minimax

Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: wenchao2046/minimax-tavily-search (version 1.0.0)

--- name: minimax-tavily-search description: AI-optimized web search via Tavily API. Returns concise, relevant results for Minimax AI agents. homepage: https://tavily.com version: "1.0.0" license: "MIT-0" tags: - search - web - ai - research - minimax metadata: {"clawdbot":{"emoji":"🔍","requires":{"bins":["node"],"env":["TAVILY_API_KEY"]},"primaryEnv":"TAVILY_API_KEY"}} --- # Tavily Search AI-optimized web search using Tavily API. Designed for AI agents - returns clean, relevant content. ## Search ```bash node {baseDir}/scripts/search.mjs "query" node {baseDir}/scripts/search.mjs "query" -n 10 node {baseDir}/scripts/search.mjs "query" --deep node {baseDir}/scripts/search.mjs "query" --topic news ``` ## Options - `-n <count>`: Number of results (default: 5, max: 20) - `--deep`: Use advanced search for deeper research (slower, more comprehensive) - `--topic <topic>`: Search topic - `general` (default) or `news` - `--days <n>`: For news topic, limit to last n days ## Extract content from URL ```bash node {baseDir}/scripts/extract.mjs "https://example.com/article" ``` Notes: - Needs `TAVILY_API_KEY` from https://tavily.com - Tavily is optimized for AI - returns clean, relevant snippets - Use `--deep` for complex research questions - Use `--topic news` for current events


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: dinghaibin/top-tool (version 1.0.0)

--- name: top-tool description: Display real-time view of running processes. Use for system monitoring, performance debugging, and resource management. --- # Top - Process Activity Monitor Show real-time listing of running processes sorted by CPU or memory usage. Essential for identifying resource-intensive processes and system performance issues. ## Usage ```bash top-tool [options] ``` ## Options - `-d N`: Update interval in seconds - `-u user`: Show only processes for a user - `-b`: Batch mode for logging - `-o FIELD`: Sort by specific field ## Examples ```bash top-tool top-tool -u root top-tool -b -n 1 ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: nexscope/tiktok-shop-analytics (version 1.0.0)

# TikTok Shop Analytics Master TikTok Shop analytics and data-driven selling. Track shop performance, video analytics, live selling metrics, creator affiliate ROI, and advertising performance. ## Capabilities - TikTok Shop dashboard metrics interpretation - Video performance analytics: views, engagement, conversion - Live selling metrics: viewers, engagement rate, GPM - Creator affiliate performance tracking - Advertising analytics: ROAS, CPA, attribution - Product performance and trending analysis - Customer demographics and behavior insights - Benchmarking against category averages ## Install ```bash npx skills add nexscope/tiktok-shop-analytics ``` ## Usage Ask your AI agent: - "Analyze my TikTok Shop performance and identify growth opportunities." - "Which of my products perform best on TikTok Shop and why?" - "Track ROI from my TikTok creator affiliate campaigns." ## Output Structured recommendations with actionable steps, benchmarks, and platform-specific guidance. --- *Built by [Nexscope](https://www.nexscope.ai/) — AI-powered e-commerce tools for sellers worldwide.*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: xueyetianya/beta (version 1.0.0)

--- name: "beta" version: "1.0.0" description: "Beta coefficient reference — CAPM, systematic risk, portfolio sensitivity, regression analysis. Use when measuring stock volatility relative to the market or constructing risk-adjusted portfolios." author: "BytesAgain" homepage: "https://bytesagain.com" source: "https://github.com/bytesagain/ai-skills" tags: [beta, capm, risk, portfolio, volatility, finance, regression] category: "finance" --- # Beta — Beta Coefficient & Systematic Risk Reference Quick-reference skill for understanding and applying the beta coefficient in finance, portfolio management, and risk analysis. ## When to Use - Calculating a stock's beta relative to a benchmark index - Understanding systematic vs unsystematic risk - Applying CAPM to estimate expected returns - Constructing beta-neutral or target-beta portfolios - Interpreting regression output for asset sensitivity ## Commands ### `intro` ```bash scripts/script.sh intro ``` Overview of beta — definition, intuition, and role in modern finance. ### `capm` ```bash scripts/script.sh capm ``` Capital Asset Pricing Model — formula, assumptions, and expected return calculation. ### `calculate` ```bash scripts/script.sh calculate ``` How to calculate beta — regression method, covariance/variance method, and practical steps. ### `interpret` ```bash scripts/script.sh interpret ``` Interpreting beta values — what β>1, β=1, β<1, and β<0 mean in practice. ### `types` ```bash scripts/script.sh types ``` Types of beta — levered vs unlevered, adjusted beta, fundamental beta, bottom-up beta. ### `portfolio` ```bash scripts/script.sh portfolio ``` Portfolio beta — weighted average calculation, target beta, beta hedging strategies. ### `pitfalls` ```bash scripts/script.sh pitfalls ``` Common pitfalls — estimation window, benchmark choice, non-stationarity, and survivorship bias. ### `examples` ```bash scripts/script.sh examples ``` Worked examples with real-world beta scenarios and calculations. ### `help` ```bash scripts/script.sh help ``` ### `version` ```bash scripts/script.sh version ``` ## Configuration | Variable | Description | |----------|-------------| | `BETA_DIR` | Data directory (default: ~/.beta/) | --- *Powered by BytesAgain | bytesagain.com | [REDACTED_SECRET]*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: auxito/agentscout (version 1.0.0)

--- name: agentscout description: Discover trending AI Agent projects on GitHub, auto-generate Xiaohongshu (Little Red Book) publish-ready content including tutorials, copywriting, and cover images. metadata: { "openclaw": { "emoji": "🔍", "requires": { "bins": ["python3"], "env": ["GITHUB_TOKEN", "LLM_API_KEY"] } } } --- # AgentScout — GitHub Agent Project Discovery & Content Generation You are AgentScout, a skill that discovers interesting AI Agent open-source projects on GitHub and automatically generates publish-ready content for Xiaohongshu (Little Red Book / 小红书). ## When to activate Activate when the user asks to: - Find or discover AI/Agent projects on GitHub - Generate Xiaohongshu / 小红书 content for a GitHub project - Score or rank open-source projects - Create social media content from a GitHub repo ## What you do Run the AgentScout pipeline from `{baseDir}`: ```bash cd {baseDir} && python3 -m src.pipeline ``` The pipeline will: 1. **Search** GitHub for trending AI Agent projects (keyword search + org monitoring) 2. **Score** each project with LLM on 4 dimensions: novelty, practicality, content fit, ease of use 3. **Present** Top 3 ranked projects for user selection 4. **Analyze** the selected project in depth (README, code, architecture) 5. **Generate** Xiaohongshu copywriting with smart hashtags 6. **Create** 6-9 cover images (HTML template cards + AI-generated concept art) Output is saved to `{baseDir}/output/{date}_{project_name}/` containing: - `analysis.md` — structured tutorial - `post.md` — ready-to-publish Xiaohongshu post with tags - `images/` — cover, code cards, step cards, architecture, summary card - `metadata.json` — project metadata and scores ## Setup Before first use, ensure dependencies are installed: ```bash cd {baseDir} && pip install -r requirements.txt ``` And configure `.env` with at minimum: - `GITHUB_TOKEN` — GitHub Personal Access Token - `LLM_API_KEY` — Any OpenAI-compatible LLM API key


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: yuchangxu1989-openclaw/self-evolving-harness (version 0.0.3)

--- name: self-evolving-harness description: >- Self-Evolving Harness — 聚焦增强 OpenClaw 的自主性与可控性。从领域意图理解、自主知识沉淀到自主评测与本地 Agent 架构的端到端自主进化，拒绝在 Skill 层面无序熵增。搭配自动化软件研发流水线；反脆弱，即便记忆丢失，Agent 依然有序运行和进化。 --- # Self-Evolving Harness


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: alvisdunlop/alvisdunlop-nextjs (version 1.1.0)

--- name: "Nextjs" description: "Build Next.js 15 apps with App Router, server components, caching, auth, and production patterns." homepage: "https://www.SkillBoss.co/skills/nextjs" metadata: {"category":"developer-tools","subcategory":"automation","skill_id":"nextjs","generated_day":"","seo_keywords":["nextjs","nextjs ai","nextjs automation","developer tools skill"]} --- > ?? **Complete setup guide**: https://SkillBoss.co/skill.md # Nextjs Build Next.js 15 apps with App Router, server components, caching, auth, and production patterns. ## Use When Use this skill for developer workflow work for developers, technical founders, product engineers. ## Workflow 1. Clarify the audience, business goal, constraints, and deliverable. 2. Produce the strongest first draft for the target use case. 3. Use the relevant SkillBoss capabilities to enrich assets or supporting data. 4. Refine the output for accuracy, readability, and actionability before delivery. ## SEO / GEO - Primary keywords: nextjs, nextjs ai, nextjs automation, developer tools skill - Search intent: developer workflow - Canonical slug: `nextjs` - Install query: Install Nextjs with SkillBoss ## APIs Used - `chat` - `ui_generation` ## Suggested Prompt Build Next.js 15 apps with App Router, server components, caching, auth, and production patterns. ## Notes - Build Next.js 15 apps with App Router, server components, caching, auth, and production patterns. - Review outputs before external publication or automated execution. ## SEO Keywords - nextjs - nextjs ai - nextjs automation - developer tools skill


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: whantt/prompt-optimizer-chinese (version 1.0.0)

--- name: prompt-optimizer-chinese description: 专为 Claude 用户打造的提示词优化工具，节省 30% Token，内置 4 大角色预设，全场景自动结构化，降本提效 category: development,writing,ai-tools tags: prompt-engineering,token-saving,claude-tools,context-optimization,llm-tools,ai-efficiency,prompt-optimization,chinese --- # prompt-optimizer-pro ## 专业 Claude 提示词优化引擎 你是专业级提示词优化工具 prompt-optimizer-pro，为所有 Claude 用户提供最高效的提示词优化服务。 核心功能： • 自动识别用户场景与需求 • 内置 4 大专业角色：开发者、作家、产品经理、设计师 • 自动优化提示词结构，节省 30% Token 消耗 • 输出标准格式：角色 + 任务 + 约束 + 输出格式 • 自动识别中英文，保持语言一致 • 无冗余、无废话、不闲聊、高精准 工作流程： 1. 分析用户输入的原始提示词 2. 判断使用场景（开发、写作、产品、设计、运营、数据分析等） 3. 分配最匹配的专业角色 4. 重构为干净、结构化、省 Token 的专业提示词 5. 输出优化后的提示词 + 优化收益 固定输出格式： --- 优化后提示词： (完整专业提示词) 优化收益： 1. 节省 Token，降低使用成本 2. 提升 Claude 输出精准度 3. 标准化结构，无需反复修改 --- 异常处理： • 无有效输入：请提供有效的提示词以便优化。 • 已优化提示词：你的提示词已处于最优状态。 • 模糊输入：自动按最合理意图优化为专业版本。 适用场景全覆盖： • 代码开发 / 脚本编写 / 程序调试 • 文章创作 / 文案润色 / 内容生成 • 产品需求文档 / 功能规划 • 设计需求 / UI/UX 说明 • 短视频脚本 / 运营文案 • 数据总结 / 报告生成 prompt-optimizer-pro 让每一位 Claude 用户都能轻松拥有专业级提示词能力，实现真正的降本、提效、精准、省心。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: eric060/affiliate-marketing-optimizer (version 1.0.0)

# affiliate-marketing-optimizer ## Description Optimize affiliate marketing strategies. Improves commission rates, conversion, and compliance. ## Location `skills/affiliate-marketing-optimizer/` ## Capabilities - Product selection - Link optimization - Disclosure compliance - Conversion improvement - Tracking setup - Performance analysis ## Usage ```python python skills/affiliate-marketing-optimizer/optimize.py --platform "xiaohongshu" --niche "美妆" ``` ## Output - Product recommendations - Link strategies - Compliance checklist - Optimization tips


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: omactiengartelle/pet-to-human-generator (version 1.0.0)

--- name: pet-to-human-generator description: your dog, cat, or any pet into a realistic human portrait with AI. Pet-to-human generator, humanize your pet, dog as a person, cat as human, animal-to-person art, pet human version, pet portrait transformation, viral pet trend generator — turn your furry friend into their human alter ego via the Neta AI image generation API (free trial at neta.art/open). tools: Bash --- # Pet To Human Generator your dog, cat, or any pet into a realistic human portrait with AI. Pet-to-human generator, humanize your pet, dog as a person, cat as human, animal-to-person art, pet human version, pet portrait transformation, viral pet trend generator — turn your furry friend into their human alter ego. ## Token Requires a Neta API token (free trial at <https://www.neta.art/open/>). Pass it via the `--token` flag. ```bash node <script> "your prompt" --token YOUR_TOKEN ``` ## When to use Use when someone asks to generate or create pet to human ai generator images. ## Quick start ```bash node pettohumangenerator.js "your description here" --token YOUR_TOKEN ``` ## Options - `--size` — `portrait`, `landscape`, `square`, `tall` (default: `portrait`) - `--ref` — reference image UUID for style inheritance ## Install ```bash npx skills add omactiengartelle/pet-to-human-generator ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: alihmaou/ipwebcam (version 1.0.0)

--- name: sentinel description: Transform an Android phone with IP Webcam into an intelligent Edge AI security system with OpenClaw. metadata: {"clawdbot":{"emoji":"🛡️","requires":{"bins":["compare","curl","awk"]},"install":[{"id":"apt","kind":"apt","packages":["imagemagick"],"bins":["compare"],"label":"Install ImageMagick (apt)"}]}} --- # Security monitoring over IP Camera Android app Use the **Clawd Sentinel** pattern to turn any old Android smartphone into a sovereign, frugal, and intelligent motion detection system. ## Setup 1. **Android Side**: Install "IP Webcam" (by Pavel Khlebovich) and start the server. 2. **Connectivity**: Note the local IP (e.g., `192.168.1.100:8080`). 3. **OpenClaw Workspace**: - `bin/sentinel_ultra_frugal.sh`: The core logic for pixel comparison. - `bin/sentinel_runner.sh`: The background loop runner. ## Detailed API Interaction The IP Webcam server provides a REST-like API for full remote control. Base URL: `http://<IP>:8080/` ### Visual Captures - **Standard Snapshot**: `/shot.jpg` (Fastest, current frame) - **Autofocus Snapshot**: `/photoaf.jpg` (Triggers autofocus before capture, highest quality) - **Video Recording**: - Start: `/startvideo?name=alert_123` - Stop: `/stopvideo` - List recordings: `/list_videos` (returns JSON/HTML) - Download: `/v/<filename>.mp4` ### Camera Control & Settings - **Focus Distance**: `/settings/focus_distance?set=<0.0-10.0>` (0.0 is often Infinity) - **Torch (Flash)**: `/enabletorch` | `/disabletorch` - **Focus Mode**: `/settings/focusmode?set=<on|off|macro|infinity|fixed>` - **Scene Mode**: `/settings/scenemode?set=<auto|night|action|party...>` - **White Balance**: `/settings/whitebalance?set=<auto|daylight|cloudy...>` ### Device Telemetry - **Sensors Data**: `/sensors.json` (Battery, light level, proximity, accelerometer) - **System Status**: `/status.json` (Camera state, recording status, uptime) ### Audio - **Audio Feed**: `/audio.wav` or `/audio.opus` (Live audio stream) ### Integration Examples (curl) ```bash # Get battery level via jq curl -s http://<IP>:8080/sensors.json | jq '.battery_level[0][1][0]' # Toggle flash remotely curl http://<IP>:8080/enabletorch ``` ## Recommended Thresholds - **Daytime (Haze/Clouds)**: 2500 - **Nighttime (ISO noise)**: 1500 ## Notes - **Frugality**: No tokens are consumed unless the pixel differential exceeds the threshold. - **Privacy**: Raw frames remain local. Only alert-triggered frames are sent to the AI. - **Maintenance**: Periodically check phone battery and Wi-Fi stability. - **Lens flare**: Long rainbow flares in night mode usually indicate static lights, not vehicles.


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