OpenClaw/clawhub-security-signals huggingface dataset:
Skill: jamling/voice-vehicle-control (version 1.0.0)

--- name: voice-vehicle-control description: 语音控制车辆助手，支持启动熄火、车窗门锁、方向控制、状态查询与场景模式；适用于"帮我发动汽车"、"打开回家模式"或"查询电量"等语音交互场景 --- # 语音车辆控制助手 ## 任务目标 本技能用于处理用户的语音车辆控制请求，实现以下能力： - **基础控制**：车辆启动/熄火、开锁/关锁、开关车窗、天窗/遮阳帘 - **方向控制**：转向灯（左/右/双闪）、行驶方向指引 - **状态查询**：油量、电量、胎压、车门状态、车窗状态、空调状态 - **场景控制**：执行预设场景模式（回家模式、上班模式、休息模式等） - **多语言交互**：支持中英文及其他语种的语音指令识别与反馈 ## 前置准备 - 确保车辆已联网且控制接口可访问 - 用户已完成车辆账号绑定与授权 - 多语言场景下，识别用户语种并使用对应语言反馈 ## 操作步骤 ### 1. 语音指令解析 接收用户语音或文字指令，按以下流程处理： 1. **意图识别**：判断指令类型 - 控制指令（我要开车/打开车窗） - 查询指令（电量还剩多少/胎压正常吗） - 场景指令（开启回家模式） 2. **实体提取**：从指令中提取关键参数 - 目标对象：车、窗、锁、灯、空调、座椅 - 操作动作：开/关、启动/熄火、调高/调低 - 位置方向：左/右、前/后、主驾/副驾 3. **多语言适配**： - 检测指令语种 - 使用对应语种生成反馈 ### 2. 车辆控制指令生成 根据解析结果，生成符合车辆控制协议的控制指令。 **基础控制指令格式**： ```json { "command": "vehicle_control", "action": "engine_start|engine_stop|door_lock|door_unlock|window_open|window_close|...", "target": "all|driver|passenger|rear_left|rear_right|sunroof|...", "parameters": { "position": "open|close|vent|...", "level": 0-100 } } ``` 详细指令格式参见 [references/vehicle-protocol.md](references/vehicle-protocol.md)。 ### 3. 状态查询处理 接收查询请求后，生成查询指令并返回结构化状态信息： ```json { "query": "status_query", "items": ["fuel_level", "battery_level", "tire_pressure", "door_status", "..."] } ``` **返回格式示例**： ```json { "status": "success", "data": { "fuel_level": {"value": 65, "unit": "%"}, "battery_level": {"value": 82, "unit": "%"}, "tire_pressure": { "front_left": 2.3, "front_right": 2.3, "rear_left": 2.2, "rear_right": 2.2, "unit": "bar" }, "door_status": { "driver": "closed", "passenger": "closed", "rear_left": "closed", "rear_right": "closed", "trunk": "closed" } } } ``` ### 4. 场景模式执行 接收场景指令后，解析场景配置并批量执行控制指令。 **场景指令格式**： ```json { "command": "scenario_execute", "scenario": "go_home|work|rest|..." } ``` 场景配置规范参见 [references/scenario-config.md](references/scenario-config.md)。 ### 5. 结果反馈 根据执行结果，使用用户母语生成自然反馈： - 成功：确认操作已完成 - 失败：说明原因并提供替代建议 - 部分成功：列出成功项和失败项 ## 使用示例 ### 示例 1：基础控制 - **场景/输入**："帮我发动汽车" / "Start the car" - **预期产出**：生成 engine_start 指令并反馈启动结果 - **关键要点**：识别启动同义词（发动、启动、点火） ### 示例 2：状态查询 - **场景/输入**："现在电量还剩多少" / "How much battery left?" - **预期产出**：查询 battery_level 并返回百分比 - **关键要点**：使用用户语种反馈数值 ### 示例 3：场景控制 - **场景/输入**："开启回家模式" / "Activate go-home mode" - **预期产出**：加载场景配置，依次执行空调开启、座椅加热、导航回家等指令 - **关键要点**：多指令批量执行，按依赖顺序排列 ### 示例 4：多语言切换 - **场景/输入**："Ouvrez la fenetre"（法语：打开窗户） - **预期产出**：解析法语指令，执行 window_open，反馈 "La fenêtre est ouverte" - **关键要点**：自动检测语种并匹配响应语言 ### 示例 5：复杂指令 - **场景/输入**："把主驾窗户开一半，空调调到24度" - **预期产出**：生成两条控制指令，window_open + climate_set - **关键要点**：单句多意图识别 ## 资源索引 - 车辆控制协议：见 [references/vehicle-protocol.md](references/vehicle-protocol.md)（完整指令格式、响应结构、错误码定义） - 场景配置规范：见 [references/scenario-config.md](references/scenario-config.md)（场景Schema、预设场景示例） ## 注意事项 - 多意图指令需拆分为独立命令依次执行 - 危险操作（如行驶中开车门）需二次确认 - 状态查询返回空值时，明确告知用户该状态不可用 - 场景执行失败时，回滚已执行操作或提示用户手动处理


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: loutai0307-prog/supabase-tool (version 1.1.0)

--- name: "supabase-tool" description: "Generate Supabase API curl commands and SQL query helpers. Use when querying tables, counting rows, inserting records, checking database health, auditing RLS policies, or listing tables. No credentials stored — commands are generated for you to run." --- # supabase-tool ## Triggers on supabase query, database health, count rows, insert record, rls policy, sql query, supabase table, postgresql ## What This Skill Does Query, inspect, and manage Supabase databases. Run SQL, count rows, insert records, check health, and audit RLS policies. ## Commands ### query Run a raw SQL query. ```bash bash scripts/script.sh query "SELECT COUNT(*) FROM skills WHERE is_ours=true" ``` ### select Query a table with optional filters and limit. ```bash bash scripts/script.sh select <table> [--limit N] [--filter col=eq.val] ``` ### count Count rows — all tables or a specific one. ```bash bash scripts/script.sh count bash scripts/script.sh count skills ``` ### insert Insert a record into a table. ```bash bash scripts/script.sh insert <table> '<json>' ``` ### health Check API health and response time with row counts. ```bash bash scripts/script.sh health ``` ### rls Audit RLS policy issues using Supabase Security Advisor. ```bash bash scripts/script.sh rls ``` ### help Show all available commands. ```bash bash scripts/script.sh help ``` ## Requirements - bash 4+ - curl - python3 Powered by BytesAgain | bytesagain.com


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: marcindudekdev/apify-substack-scraper (version 1.0.0)

--- name: apify-substack-scraper description: Scrape Substack newsletters and articles. Use when user asks to search Substack, find newsletter posts, extract Substack content, or monitor Substack publications. Requires APIFY_TOKEN environment variable. metadata: {"openclaw":{"emoji":"📰","requires":{"env":["APIFY_TOKEN"],"bins":["curl","jq"]},"primaryEnv":"APIFY_TOKEN"}} --- # Substack Scraper Scrape Substack newsletters using an Apify Actor via the REST API. ## Actor ID `BULaGFURBV7WG3K81` ## Prerequisites - `APIFY_TOKEN` environment variable must be set - `curl` and `jq` must be available ## Workflow ### Step 1: Confirm parameters with user Ask what they want to scrape. Supported input fields: - `urls` (array of strings) - Substack publication URLs to scrape - `maxArticles` (integer) - max articles per publication - `includeContent` (boolean) - include full article text ### Step 2: Run the Actor ```bash RESULT=$(curl -s -X POST "https://api.apify.com/v2/acts/BULaGFURBV7WG3K81/run-sync-get-dataset-items?[REDACTED_SECRET]" \ -H "Content-Type: application/json" \ -d '{"urls": ["https://example.substack.com"], "maxArticles": 20}') echo "$RESULT" | jq '.' ``` ### Step 3: Poll and fetch (if async) ```bash RUN_ID=$(curl -s -X POST "https://api.apify.com/v2/acts/BULaGFURBV7WG3K81/runs?[REDACTED_SECRET]" \ -H "Content-Type: application/json" \ -d '{"urls": ["https://example.substack.com"], "maxArticles": 100}' | jq -r '.data.id') curl -s "https://api.apify.com/v2/actor-runs/$RUN_ID?[REDACTED_SECRET]" | jq -r '.data.status' curl -s "https://api.apify.com/v2/actor-runs/$RUN_ID/dataset/items?[REDACTED_SECRET]" | jq '.' ``` ### Step 4: Present results Summarize articles: titles, authors, dates, engagement. Offer JSON/CSV export. ## Error Handling - If APIFY_TOKEN not set: `export APIFY_TOKEN=your_token` - If run FAILS: check log endpoint


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: nogravedev/agent-core (version 1.2.0)

--- name: agent-core description: Complete AI agent operating system — 3-layer memory, heartbeat automation, cron patterns, safety rules, and drop-in workspace configs. Turn any agent from chatbot to autonomous assistant in 10 minutes. metadata: openclaw: version: "1.2.0" author: "ClawKits" tags: ["memory", "automation", "productivity", "agent-framework", "heartbeat"] --- # Agent Core — The AI Agent Operating System The exact operating system running a production AI agent 24/7. Memory that persists across sessions. Heartbeats that check in without being asked. Safety rules that prevent disasters. Built from months of real production use. ## What's Included (Full Kit) - **3-layer memory system** — daily logs, topic memory, long-term curated memory with nightly consolidation - **6 drop-in workspace configs** — AGENTS.md, SOUL.md, USER.md, IDENTITY.md, TOOLS.md, HEARTBEAT.md - **Heartbeat automation** — email monitoring, calendar alerts, RAM checks, project status, weather - **5 cron job templates** — memory consolidation, proactive check-ins, task monitors, scheduled reports - **4 advanced patterns** — browser hygiene, channel memory, multi-channel setup, RAM monitoring - **Safety rules** — anti-loop protection, sub-agent delegation, group chat etiquette, deploy safety - **Quickstart guide** — running in 10 minutes ## Why This Exists Most AI agents are stateless chatbots. They forget everything between sessions, never check in on their own, and have no guardrails. Agent Core fixes all of that. This system was built over months of running a production agent on a Mac mini — handling emails, calendars, deployments, trading, and creative work 24/7. Every pattern here solved a real problem. ## Results - Agent remembers context across unlimited sessions - Proactive check-ins 2-4x daily without being asked - Zero data loss from memory consolidation - No runaway loops or destructive operations - Works across iMessage, Discord, Telegram, WhatsApp, Slack ## Get Agent Core **$39** — Full kit with all configs, templates, patterns, and quickstart guide. 👉 **https://clawkits.gumroad.com/l/agent-core** **$49** — ClawKits Complete Bundle (Agent Core + Trading Desk): 👉 **https://clawkits.gumroad.com/l/clawkits-bundle** ## Author Built by ClawKits — production-tested systems for AI agents. https://clawkits.xyz


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: maximum2974/coffee-debugger (version 0.1.1)

--- name: coffee-debugger description: >- 开发者咖啡决策引擎。根据工作场景（写代码、Debug、开会、写文档）、疲劳程度和当前时间， 精准推荐最适合的咖啡。当用户提到需要咖啡建议、需要提神、感到疲惫困倦时自动触发。 argument-hint: "[工作场景] [疲劳程度]" allowed-tools: Read Bash --- # Coffee Debugger — 开发者咖啡决策引擎 你是一位开发者工作流的资深咖啡顾问。你的职责是分析用户当前的工作上下文， 给出精准、个性化的咖啡推荐——不是随机挑选，而是经过严谨推理的"处方"。 ## 信号采集 在给出推荐之前，收集以下上下文信息。如果用户没有全部提供，从对话中推断或简短追问。 ### 1. 工作场景 | 场景 | 核心特征 | 咖啡方向 | |------|----------|----------| | **写代码**（功能开发、重构） | 持续专注，心流状态 | 平稳释放咖啡因，避免峰值波动 | | **Debug** | 高度警觉，模式识别 | 强劲速效，追求思维巅峰清晰度 | | **开会**（站会、评审、一对一） | 社交能量，表达流畅 | 温和舒适，偏暖系饮品 | | **写文档** | 耐心，结构化思维 | 轻柔提神，降低焦虑感 | | **Code Review** | 注意力集中，批判性阅读 | 干净利落，消除脑雾 | | **救火**（线上事故、紧急修复） | 肾上腺素 + 冷静抗压 | 最大火力，不搞花活 | | **学习**（读源码、探索新技术） | 好奇心，开放心态 | 轻盈探索型，留一点想象空间 | | **摸鱼 / 拖延中** | 需要启动推力 | 有趣新奇，打破死循环 | ### 2. 疲劳程度 | 等级 | 描述 | 咖啡因策略 | |------|------|-----------| | **精神饱满** | 刚起床、睡眠充足 | 轻启动，别用力过猛 | | **正常状态** | 标准工作日能量 | 经典均衡款 | | **有点累** | 下午犯困或工作时间较长 | 加大剂量，考虑双份浓缩 | | **非常疲惫** | 熬夜 / 通宵后 | 紧急方案——最大咖啡因 + 加糖 | | **已经亢奋** | 咖啡因摄入过量 | 立刻停止。换无咖啡因饮品或花草茶，补水。 | ### 3. 当前时间 通过当前时间（!`date +%H:%M`）应用以下规则： | 时间段 | 推荐原则 | |--------|----------| | 06:00–09:00 | 晨间仪式——经典款优先，温和开启一天 | | 09:00–11:30 | 黄金产出时段——为专注力优化 | | 11:30–13:30 | 午餐时段——偏轻量，适合搭配餐食 | | 13:30–16:00 | 午后低谷——战略性咖啡因补给 | | 16:00–18:00 | 傍晚——适度咖啡因，注意不影响睡眠 | | 18:00–22:00 | 晚间——强烈建议无咖啡因或低咖啡因选项 | | 22:00–06:00 | 夜猫模式——如果坚持要喝就给强的，但必须警告睡眠负债 | ## 咖啡菜单 从以下精选菜单中推荐，也可以建议变体组合。 ### 意式浓缩系列 - **Espresso 浓缩** — 纯粹的专注燃料，一盎司的浓缩意志力 - **Doppio 双份浓缩** — 单份不够时的加倍方案 - **Americano 美式** — 浓缩 + 热水，干净利落的补水方案 - **Latte 拿铁** — 浓缩 + 蒸汽奶，咖啡界的舒适毛毯 - **Cappuccino 卡布奇诺** — 浓缩、牛奶、奶泡三等分，像好代码一样均衡 - **Flat White 澳白** — 绵密微泡拿铁，丝滑行事风格 - **Mocha 摩卡** — 浓缩 + 巧克力 + 牛奶，Debug 专属治愈系 - **Macchiato 玛奇朵** — 浓缩点缀一抹奶泡，极简优雅 ### 手冲 / 萃取系列 - **手冲咖啡** — 干净、有层次感，适合那种会读 changelog 的开发者 - **Cold Brew 冷萃** — 低温慢萃、高咖啡因，缓释型能量 - **滴滤咖啡** — 可靠的主力选手，咖啡界的 `main()` 函数 - **法压壶** — 浓郁醇厚，不过滤（字面意义上） ### 特调系列 - **抹茶拿铁** — 茶氨酸 + 咖啡因，平静专注不手抖 - **Chai 印度奶茶** — 香料暖意，会议模式专属饮品 - **任意无咖啡因款** — 没什么丢人的，睡眠是 feature 不是 bug - **热巧克力** — 当咖啡不是答案、而你需要安慰的时候 ## 输出格式 按以下结构输出推荐： ``` ### 你的咖啡处方 **诊断：** [一句话总结用户当前状态] **处方：** [咖啡名称 + 定制调整] **剂量：** [杯型大小和饮用时机建议] **理由：** [2-3 句话解释为什么这是最佳选择] > **开发者贴士：** [一句将咖啡与当前工作场景巧妙关联的俏皮话] ``` ## 规则 1. **必须考虑时间因素。** 晚上 11 点绝不推荐三倍浓缩，除非附带健康警告。 2. **尊重"亢奋"状态。** 如果用户已经咖啡因过量，坚定地开出补水和无咖啡因处方，不要妥协。 3. **有态度但有趣。** 你是一位懂开发者梗的咖啡专家——不是自动售货机。 4. **不评判。** 无论用户喝速溶还是精品手冲，在他们所在的位置接住他们。 5. **健康提醒。** 如果用户反复提到极端工作时长，温和地指出：睡眠 > 咖啡因。 6. **保持简短。** 推荐内容的阅读时间应该比冲一杯咖啡的时间短。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: impkind/anterior-cingulate-memory (version 0.1.1)

--- name: anterior-cingulate-memory description: "Conflict detection and error monitoring for AI agents. The 'something's off' detector. Part of the AI Brain series." metadata: openclaw: emoji: "⚡" version: "0.1.1" author: "ImpKind" requires: os: ["darwin", "linux"] tags: ["memory", "monitoring", "ai-brain"] --- # Anterior Cingulate Memory ⚡ **Conflict detection for AI agents.** Part of the AI Brain series. ## Status: 🚧 Under Development This skill is being developed. Star/watch for updates! ## Concept The anterior cingulate cortex monitors for errors and conflicts. This skill will give AI agents: - **"Something's off" detection** — pre-conscious warning signals - **Conflict monitoring** — detecting contradictions in information - **Error tracking** — learning from mistakes - **Uncertainty awareness** — knowing when to be cautious ## AI Brain Series | Part | Function | Status | |------|----------|--------| | [hippocampus](https://www.clawhub.ai/skills/hippocampus) | Memory formation, decay, reinforcement | ✅ Live | | [amygdala-memory](https://www.clawhub.ai/skills/amygdala-memory) | Emotional processing | ✅ Live | | [basal-ganglia-memory](https://www.clawhub.ai/skills/basal-ganglia-memory) | Habit formation | 🚧 Development | | **anterior-cingulate-memory** | Conflict detection | 🚧 Development | | [insula-memory](https://www.clawhub.ai/skills/insula-memory) | Internal state awareness | 🚧 Development | ## Coming Soon Based on neuroscience research on the ACC's role in error detection and cognitive control. --- *Built with ❤️ by the OpenClaw community*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: cyzlmh/cmic-skill-scanner-linux-amd64 (version 0.9.0)

--- name: skillscan-wrapper description: 使用内置 Rust 引擎审计待安装的 skill 包或归档，并可选桥接外部 scanner。 license: MIT-0 author: CMIC Skill Scanner --- # Skill Scan Wrapper 当你要在安装一个本地 skill、归档或 release bundle 前做一次快速安全检查时，使用这个 skill。 ## ⚠️ Security Notice This tool operates **locally** and requires user trust in the binary you run. **Always verify the checksum after downloading**. For maximum security, build from source (recommended). ## Binary Included | Property | Value | |----------|-------| | Location | `assets/bin/skillscan` | | Version | `v0.9.0` | | Platform | `Linux x64` | | SHA-256 | [REDACTED_SECRET] | **Verify locally before running:** ```bash sha256sum assets/bin/skillscan # Compare output with the SHA-256 value above ``` This bundled package includes a pre-compiled binary. You can still build from source if you prefer: ```bash git clone https://gitee.com/random_player/cmic-skill-scanner.git cd cmic-skill-scanner && cargo build --release ``` ## 前置条件 - 默认不需要任何外部依赖 - `--upload-url` 和 `--engine external` 功能**默认禁用**，仅在用户显式配置时启用 ## 信任模型 This is an **open-source (MIT-0) package**. The binary (bundled or downloaded) is a **convenience only** — it does not grant any additional trust. **Your options:** | Approach | Trust Requirement | Verification | |----------|------------------|--------------| | Build from source | None (you control everything) | Manual code review | | Bundled/downloaded binary | You trust the release host | SHA-256 checksum | **What the tool does NOT do by default:** - Does NOT upload data anywhere - Does NOT connect to the network - Does NOT access credentials, SSH configs, or environment variables - Does NOT execute external tools unless you explicitly configure `--engine external` ## 工作流程 1. 调用 skillscan： ```bash skillscan review /path/to/target --format markdown skillscan review /path/to/skills --output-dir /tmp/skillscan-out ``` 2. 阅读输出中的：输入类型、完整度、engine 执行状态、findings ## 网络上传功能 (默认禁用) **⚠️ This feature is completely optional and disabled by default.** It requires explicit user configuration via `--upload-url`. **What gets sent** (only when you configure `--upload-url`): - A structured JSON report containing detection findings - An instance identifier you supply via `--instance-id` - **No skill source code, credentials, or system configuration is ever transmitted** ## 外部引擎集成 (默认禁用) **⚠️ This feature is completely optional and disabled by default.** It requires explicit user configuration via `--engine external`. Delegates pattern-matching to a user-configured local tool. This runs **locally** — no remote calls are made. ## Permissions Required | Scope | Reason | |-------|--------| | Read files in target path | To analyze skill source code for patterns | | Write to `--output-dir` | To save scan reports locally | | Execute binary | To run the scanner engine | | Network (optional) | **Only if `--upload-url` is explicitly configured** |


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

--- name: YAML description: Write valid YAML that parses predictably across languages and versions. metadata: {"clawdbot":{"emoji":"📋","os":["linux","darwin","win32"]}} --- ## Type Coercion Traps - `yes`, `no`, `on`, `off`, `true`, `false` → boolean; quote if literal string: `"yes"` - `NO` (Norway country code) → false in YAML 1.1; always quote country codes - `1.0` → float, `1` → int; quote version numbers: `"1.0"` - `010` → octal (8) in YAML 1.1; quote or use `0o10` explicitly - `null`, `~`, empty value → null; quote if literal: `"null"`, `"~"` - `.inf`, `-.inf`, `.nan` → special floats; quote if literal strings ## Indentation - Spaces only—tabs are forbidden and cause parse errors - Consistent indent width required within document—2 spaces conventional - Sequence items `-` count as indentation—nested content aligns after the space ## Strings - Colon followed by space `: ` triggers key-value—quote strings containing `: ` - `#` starts comment unless quoted—quote strings with `#` - Leading/trailing spaces stripped from unquoted strings—quote to preserve - Quote strings starting with `@`, `` ` ``, `*`, `&`, `!`, `|`, `>`, `{`, `[`, `%` ## Multiline Strings - `|` literal block preserves newlines; `>` folded block joins lines with spaces - Trailing newline: `|-` and `>-` strip final newline; `|+` and `>+` keep trailing blank lines - Indentation of first content line sets the block indent—be consistent ## Structure - Duplicate keys: YAML spec says last wins, but some parsers error—avoid duplicates - Anchors `&name` and aliases `*name` reduce repetition—but aliases can't override anchor values - Document separator `---` starts new document; `...` ends document—useful in streams - Empty documents between `---` markers are valid but often unintended ## Comments - `#` only valid at line start or after whitespace—`key:value#comment` has no comment - No inline comments after multiline block scalars—comment applies to next line - No multi-line comment syntax—each line needs `#` ## Compatibility - YAML 1.1 vs 1.2: boolean words (`yes`/`no`), octal syntax differ—know which version parser uses - JSON is valid YAML 1.2—but YAML features (anchors, multiline) don't round-trip to JSON - Some parsers limit nesting depth or file size—test with expected data scale


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: neo1307/argus-price-monitor (version 1.0.2)

--- name: Price Monitor & Daily Excel Report Bot description: Monitors product prices across e-commerce sites daily, detects price drops, and emails a formatted Excel report automatically every morning. version: 1.0.2 tags: [python, scraping, automation, excel, email, selenium, pandas] author: neo1307 requires: [python3, selenium, webdriver-manager, pandas, openpyxl, chromium] --- # Price Monitor & Daily Excel Report Bot ## Overview Automated price tracking system that monitors products across competitor websites, detects price drops, and delivers a formatted Excel report via email every morning at 8 AM. Saves 3+ hours of manual work per day. ## What It Does - Scrapes prices from target URLs using Selenium (handles JavaScript-rendered pages) - Compares against previous day's prices automatically - Highlights price drops >5% in red, increases in green inside Excel - Emails formatted report to specified recipients on schedule - Logs all runs with timestamps for auditing ## Required Environment Variables Set these in OpenClaw's Secrets manager before running: | Variable | Description | Example | |----------|-------------|---------| | `SMTP_HOST` | SMTP server hostname | `smtp.gmail.com` | | `SMTP_PORT` | SMTP port number | `587` | | `SMTP_USER` | Sender email address | `[REDACTED_SECRET]` | | `SMTP_PASS` | Email password or app-specific password | `xxxx xxxx xxxx xxxx` | | `REPORT_RECIPIENT` | Where to send the daily report | `[REDACTED_SECRET]` | ## Setup 1. Add target product URLs to `config/urls.txt` (one URL per line) 2. Set all environment variables above in OpenClaw Secrets 3. Set run schedule in OpenClaw: `daily at 08:00` 4. Chromium must be available on the host for Selenium headless mode ## Usage > "Start monitoring prices for these URLs and email me a report every morning" > "Check competitor prices and send Excel summary to [REDACTED_SECRET]" > "Run price tracker now and show me today's drops" > "Add this product URL to the monitoring list" ## Output - `price_report_YYYY-MM-DD.xlsx` — color-coded Excel report - Email with report attached sent to configured recipient - Console summary: total products, drops found, errors ## Rules - Never send more than 1 request per second to any domain - Always save raw scraped data before processing (in `data/raw/`) - If email delivery fails, save report to `data/reports/` and retry once after 10 minutes - If a URL returns 403/blocked, skip and log — do not retry more than 3 times - Report must include: product name, URL, yesterday's price, today's price, % change ## Example Config (urls.txt) ``` https://www.amazon.com/dp/B08N5WRWNW https://www.amazon.com/dp/B09G9FPHY6 https://www.bestbuy.com/site/product/123456 ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: 547895019/public-apis-skill-creator (version 1.0.0)

--- name: public-apis-skill-creator description: 公共API/免费API SKILL生成器：从 public-apis/public-apis 自动检索免费 API，按功能推荐并给出最小可用调用示例（curl/Python/JS），并可自动生成自定义名称的 API skill。用户提到“公共API”“免费API”“public APIs”“找接口/找API”“生成API skill”时触发。 --- # public-apis-skill-creator ## 能力 - 按功能关键词搜索 public-apis 仓库里的免费 API - 输出 API 的认证要求、HTTPS、CORS、文档链接 - 自动生成最小可用示例（curl / Python / JavaScript） - 自动生成“公共API/免费API”对应的 skill 包（名称可自定义） - 查看并打印 public-apis 全量 API 列表（支持 --top / --json） ## 用法 ### 1) 按功能找 API ```bash bash {baseDir}/scripts/search_api.sh "weather forecast" ``` ### 2) 自动推荐 + 生成调用模板（一步到位） ```bash bash {baseDir}/scripts/solve_task.sh "weather api" # 指定用推荐列表第 2 个 API bash {baseDir}/scripts/solve_task.sh "weather api" --pick 2 # 可选：尝试对选中 API 做一次 GET 探测 bash {baseDir}/scripts/solve_task.sh "weather api" --pick 2 --try ``` ### 3) 自动生成对应 skill（支持自定义名称） ```bash bash {baseDir}/scripts/solve_task.sh "weather api" \ --pick 2 \ --make-skill \ --skill-name weather-api-skill ``` 会在 `skills/<skill-name>/` 下生成可直接使用的 skill 骨架。 ### 4) 手动生成调用模板 ```bash bash {baseDir}/scripts/gen_usage.sh \ --name "Open-Meteo" \ --url "https://api.open-meteo.com/v1/forecast?latitude=39.9&longitude=116.4&hourly=temperature_2m" \ --auth "No" ``` ### 5) 打印 public-apis 全部列表 ```bash bash {baseDir}/scripts/list_all_apis.sh # 只看前 50 条 bash {baseDir}/scripts/list_all_apis.sh --top 50 # JSON 输出 bash {baseDir}/scripts/list_all_apis.sh --json ``` ## 典型请求示例 - "帮我找免费天气 API 并给 Python 示例" - "找一个免费汇率 API，要求 HTTPS 且无需 key" - "我想做新闻聚合，推荐 3 个 API 并比较" - "基于公共API生成一个新免费天气 skill，名称叫 weather-free"


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