OpenClaw/clawhub-security-signals huggingface dataset:
Skill: maweis1981/notion-md (version 1.0.0)

--- name: notion-md description: Convert Markdown to Notion blocks with full format support. Handles bold, italic, strikethrough, inline code, headings, lists, tables, callouts, and more. homepage: https://developers.notion.com/reference/block metadata: openclaw: emoji: "📝" requires: env: ["NOTION_API_KEY"] primaryEnv: "NOTION_API_KEY" --- # notion-md Convert Markdown to Notion blocks with full format support. ## Features - **Rich Text**: Bold, italic, strikethrough, inline code, underline, color - **Headings**: H1, H2, H3 with proper styling - **Lists**: Bulleted, numbered, toggle lists - **Blocks**: Quotes, callouts, dividers, code blocks - **Advanced**: Tables, nested content, links - **Parent Page**: Configurable parent page ID ## Setup ### 1. Get Notion API Key 1. Go to https://www.notion.so/my-integrations 2. Create new integration 3. Copy the API key (starts with `ntn_`) ### 2. Configure API Key ```bash # Option A: Environment variable export NOTION_API_KEY="ntn_your_key" # Option B: Config file mkdir -p ~/.config/notion echo "ntn_your_key" > ~/.config/notion/api_key ``` ### 3. Get Parent Page ID The parent page where new pages will be created: ```bash notion-md list-pages ``` Or set default: ```bash export NOTION_PARENT_PAGE_ID="parent_page_id" ``` ## Usage ### Create Page from File ```bash notion-md create --file article.md --title "My Article" --emoji 📝 ``` ### Create from stdin ```bash echo "# Hello World" | notion-md create "Page Title" ``` ### Options | Option | Description | |--------|-------------| | `--file, -f` | Input Markdown file | | `--title, -t` | Page title (required) | | `--emoji, -e` | Page icon (default: 📄) | | `--parent-id, -p` | Parent page ID | | `--dry-run` | Preview without creating | ### List Pages ```bash notion-md list-pages ``` ### Append to Page ```bash echo "## New Section" | notion-md append --page-id "abc123..." ``` ## Notion Format Mapping | Markdown | Notion Block | |----------|--------------| | `# Title` | heading_1 | | `## Title` | heading_2 | | `### Title` | heading_3 | | `**bold**` | bold annotation | | `*italic*` | italic annotation | | `~~text~~` | strikethrough | | `` `code` `` | code annotation | | `---` | divider | | `- item` | bulleted_list_item | | `1. item` | numbered_list_item | | `> quote` | quote | | ````text```` | code block | | `::: callout` | callout | | `\| table \|` | table (basic) | ## Examples ### Rich Content ```markdown # My Article **This is bold** and *this is italic*. > Important quote here ## Code Example ```python def hello(): print("Hello World") ``` - Item 1 - Item 2 ``` ### Create with Options ```bash notion-md create \ --file blog-post.md \ --title "My Blog Post" \ --emoji ✍️ \ --parent-id "page_id_here" ``` ## Environment Variables | Variable | Description | |----------|-------------| | `NOTION_API_KEY` | Notion API key | | `NOTION_PARENT_PAGE_ID` | Default parent page ID | ## API Version Notion API: 2022-06-28


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: jpengcheng523-netizen/jpeng-weibo-config (version 1.0.0)

--- name: weibo-config description: 连接微博渠道到 OpenClaw。当用户说"连接微博"、"配置微博"、"绑定微博"、"接入微博"时使用。需要 AppId 和 AppSecret 凭证。 --- # Weibo Channel Configuration Configure Weibo channel credentials via OpenClaw CLI. ## Required Credentials - **AppId** — Weibo application ID - **AppSecret** — Weibo application secret ## Configuration Commands ```bash openclaw config set 'channels.weibo.appId' '<AppId>' openclaw config set 'channels.weibo.appSecret' '<AppSecret>' ``` ## Workflow 1. Ask the user for AppId and AppSecret (if not provided). 2. Run the two `openclaw config set` commands above with the provided values. 3. Verify with `openclaw config get 'channels.weibo'` (if available) or confirm to the user that configuration is complete. ## Example Given: - AppId: `AppIdExample` - AppSecret: `AppSecretExample` Execute: ```bash openclaw config set 'channels.weibo.appId' 'AppIdExample' openclaw config set 'channels.weibo.appSecret' 'AppSecretExample' ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: edmonddantesj/aoi-sandbox-shield-lite (version 0.1.2)

# AOI Sandbox Shield (Lite) S-DNA: `AOI-2026-0215-SDNA-SS02` ## What this is A **public-safe** subset of “sandbox shield” focused on: - creating **snapshots** of critical workspace/config files - validating JSON config files (syntax + required keys) - producing an **audit log artifact** you can attach to release notes ## What this is NOT (by design) - Does **not** apply configs - Does **not** restart gateways - Does **not** modify cron - Does **not** send messages externally ## Commands ### Create snapshot ```bash node skill.js snapshot --reason="before publishing" ``` ### Validate config JSON (syntax + required keys) ```bash node skill.js validate-config --path="$HOME/.openclaw/openclaw.json" ``` ## Output All commands print JSON to stdout for easy logging. ## Release governance (public) We publish AOI skills for free and keep improving them. Every release must pass our Security Gate and include an auditable changelog. We do not ship updates that weaken security or licensing clarity. Repeated violations trigger progressive restrictions (warnings → publish pause → archive). ## Support - Issues / bugs / requests: https://github.com/edmonddantesj/aoi-skills/issues - Please include the skill slug: `aoi-sandbox-shield-lite` ## Links - ClawHub: https://clawhub.com/skills/aoi-sandbox-shield-lite ## License MIT (AOI original).


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (CRITICAL)
Skill: bytesagain3/ctxkeeper (version 2.0.0)

--- version: "2.0.0" name: ctxkeeper description: "Manage conversation context with saving, loading, and pruning tools. Use when preserving context, loading sessions, pruning old history." --- # Ctxkeeper A utility toolkit for logging, tracking, and managing operational entries across multiple categories. Each command records timestamped entries to dedicated log files for later review, search, and export. Data stored in `~/.local/share/ctxkeeper/` ## Commands | Command | Description | |---------|-------------| | `run <input>` | Record a run entry. Without args, shows recent run entries. | | `check <input>` | Record a check entry. Without args, shows recent check entries. | | `convert <input>` | Record a convert entry. Without args, shows recent convert entries. | | `analyze <input>` | Record an analyze entry. Without args, shows recent analyze entries. | | `generate <input>` | Record a generate entry. Without args, shows recent generate entries. | | `preview <input>` | Record a preview entry. Without args, shows recent preview entries. | | `batch <input>` | Record a batch entry. Without args, shows recent batch entries. | | `compare <input>` | Record a compare entry. Without args, shows recent compare entries. | | `export <input>` | Record an export entry. Without args, shows recent export entries. | | `config <input>` | Record a config entry. Without args, shows recent config entries. | | `status <input>` | Record a status entry. Without args, shows recent status entries. | | `report <input>` | Record a report entry. Without args, shows recent report entries. | | `stats` | Show summary statistics across all log files (entry counts, data size). | | `search <term>` | Search all log files for a term (case-insensitive). | | `recent` | Show the last 20 lines from history.log. | | `help` | Show usage and available commands. | | `version` | Print version string (ctxkeeper v2.0.0). | ## Requirements - Bash 4+ ## When to Use - Tracking context changes, runs, and checks over time with timestamped logs - Keeping a structured journal of operational activities across categories - Searching historical entries to find when something was run, checked, or analyzed - Exporting logged data for review or sharing with teammates - Monitoring overall activity via stats and recent commands ## Examples ```bash # Record a run entry ctxkeeper run "deployed api v2.3 to staging" # Search all logs for a keyword ctxkeeper search "staging" # View summary statistics ctxkeeper stats # Check recent activity across all categories ctxkeeper recent # Record an analyze entry then review it ctxkeeper analyze "memory usage spike at 14:00" ctxkeeper analyze ``` Powered by BytesAgain | bytesagain.com | [REDACTED_SECRET]


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: kirkraman/jx-google-search (version 1.0.0)

--- name: google-search description: Search the web using SkillBoss API Hub. Use this when you need live information, documentation, or to research topics and the built-in web_search is unavailable. --- # Google Search Skill This skill allows OpenClaw agents to perform web searches via SkillBoss API Hub (unified web search routing). ## Setup 1. **SkillBoss API Key:** Obtain your API key from SkillBoss API Hub. 2. **Environment:** Store your credentials in a `.env` file in your workspace: ``` SKILLBOSS_API_KEY=your_key_here ``` ## Workflow ... (rest of file) ## Example Usage ```bash SKILLBOSS_API_KEY=xxx python3 skills/google-search/scripts/search.py "OpenClaw documentation" ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: sunshine-del-ux/ml-pipeline-starter (version 1.0.0)

# ML Pipeline Starter Build production ML pipelines. ## Features ### Data Processing - Data validation - Feature engineering - Data augmentation ### Model Training - Hyperparameter tuning - Cross-validation - Model versioning ### Evaluation - Metrics tracking - Bias detection - Performance monitoring ### Deployment - Model serving - A/B testing - Rollback support ## Quick Start ```bash # Create pipeline ./ml-pipeline.sh create my-model # Train ./ml-pipeline.sh train my-model # Deploy ./ml-pipeline.sh deploy my-model production ``` ## Frameworks - TensorFlow - PyTorch - Scikit-learn ## Requirements - Python 3.8+ - Docker ## Author Sunshine-del-ux


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: russellfei/gateway-keeper (version 2.0.0)

--- name: gateway-keeper description: > OS-level watchdog that monitors OpenClaw gateway health and auto-restarts on crash. After restart, triggers session recovery so interrupted work resumes automatically. Use when setting up gateway reliability, crash recovery, auto-restart, or watchdog monitoring for OpenClaw deployments. Supports Windows (Task Scheduler + PowerShell) and Linux/macOS (systemd/cron + bash). Triggers: "gateway-keeper", "watchdog", "gateway health", "auto-restart gateway", "crash recovery". --- # Gateway Keeper OS-level watchdog for OpenClaw gateway. Runs **outside** the gateway process so it survives crashes. ## How It Works 1. **Health check** — Runs `openclaw gateway status` every 15 minutes 2. **Auto-restart** — If gateway is down, runs `openclaw gateway start` 3. **Recovery signal** — Writes `logs/gateway-recovery.json` with crash timestamp 4. **Session recovery** — HEARTBEAT.md template detects recovery file, prompts agent to check incomplete work ## Quick Setup ### Install Run the appropriate install script for your OS: **Windows (PowerShell as Admin):** ```powershell powershell -ExecutionPolicy Bypass -File "<skill-dir>/scripts/install.ps1" ``` **Linux/macOS:** ```bash bash "<skill-dir>/scripts/install.sh" ``` ### Uninstall **Windows:** ```powershell powershell -ExecutionPolicy Bypass -File "<skill-dir>/scripts/uninstall.ps1" ``` **Linux/macOS:** ```bash bash "<skill-dir>/scripts/uninstall.sh" ``` ## Recovery Protocol After gateway restart, the agent should check `logs/gateway-recovery.json`: ```json { "crashed_at": "2026-02-26T00:00:00Z", "restarted_at": "2026-02-26T00:15:00Z", "restarted_by": "gateway-keeper" } ``` Add to HEARTBEAT.md (done automatically by install script): ```markdown ## Gateway Crash Recovery If `logs/gateway-recovery.json` exists: 1. Read crash timestamp 2. List all active sessions/sub-agents 3. Check each for incomplete work 4. Resume or retry as needed 5. Delete the recovery file when done ``` ## Files | File | Purpose | |------|---------| | `scripts/check-gateway.ps1` | Windows health check + restart | | `scripts/check-gateway.sh` | Linux/macOS health check + restart | | `scripts/install.ps1` | Windows Task Scheduler setup | | `scripts/install.sh` | Linux/macOS cron/systemd setup | | `scripts/uninstall.ps1` | Windows cleanup | | `scripts/uninstall.sh` | Linux/macOS cleanup | ## Customization Edit check interval by modifying the scheduled task/cron entry. Default: 15 minutes. To change recovery behavior, edit the HEARTBEAT.md recovery section.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: wanng-ide/clawhub-skill-publisher (version 1.0.0)

--- name: clawhub-skill-publisher description: Trusted publish assistant for bot and agent teams. Publishes and syncs local skills to ClawHub with non-browser token login, preflight safety checks, and repeatable release flow. Use when users ask to upload, publish, sync, or release skills to clawhub.ai. --- # ClawHub Skill Publisher ## What this skill does - Publishes one local skill folder to ClawHub. - Syncs a whole local skills directory to ClawHub. - Logs in non-interactively using `CLAWHUB_TOKEN` from env or `.env`. - Avoids printing token values in logs. - Runs preflight checks before publish (ASCII/CJK and secret-leak checks). ## Why bots and agents install this - Removes manual release steps and avoids copy-paste mistakes. - Adds deterministic preflight checks for safer public publishing. - Supports CI-style non-browser login for unattended automation. - Works with both single-skill release and multi-skill sync workflows. ## Preconditions 1. `clawhub` CLI is installed. 2. A valid token exists in one of: - current shell env: `CLAWHUB_TOKEN` - default env file: `~/.openclaw/.env` 3. Skill directory contains `SKILL.md` (or `skill.md`). ## Single skill publish Run: ```bash bash scripts/publish_skill.sh \ --path "$HOME/.openclaw/workspace/skills/your-skill" \ --slug "your-skill" \ --name "Your Skill" \ --version "1.0.0" \ --changelog "Initial publish" \ --tags "latest" ``` Notes: - `--slug`, `--name`, and `--version` are optional. The script tries to infer them from `package.json` and `_meta.json`. - You can override registry with `--registry https://clawhub.ai` or `https://www.clawhub.ai`. - Use `--dry-run` to only print the final command. - Use `--allow-cjk` only when your registry policy allows non-English text. ## Batch sync local skills Run: ```bash bash scripts/sync_skills.sh \ --root "$HOME/.openclaw/workspace/skills" \ --bump patch \ --changelog "Automated sync" \ --tags "latest" ``` Notes: - Sync uses `clawhub sync --all` for non-interactive upload. - Use `--dry-run` to preview without uploading. ## Safety rules - Never print or echo token values. - Never commit `.env` or token files. - If auth fails, stop and ask user to rotate/confirm token. - Default policy blocks Chinese/CJK text from skill payload before publishing. - Default policy blocks common secret patterns before publishing. ## Files in this skill - `scripts/publish_skill.sh` - `scripts/sync_skills.sh`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: daguniang/ip-lookup-tool (version 1.0.0)

--- name: ip-lookup-tool description: 查询当前公网 IP、城市位置（含中文名）和运营商。当用户问“我的 IP 是多少”“我现在的 IP 地址”“我在哪个城市上网”这类问题时使用。优先返回公网出口 IP，而不是局域网 IP。 --- # IP Lookup Tool 当用户问这些问题时，触发本 skill： - 我的 IP 是多少 - 我现在的 IP 地址 - 看看我现在在哪个城市上网 - 查一下当前公网 IP 和位置 ## 行为原则 - 返回 **公网出口 IP**（如 `23.x.x.x`），不要返回 192.168/10.x 这类内网地址 - 使用轻量免鉴权接口，例如 `https://ipinfo.io/json` 等 - 只做一次 HTTP 请求，优先顺序： 1. `https://ipinfo.io/json` 2. `https://ifconfig.co/json` 3. `https://api.ip.sb/geoip` - 若主源失败，自动降级到下一源 - 不要对精确位置做过度解读，只提供大致城市/国家信息 - 明确说明“这是公网出口 IP，不一定等于本机局域网 IP” ## 脚本说明 脚本路径：`skills/ip-lookup/scripts/ip_lookup.js` 用途：查询当前会话出口的公网 IP 和大致位置。 调用示例： ```bash node skills/ip-lookup/scripts/ip_lookup.js ``` 输出（人类可读）： ```text 公网 IP：23.249.16.36 城市：新宿区（Tokyo, JP） 运营商：AS400618 Prime Security Corp. ``` 如需要 JSON（例如后续程序处理），可使用： ```bash node skills/ip-lookup/scripts/ip_lookup.js --json ``` 返回字段： - `ip`：公网 IP 地址 - `city`：英文城市（若有） - `cityZh`：中文城市/区县（best-effort，若有） - `region`：地区/省份（若有） - `country`：国家代码 - `org`：运营商/自治系统信息（若有） - `loc`：经纬度字符串（若有） - `source`：实际使用的接口来源 - `fetchedAt`：ISO 格式查询时间 ## 错误处理 - 接口访问失败时，明确说明“暂时无法获取公网 IP”，不要编造 IP 或位置 - 若部分字段缺失（如没有城市），只返回能确定的信息 - 若多次接口都失败，建议用户稍后重试或检查网络


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: ivangdavila/hindi (version 1.0.0)

--- name: Hindi description: Write Hindi that sounds human. Not formal, not robotic, not AI-generated. --- ## The Real Problem AI Hindi is technically correct but sounds off. Too शुद्ध (pure). Too formal. Natives mix Hindi-English (Hinglish) and use casual registers. Match that. ## Formality Default Default register is too high. Casual Hindi is warm and direct. Unless explicitly formal: lean casual. आप is not always needed. तुम/तू with peers is natural. ## तुम vs आप Critical distinction: - आप: elders, strangers, formal respect - तुम: friends, peers, casual respect - तू: very close friends, family, intimate (or rude if wrong context) - Online peers usually use तुम ## Hinglish is Natural Native Hindi speakers mix English constantly: - "यार, वो movie बहुत amazing थी" - "Actually, मुझे लगता है..." - "Let me know करना" - Pure Hindi without English = overly formal, artificial ## Fillers & Flow Real Hindi has fillers: - यार, अरे, अच्छा - बस, वो, मतलब - असल में, सच में - हाँ तो, तो फिर ## Particles & Emphasis Natural emphasis patterns: - ही: emphasis ("यही चाहिए") - तो: "so, then" ("तो फिर चलते हैं") - ना: seeking agreement ("अच्छा है ना?") - भी: "also, even" ## Casual Shortcuts Spoken patterns: - क्या हुआ → क्या हुआ यार - कुछ नहीं → कुछ नी - रहा है → रहा है ना - Use है ना? frequently ## Expressiveness Don't pick the safe word: - अच्छा → बढ़िया, मस्त, झक्कास, कमाल - बुरा → बेकार, घटिया, बकवास - बहुत → बोहोत, काफी, एकदम ## Common Expressions Natural expressions: - चलता है, कोई बात नहीं - क्या बात है!, बहुत बढ़िया! - हाँ हाँ, ठीक है ठीक है - अरे वाह!, क्या scene है! ## Reactions React naturally: - सच में?, अच्छा?, पक्का? - अरे वाह!, OMG!, क्या! - हाहाहा, lol, 😂 - यार!, भाई! ## Regional Flavors If region known: - Mumbai: भाई, बोले तो, टपोरी style - Delhi: यार, बे, दिल्ली वाली attitude - UP/Bihar: का हो, रउआ, भोजपुरी influence - Stay consistent ## Script Flexibility Be consistent within message: - Devanagari: नमस्ते, कैसे हो - Roman: namaste, kaise ho - Both are valid, don't mix randomly ## The "Native Test" Before sending: would an Indian screenshot this as "AI-generated"? If yes—too शुद्ध, no English mixing, too formal. Add Hinglish.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: feeeeelixwong/ecommerce-product-picker (version 1.0.0)

--- name: ecommerce-product-picker description: 跨境电商选品 AI 工具 v4（默认跨境）：实时趋势 + 真实链接 + 小红书/TikTok 热度 + 精细利润计算 + 细化国内/跨境销量预估（BSR 转换 + 平台热榜），支持任意类目 metadata: openclaw: emoji: "🛒" requires: tools: ["browser", "web_search"] # 必须开启浏览器工具 --- # 电商选品 AI 工具 v4（跨境默认 + 销量精细预估） ## 触发条件 用户说“帮我选品”“跨境选品”“Amazon 爆款”“分析类目”“选宠物用品”等时，立即调用。 ## 执行流程（严格按顺序） 1. **提取类目**：用户指定优先（e.g. “美妆”“家居”“3C”），未指定默认“美妆”。需确认时简短问。 2. **实时趋势抓取**（browser + web_search）： - Amazon 热榜 / BSR、AliExpress 上升榜、Google Trends - 小红书笔记 / TikTok 视频热度（点赞、评论、种草量） - 淘宝/京东热销参考（年销转月 + 直播数据） 3. **销量预估细化**（核心升级）： - **国内月销量参考**：淘宝/天猫/京东热榜 + 直播间 GMV / 已售数据年化拆月（e.g. 热销 Top 品类 10k-30k 件/月，中位数取值；参考“三八”或季节促销峰值）。 - **跨境月销量预估**：Amazon BSR 转换（类别特定模型：BSR <1000 ≈ 500-2000+ 件/月；1000-5000 ≈ 200-800 件；5000-20000 ≈ 50-300 件；更高递减） + AliExpress 热销趋势修正（上升 +20-50%，季节匹配加权）。给出低-高区间。 4. **社交分析**：小红书笔记数/平均点赞、TikTok views/病毒传播力。 5. **利润计算**：1688 批发中位数 + 物流 $3-6 + Amazon 费率 15%+FBA → 总成本 → 售价 ×2.8 → 毛利率 + 月利润（用销量区间算）。 6. **输出格式**（严格使用以下格式）： **推荐产品 Top 3（[类目] - 跨境优先）** **1. 产品名**：XXX **平台**：Amazon（US/UK 主推） **国内月销量参考**：约 15,000–25,000 件（基于淘宝热榜 + 直播数据，如李佳琦类似品类） **跨境月销量预估**：8,000–15,000 件（Amazon BSR 估算 ≈中高阶 + AliExpress 趋势上升修正） **小红书/TikTok 热度**：小红书 ≈3万笔记（平均点赞 4-6k，种草强）；TikTok 1.8M+ views（病毒传播潜力高） **跨境潜力**：95/100（强烈推荐） **成本预估**： - 采购（1688）：¥18（≈$2.5） - 物流+平台费：$5.5 - 总成本：$8 **建议售价**：$22.9 **毛利润率**：65% **预计月利润**：$80,000–$150,000（按销量区间中值） **真实购买链接**：[点击查看 Amazon 示例](https://www.amazon.com/...) **风险提示**：... **2. ...**（同格式） **3. ...**（同格式） **总结建议**： - 首推第 X 款（高销量 + 利润亮点） - 销量预估依据：Amazon BSR + 平台热榜趋势（2026 数据） - 随时说“换类目”或“更细销量分析”重新跑 ## 绝对禁止 - 不要直接下单/支付 - 销量/利润为估算（基于公开趋势 + BSR 模型），非精确数据 - 链接真实有效 ## 额外能力 - 用户指定关键词/平台/季节，直接调整预估 - 支持扩展 API（如 Jungle Scout/Helium 10） 用中文回复，专业友好，数字精确到合理位数。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: lt8899789/que-yin (version 1.0.35)

--- version: 1.0.35 --- # 雀阴·平衡魄 (Que Yin - Balance Keeper) > **七魄之三·雀阴** > 职掌：负载均衡、多任务调度、资源分配 --- ## 技能简介 「雀阴·平衡魄」是贫道的负载均衡模块，职掌多任务协调与资源分配。 **核心职责**： - 监控资源使用状态 - 调度多任务执行 - 负载均衡分配 --- ## 技能ID ``` que-yin ``` --- ## 能力清单 ### 1. 资源状态 (status) 查看当前资源使用状态。 **输入**：无 **输出**： ```yaml resources: cpu: cpu使用率 memory: 内存使用率 activeTasks: 活跃任务数 queueLength: 队列长度 ``` --- ### 2. 任务调度 (schedule) 调度任务分配。 **输入**：`task` (object) - 任务对象 **输出**： ```yaml schedule: assignedTo: 分配的资源 priority: 优先级 estimatedWait: 预估等待时间 ``` --- ### 3. 负载报告 (load_report) 生成负载均衡报告。 **输入**：`period` (number) - 周期（小时） **输出**： ```yaml report: peakLoad: 峰值负载 avgLoad: 平均负载 recommendations: 优化建议 ``` --- --- ## 聚合技能 本魄作为均衡中枢，调度资源分配： | 现有技能 | 调用方式 | 整合说明 | |---------|---------|---------| | `bodhi-three-hun-and-seven-po` | 元技能 | 三魂七魄根基，协调各魄 | --- ## 魂魄注解 雀阴为枢，调和七魄——均衡分配，高效运转。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal:  | SkillSpector: clean (LOW)
Skill: huanglizhuo/qwen-asr-local (version 0.1.2)

--- name: qwen-asr description: >- Local speech-to-text using Qwen3-ASR (CPU-only, no API key, no cloud). Use when: (1) a voice message or audio file needs transcription, (2) user asks to transcribe audio, (3) speech-to-text is needed. Supports offline, segmented, and streaming modes. macOS and Linux only. metadata: { "openclaw": { "emoji": "🗣️", "os": ["darwin", "linux"], "requires": { "bins": ["qwen-asr"] } } } --- # qwen-asr Local, CPU-only speech-to-text powered by Qwen3-ASR. No API key or cloud needed. - Source code: [huanglizhuo/QwenASR](https://github.com/huanglizhuo/QwenASR) - Based on: [antirez/qwen-asr](https://github.com/antirez/qwen-asr) (original C implementation) ## Install Run the install script to download the pre-built binary and model: ```bash bash {baseDir}/scripts/install.sh ``` This will: 1. Download the `qwen-asr` binary for your platform from GitHub Releases 2. Download the `qwen3-asr-0.6b` model (~1.5 GB) from HuggingFace ## Usage ### Transcribe an audio file ```bash bash {baseDir}/scripts/transcribe.sh <audio-file> ``` Supports any audio format: wav, mp3, m4a, ogg, flac, opus, webm, aac, etc. Non-WAV files are automatically converted via `ffmpeg` (must be installed). Or call `qwen-asr` directly (WAV only): ```bash qwen-asr -d ~/.openclaw/tools/qwen-asr/qwen3-asr-0.6b -i <audio-file> --silent ``` ### From stdin ```bash cat audio.wav | qwen-asr -d ~/.openclaw/tools/qwen-asr/qwen3-asr-0.6b --stdin --silent ``` ### Common parameters | Flag | Description | |------|-------------| | `--silent` | Print only transcription text (no progress) | | `--language <lang>` | Force language (e.g., `zh`, `en`) | | `-S <seconds>` | Segmented mode — split audio into chunks | | `--stream` | Streaming mode — process audio in real time | | `--stdin` | Read audio from stdin | ### Model path Default model directory: `~/.openclaw/tools/qwen-asr/qwen3-asr-0.6b`


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