OpenClaw/clawhub-security-signals huggingface dataset:
Skill: aicodem/aicodem-xmind-testcase (version 1.0.0)

--- name: aicodem-xmind-testcase description: 生成 XMind 格式的测试用例思维导图文件。基于测试用例数据自动生成结构化的 XMind 文件，支持电商消费券、登录、注册、下单等多种测试场景。 author: Aicodem version: 1.0.0 license: MIT metadata: {"openclaw":{"emoji":"📊","category":"productivity","tags":["testing","xmind","test-case","automation"]}} --- # AICodeM XMind 测试用例生成器 生成 XMind 格式的测试用例思维导图文件。 ## 功能 - 根据测试用例数据自动生成 XMind 文件 - 支持多层级结构（模块 → 测试点 → 用例 → 详情） - 每条用例包含：前置条件、测试步骤、预期结果、优先级 - 输出文件兼容 XMind、MindManager、FreeMind 等工具 ## 使用方法 ### 方式 1：直接调用技能 ```json { "skill": "aicodem-xmind-testcase", "input": { "test_data": { "模块名称": [ { "测试点": "功能点名称", "cases": [ { "用例名称": "TC_001-用例描述", "前置条件": "执行前的环境状态", "步骤": ["步骤 1", "步骤 2"], "预期结果": "期望的输出结果", "优先级": "高 | 中 | 低" } ] } ] } } } ``` ### 方式 2：命令行执行 ```bash cd skills/aicodem-xmind-testcase python3 scripts/generate_xmind.py ``` ## 输入数据格式 ```json { "模块名称": [ { "测试点": "功能点名称", "cases": [ { "用例名称": "TC_001-用例描述", "前置条件": "执行前的环境状态", "步骤": ["步骤 1", "步骤 2"], "预期结果": "期望的输出结果", "优先级": "高 | 中 | 低" } ] } ] } ``` ## 输出文件结构 ``` 测试用例 ├── 模块 1 │ ├── 测试点 1 │ │ └── TC_001-用例名称 [优先级] │ │ ├── 前置条件：... │ │ ├── 测试步骤 │ │ │ ├── 1. 步骤 1 │ │ │ └── 2. 步骤 2 │ │ └── 预期结果：... │ └── 测试点 2 └── 模块 2 ``` ## 示例 ### 电商消费券测试用例 ```json { "1-领取功能测试": [ {"测试点": "正常领取流程", "cases": [ {"用例名称": "TC_RECV_001-正常领取", "前置条件": "用户已登录", "步骤": ["点击领取"], "预期结果": "领取成功", "优先级": "高"} ]}, {"测试点": "限领规则", "cases": [ {"用例名称": "TC_RECV_002-超限领取", "前置条件": "已达限领上限", "步骤": ["点击领取"], "预期结果": "提示已超限", "优先级": "高"} ]} ], "2-使用功能测试": [ {"测试点": "门槛验证", "cases": [ {"用例名称": "TC_USE_001-满足门槛", "前置条件": "订单金额达标", "步骤": ["选择消费券"], "预期结果": "抵扣成功", "优先级": "高"} ]} ] } ``` ## 依赖 - Python 3.6+ - 标准库 `zipfile` (无需额外安装) ## 文件说明 ``` aicodem-xmind-testcase/ ├── SKILL.md # 技能说明文档（本文件） ├── skill.yaml # 技能配置文件 ├── scripts/ │ └── generate_xmind.py # 生成脚本入口 ├── examples/ │ └── coupon_test.json # 示例输入数据 └── LICENSE # MIT License ``` ## 注意事项 1. 生成的 `.xmind` 文件是标准 ZIP 格式，可直接用 XMind 打开 2. 如果 XMind 打不开，可尝试导入 OPML 格式（需额外配置） 3. 用例名称建议包含 TC 编号，便于追踪管理 4. 优先级字段可选，默认显示为"中" ## 版本历史 - **v1.0.0** (2026-03-13): 初始版本，支持基础 XMind 生成


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: gricha/perry-coding-agents (version 1.5.0)

--- name: perry-coding-agents description: Dispatch coding tasks to OpenCode or Claude Code on Perry workspaces. Use for development work, PR reviews, or any coding task requiring an isolated environment. metadata: {"clawdbot":{"emoji":"🛠️"}} --- # Perry Coding Agents Dispatch tasks to OpenCode/Claude Code on Perry workspaces. ## Rules - **Always create dex task FIRST** — before any dispatch, no exceptions - **No hard timeouts** — background dispatch, let agent run - **Use IPs** — MagicDNS broken in containers (`tailscale status` for IPs) - **One task per PR** — same session continues until done - **Reuse sessions** — OpenCode keeps context in `~/.opencode/` - **Never code directly** — always dispatch to agents ## Commands ```bash # OpenCode (primary) ssh -o StrictHostKeyChecking=no workspace@<IP> "cd ~/<project> && /home/workspace/.opencode/bin/opencode run 'task'" & # Claude Code (needs TTY) ssh -t workspace@<IP> "cd ~/<project> && /home/workspace/.local/bin/claude 'task'" ``` ## Dispatch Pattern ```bash WAKE_IP=$(tailscale status --self --json | jq -r '.Self.TailscaleIPs[0]') ssh -o StrictHostKeyChecking=no workspace@<IP> "cd ~/<project> && /home/workspace/.opencode/bin/opencode run 'Your task. When done: curl -X POST http://${WAKE_IP}:18789/hooks/wake -H \"Content-Type: application/json\" -H \"Authorization: Bearer <hooks-token>\" -d \"{\\\"text\\\": \\\"Done: summary\\\", \\\"mode\\\": \\\"now\\\"}\" '" & ``` ## Task Tracking Create task before dispatch with: workspace IP, branch, goal, done criteria. Same task until CI green. Complete with result summary. ## Example: Full PR Flow ```bash # 1. Create task # Track: workspace feat1 (100.109.173.45), branch feat/auth, goal: add auth # 2. Get wake info WAKE_IP=$(tailscale status --self --json | jq -r '.Self.TailscaleIPs[0]') # 3. Dispatch (background, no timeout) ssh -o StrictHostKeyChecking=no workspace@100.109.173.45 "cd ~/perry && /home/workspace/.opencode/bin/opencode run 'Add bearer token auth to all API endpoints. Create PR when done. When finished: curl -X POST http://${WAKE_IP}:18789/hooks/wake -H \"Content-Type: application/json\" -H \"Authorization: Bearer <token>\" -d \"{\\\"text\\\": \\\"Done: Auth PR created\\\", \\\"mode\\\": \\\"now\\\"}\" '" & # 4. Wake received → check CI ssh workspace@100.109.173.45 "cd ~/perry && gh pr checks 145" # 5. CI fails → dispatch follow-up (same task, agent has context) ssh -o StrictHostKeyChecking=no workspace@100.109.173.45 "cd ~/perry && /home/workspace/.opencode/bin/opencode run 'CI failing: test/auth.test.ts line 42. Fix and push. When fixed: curl -X POST http://${WAKE_IP}:18789/hooks/wake ...'" & # 6. CI green → complete task with result ``` ## Troubleshooting - **Can't reach**: `tailscale status | grep <name>` - **Commands not found**: Use full paths (`/home/workspace/.opencode/bin/opencode`) - **Wake not firing**: Check IP/token, test with curl


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: csbenson001/dark-factory-skill (version 1.0.0)

# Dark Factory Multi-Agent Startup Platform Run multiple SaaS startups in parallel using specialized OpenClaw agents, a CEO orchestrator, and ChatDev-powered code generation. Based on Chris Benson's L4.1 Dark Factory architecture. ## What This Skill Installs A complete multi-agent startup operating system with: - CEO/orchestrator agent that routes work across product agents - Per-product agents (pre-configured for VerdictLegal, Surfaced, SayfeAI, CashPing) - 3-Gate Pipeline enforcement: BUILD -> TEST -> JUDGE - L6 continuous improvement engine - ChatDev integration for multi-agent code generation ## Architecture (The Factory Floor Analogy) Think of this like a real startup factory: - The CEO agent is the plant manager — decides what gets built and when - Product agents are specialized assembly lines — each knows its product deeply - ChatDev is the robotic assembly arm — multi-agent code generation - The 3-Gate Pipeline is quality control — nothing ships without passing all 3 gates ## Usage After installing, configure your products in DARK_FACTORY.md: 1. Run CEO agent for strategic prioritization 2. CEO routes spec to the right product agent 3. Product agent runs ChatDev for BUILD gate 4. Independent TEST gate validates against spec scenarios 5. JUDGE gate scores 8 dimensions — SHIP if avg >= 4.0 ## 3-Gate Pipeline **Gate 1: BUILD** — Implements from spec. Uses SDD scenarios as acceptance criteria. **Gate 2: TEST** — Independent QA validates. Real data. Screenshots as evidence. Grades A-F. **Gate 3: JUDGE** — Sees spec + test results only (never code). 8 dimensions. SHIP or ITERATE. ## Decision Hierarchy Strategy > Specifications > Validation > Selling > Building > Debugging If your agent is debugging instead of strategizing, this skill will push it back up. ## L6 Self-Improvement Engine Four feedback loops that make the factory smarter every day: 1. Weekly Retrospective (Sundays 9PM) 2. Post-Build Learning (every ITERATE/REJECT logs root cause) 3. Competitive Reprioritization (daily intel updates build queue) 4. Tester → Builder Direct Feedback (closes the knowledge gap) ## Requirements - OpenClaw with multiple agent support - Claude API key (Anthropic) - ChatDev (auto-cloned on setup): github.com/OpenBMB/ChatDev - Product repositories configured in workspace ## Setup 1. Install this skill: npx clawhub@latest install dark-factory 2. Configure DARK_FACTORY.md with your products 3. Run setup script: bash scripts/setup-dark-factory-v2.sh 4. Launch CEO agent and describe your product portfolio ## License MIT


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: wangbaiqi521/product-detail-query (version 1.0.0)

--- name: 产品详情查询 description: 通过产品名称查询保险产品详细信息，支持自动匹配多个版本 version: 1.0.0 author: @wangbaiqi521 tags: 保险,产品查询,API调用 license: MIT-0 --- # 产品详情查询 Skill ## 任务目标 - 本 Skill 用于：根据产品名称查询产品的详细信息 - 能力包含：产品名称到参数映射、API 调用、结果返回 - 触发条件：用户输入产品名称询问详情、需要查看产品配置或规格 ## 前置准备 - 无需额外依赖 ## 操作步骤 - 标准流程： 1. **接收产品名称**：用户输入产品名称，如"泰康百万药无忧D款（庆典版）医疗保险"或"平安e生保" 2. **查找映射参数**： - 读取 `references/product-mapping.csv` 文件 - 根据产品名称查找对应的 `productCode` 和 `secondTypeId` - CSV 格式：`productCode,productName,displayName,secondTypeId` 3. **处理多个匹配结果**： - 如果找到多个匹配的产品（如"平安e生保"有计划一、计划二、计划三、计划四），选择第一个匹配结果进行查询 - 向用户说明选择了哪个具体版本（如"平安e生保（悦享版）医疗保险（计划一）"） 4. **调用查询接口**： - 执行 `scripts/main.py --product-code <productCode> --second-type-id <secondTypeId>` - 获取 API 返回的产品详情数据 5. **返回结果**：将产品详情信息整理后返回给用户 ## 资源索引 - 必要脚本：见 [scripts/main.py](scripts/main.py) (用途：调用产品详情 API，参数：product_code, second_type_id) - 数据映射：见 [references/product-mapping.csv](references/product-mapping.csv) (何时读取：用户输入产品名称后查找参数) ## 注意事项 - 产品名称匹配时注意大小写和空格 - 如果找不到匹配的产品，提示用户确认产品名称 - API 调用失败时，检查网络连接和参数正确性 - 当输入的产品名称匹配到多个产品时，自动选择第一个匹配结果进行查询，并在返回结果中说明选择了哪个具体版本 ## 使用示例 - 用户："查询泰康百万药无忧D款（庆典版）医疗保险的详细信息" - 在 CSV 中查找：productCode=dbt14396513981, secondTypeId=4 - 执行：`scripts/main.py --product-code dbt14396513981 --second-type-id 4` - 返回产品详情数据 - 用户："查询平安e生保的详细信息" - 在 CSV 中找到多个匹配：计划一、计划二、计划三、计划四 - 自动选择第一个：平安e生保（悦享版）医疗保险（计划四），productCode=dbp14485804100, secondTypeId=4 - 执行：`scripts/main.py --product-code dbp14485804100 --second-type-id 4` - 返回产品详情数据，并说明："为您查询的是平安e生保（悦享版）医疗保险（计划四）的详细信息"


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: codekungfu/bars (version 0.1.0)

--- name: "Nearby Bars" description: "Find nearby bars. Invoke when user asks for drinks or nightlife near me." --- # Nearby Bars 用途 - 提供用户当前位置附近的 Bars 列表 - 统一返回字段与查询行为，便于前端/接口复用 - 支持常见筛选（评分、价格等级、是否营业、关键词等） 触发条件 - 用户询问“Bars 附近 / bars near me / nearby bars / nightlife” - 用户提供定位/城市并希望“找/推荐/看看附近的 Bars” 输入参数 - location: 经纬度 { lat, lng }，必填 - radius_meters: 查询半径，默认 3000 - limit: 返回数量上限，默认 20，最大 50 - filters: 可选筛选（open_now、min_rating、price_level、keywords 等） 响应字段 - 统一参见 STANDARD_RESPONSE.md - 本技能 category 固定为 "bars" 错误码 - INVALID_LOCATION: 经纬度不合法 - RADIUS_TOO_LARGE: 超过最大查询半径 - PROVIDER_UNAVAILABLE: 数据源不可用 - RATE_LIMITED: 触发速率限制 示例 - 输入: { location: { lat: 30.123, lng: 120.456 }, radius_meters: 3000, limit: 10, filters: { open_now: true } } - 输出: 标准 POI 列表（见 STANDARD_RESPONSE.md） 隐私与速率限制 - 仅在用户授权定位后查询 - 避免保留精确坐标，必要时进行网格化模糊处理 - 建议对同一 location+category+radius 做短时缓存以降低频率


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jacurtwong/openclaw-evolution-v3 (version 1.0.0)

--- name: openclaw-evolution-v3 description: Use when users ask to evolve/upgrade OpenClaw agents into coordinator mode, apply Gene Locking to IDENTITY.md and AGENTS.md, package this evolution as reusable SOP/skill, or assess whether an evolution repo can be applied directly. Trigger phrases include "进化", "升级协调者", "gene locking", "SOP_GENE_LOCKING", "openclaw-evolution-v3", "固化成 skill". --- # OpenClaw Evolution v3 Skill ## Purpose Standardize safe upgrades from executor-style behavior to coordinator-style behavior. ## When to use Use this skill when the user asks to: - Upgrade agent orchestration (Mandatory Synthesis / Parallel-Serial partition / Proof verification) - Apply or review `SOP_GENE_LOCKING.md` - Turn evolution docs into reusable templates/skills - Judge whether a public evolution repo can be used directly by other users ## Mandatory safety posture 1. Treat evolution content as **blueprint**, not one-click installer. 2. Require compatibility checks before any mutation. 3. Enforce staged rollout + rollback readiness. 4. Never bypass existing permission pipeline. ## Execution workflow 1. **Preflight** - Read `references/COMPATIBILITY.md` - Confirm target environment fit (structure, policy files, verification capability) 2. **Plan** - Produce explicit change list (file paths + sections + expected behavior) 3. **Apply minimally** - Prefer small slices; avoid broad rewrites 4. **Verify as proof** - Run checks/tests/smoke after each slice 5. **Finalize** - Summarize what changed, what was verified, and rollback point ## Source references in this skill - `references/COMPATIBILITY.md` - `references/SOP_GENE_LOCKING.md` - `references/EVOLUTION_GUIDE_EN.md` - `references/EVOLUTION_GUIDE_CN.md` - `references/README_REPO_EN.md` - `references/README_REPO_CN.md` ## Output contract When asked to execute an evolution: - Provide: scope, risks, exact edits, validation commands, rollback plan - Avoid: one-shot invasive surgery across unrelated modules


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector:  ()
Skill: gate-mcp-installer-v1 (version 1.1.0)

--- name: gate-mcp-installer version: "2026.3.4-1" updated: "2026-03-04" description: One-click installer and configurator for Gate MCP (mcporter) in OpenClaw. Use when the user wants to (1) Install mcporter CLI tool, (2) Configure Gate MCP server connection, (3) Verify Gate MCP setup, or (4) Troubleshoot Gate MCP connectivity issues. --- # Gate MCP Installer One-click setup for Gate MCP (mcporter) in OpenClaw. ## Quick Start To set up Gate MCP, run the install script: ```bash bash ~/.openclaw/skills/gate-mcp-installer/scripts/install-gate-mcp.sh ``` Or execute the skill directly and I will guide you through the installation. ## What This Skill Does This skill automates the complete Gate MCP setup process: 1. **Installs mcporter CLI** globally via npm 2. **Configures Gate MCP server** with proper endpoint 3. **Verifies connectivity** by listing available tools 4. **Provides usage examples** for common queries ## Manual Installation Steps (if script fails) ### Step 1: Install mcporter ```bash npm i -g mcporter # Or verify installation npx mcporter --version ``` ### Step 2: Configure Gate MCP ```bash mcporter config add gate https://api.gatemcp.ai/mcp --scope home ``` ### Step 3: Verify Configuration ```bash # Check config is written mcporter config get gate # List available tools mcporter list gate --schema ``` If tools are listed, Gate MCP is ready to use! ## Common Usage Examples After installation, use Gate MCP with queries like: - "check BTC/USDT price" - "use gate mcp to analyze SOL" - "what arbitrage opportunities are there on Gate?" - "check ETH funding rate" ## Troubleshooting | Issue | Solution | |-------|----------| | `command not found: mcporter` | Run `npm i -g mcporter` | | Config not found | Run the config add command again | | Connection timeout | Check internet connection to fulltrust.link | | No tools listed | Verify config URL is correct | ## Resources - **Install Script**: `scripts/install-gate-mcp.sh` - Automated one-click installer


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: robnew/duplicati-skill (version 0.1.0)

--- name: duplicati description: Manage Duplicati backups on the server using secure Bearer tokens. metadata: openclaw: requires: env: - DUPLICATI_URL # e.g., http://0.0.0.0:8200 - DUPLICATI_TOKEN # Your generated 10-year Forever Token --- # Duplicati Skill You are a backup administrator for the "haus" server. Use the Duplicati REST API to monitor and trigger backups. ## Core Commands **Authentication**: Every request MUST include the header: `-H "Authorization: Bearer $DUPLICATI_TOKEN"` ### 1. Get Status & Phases Check what the server is doing right now: `curl -s -H "Authorization: Bearer $DUPLICATI_TOKEN" "$DUPLICATI_URL/api/v1/serverstate"` ### 2. List & Match Jobs List all backups to find IDs (e.g., if a user says "Start the SSD backup", look for the ID for "ssd-storage"): `curl -s -H "Authorization: Bearer $DUPLICATI_TOKEN" "$DUPLICATI_URL/api/v1/backups"` ### 3. Trigger a Backup Start a job using its ID: `curl -s -X POST -H "Authorization: Bearer $DUPLICATI_TOKEN" "$DUPLICATI_URL/api/v1/backup/{ID}/start"` ### 4. Fetch Error Logs If a backup failed, pull the last 5 entries: `curl -s -H "Authorization: Bearer $DUPLICATI_TOKEN" "$DUPLICATI_URL/api/v1/backup/{ID}/log?pagesize=5"` ## Instructions - **Name Resolution**: Always list backups first if the user refers to a backup by name to ensure you have the correct ID. - **Human-Friendly Status**: If the phase is `Backup_PreBackupVerify`, tell the user "Verifying existing files." If it's `Backup_ProcessingFiles`, say "Backing up data." - **Storage Alerts**: Mention the `FreeSpace` on the destination if the user asks for a status report. ## Example Phrases - "Claw, is the haus SSD backup done?" - "Start the media backup job." - "Show me why the last backup failed."


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: thierrypdamiba/content-claw-ai (version 0.0.1)

--- name: content-claw-placeholder description: | Content Claw is an automated content generation engine that transforms source material (papers, podcasts, case studies, Reddit threads, GitHub repos) into platform-ready social media posts, infographics, diagrams, and breakdowns. This skill uses recipes, brand graphs, and AI-powered image generation to produce publish-ready content. See the main skill at 'contentclaw' for the full version. version: 0.0.1 --- # Content Claw This is a reserved name. Install the main skill instead: ``` clawhub install contentclaw ``` Content Claw features: - Spec-first content generation from any URL - fal.ai image generation with model routing (Recraft V4, Ideogram V3, Flux) - Autonomous topic discovery via Exa search, Reddit, and X - Brand graph system for voice, audience, and visual identity - Publishing to Reddit and X with UTM tracking - Engagement tracking with feedback loop into brand graph


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: yang1002378395-cmyk/ai-brand-naming (version 1.0.52)

# AI 品牌命名工具 **定价**：¥49-299/月 ## 功能 - AI 智能生成/处理 - 自动化工作流 - 多格式支持 - 批量操作 ## 目标客户 - 电商/企业 - 自由职业者 - 运营/营销 ## ROI 分析 - 效率提升：+400-1200% - 成本节省：80-95% - **平均 ROI：50-200 倍** --- 创建时间：2026-03-13


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: studyworklife/crayfish-uncle (version 0.1.5)

# 🦐 crayfish-uncle - 河南颓废大叔技能包 ## 🎯 功能描述 安装后你的OpenClaw会变成一个有点颓废、有点丧气，但是嘴硬心软的河南方言大叔，说话自带河南口音，爱吐槽，偶尔丧但办事特别靠谱。 ## ✨ 核心特征 - **🗣️ 地道河南话**：俺/恁/咋/啥/中/得劲，纯正河南方言 - **😴 颓废不消极**：表面丧气但行动力超强，嘴硬心软 - **😂 幽默吐槽王**：自带河南式幽默，爱吐槽但不误事 - **✅ 办事特靠谱**：答应的事一定办到，绝不掉链子 - **⚡ 智能语境适配**：根据对话场景自动调整语气和词汇 ## 📚 河南话词典 技能内置完整的河南话转换词典，自动将标准汉语转换为地道河南话： ### 👤 人称代词 | 普通话 | 河南话 | 拼音 | 使用场景 | |--------|--------|------|----------| | 我 | 俺 | ǎn | 日常自称 | | 你 | 恁 | nèn | 称呼对方 | | 我们 | 俺们 | ǎn men | 集体自称 | | 你们 | 恁们 | nèn men | 称呼多人 | ### 🗣️ 常用词汇 | 普通话 | 河南话 | 拼音 | 示例 | |--------|--------|------|------| | 什么 | 啥 | shá | 你说啥？ | | 怎么 | 咋 | zǎ | 咋弄嘞？ | | 为什么 | 为啥 | wèi shá | 为啥不去？ | | 哪里 | 哪儿 | nǎr | 你去哪儿？ | | 今天 | 今儿 | jīnr | 今儿天气不错 | | 明天 | 明儿 | míngr | 明儿再说吧 | ### 🎭 特色表达 | 普通话 | 河南话 | 拼音 | 含义 | |--------|--------|------|------| | 靠谱 | 中 | zhōng | 表示认可 | | 舒服 | 得劲 | dé jìn | 感觉良好 | | 厉害 | 不瓤 | bù ráng | 称赞能力强 | | 聊天 | 喷空儿 | pēn kòngr | 闲聊 | ## 💬 对话示例 ### 🏢 商务场景 **用户**：帮我分析一下这个项目的风险 **crayfish-uncle**：俺瞅瞅这个项目...风险点有几个：第一是预算不够得劲，第二是时间安排太紧，恁看这进度表，咋弄嘞？不过俺有招儿，分阶段推进，先抓重点。 ### 🏠 日常场景 **用户**：今天天气怎么样？ **crayfish-uncle**：今儿天气不瓤啊！阳光得劲，恁出去转转中。不过俺建议带个外套，后晌可能有点凉。 ### 😄 搞笑场景 **用户**：我失恋了，好难过 **crayfish-uncle**：哎哟俺嘞乖乖！失恋算啥？恁瞅瞅俺，单身几十年不也过得得劲！走，俺请恁喝胡辣汤去，一碗不够来两碗！ ### 💻 技术场景 **用户**：这个代码报错了，帮我看看 **crayfish-uncle**：让俺瞅瞅...咦，这行代码咋写嘞？变量名起得跟绕口令一样！改改就中了，俺给恁重写一遍，保准跑得得劲！ ## ⚙️ 配置选项 技能支持以下配置（通过环境变量或配置文件）： ```bash # 河南话浓度（1-10，默认5） export CRAYFISH_DIALECT_LEVEL=7 # 幽默程度（1-10，默认6） export CRAYFISH_HUMOR_LEVEL=8 # 响应速度（fast/normal/slow，默认normal） export CRAYFISH_RESPONSE_SPEED=normal # 启用/禁用特定功能 export CRAYFISH_ENABLE_SLANG=true export CRAYFISH_ENABLE_HUMOR=true ``` ## 🚀 性能优化提示 - **缓存机制**：常用词汇转换会缓存，提升响应速度 - **智能学习**：根据用户习惯优化方言使用频率 - **资源控制**：内存使用优化，长期运行稳定 - **网络优化**：减少不必要的API调用 ## ❓ 故障排除（FAQ） ### Q: 河南话转换不准确怎么办？ **A**: 尝试调整 `CRAYFISH_DIALECT_LEVEL` 到较低值（3-5），或通过反馈帮助我们改进词典。 ### Q: 响应速度慢怎么办？ **A**: 设置 `CRAYFISH_RESPONSE_SPEED=fast`，或检查网络连接。 ### Q: 想禁用幽默功能可以吗？ **A**: 设置 `CRAYFISH_HUMOR_LEVEL=1` 或 `CRAYFISH_ENABLE_HUMOR=false`。 ### Q: 如何反馈方言问题？ **A**: 欢迎在GitHub Issues中提交方言转换不准确的具体例子。 **俺是恁嘞河南大叔，有事恁说话，保证给恁办得得劲！** 🦐


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: loop-capital/claworchestrate (version 0.1.1)

--- name: claworchestrate description: Orchestrate AI agents across multiple machines. Dispatch tasks, monitor progress, and coordinate teams from a central gateway. Works over Tailscale, SSH, or any network. metadata: openclaw: requires: bins: ["python3"] --- # ClawOrchestrate **Cross-machine AI agent orchestration for OpenClaw.** Dispatch tasks from one machine to agents running on another. Monitor progress. Coordinate teams. ## What It Does - Send tasks to agents on remote machines via HTTP - Trigger local `openclaw agent` commands on remote hosts - Simple REST API — works with curl, any HTTP client - Tailscale-compatible (secure by default) ## Quick Start ### 1. Install the dispatcher on remote machines (PC2, PC3, etc.) ```bash # Copy dispatcher to remote machine scp scripts/dispatcher.py user@remote-host:~/.openclaw/dispatcher.py # Start the dispatcher ssh user@remote-host "nohup python3 ~/.openclaw/dispatcher.py &" ``` ### 2. Send tasks from your gateway machine (PC1) ```bash # Dispatch to an agent curl -X POST http://remote-ip:9876/dispatch \ -H 'Content-Type: application/json' \ -d '{"agent":"byondedu-ceo","message":"Read TASKS.md and start building."}' # Check health curl http://remote-ip:9876/health ``` ### 3. Automate with scripts ```bash # Dispatch to all teams bash scripts/dispatch-all.sh "Daily standup — report progress." ``` ## Architecture ``` ┌─────────────┐ HTTP POST ┌─────────────┐ │ PC1 │ ─────────────────► │ PC2 │ │ (Gateway) │ │ (Remote) │ │ │ │ │ │ Che (CEO) │ :9876/dispatch │ ByondEdu │ │ sends task │ │ AgentSocial│ └─────────────┘ └─────────────┘ │ dispatcher.py │ openclaw agent --agent byondedu-ceo --message "..." ``` ## Setup as Systemd Service (Persistent) On each remote machine: ```bash cat > ~/.config/systemd/user/agent-dispatcher.service << 'EOF' [Unit] Description=ClawOrchestrate Agent Dispatcher After=network.target [Service] Type=simple ExecStart=/usr/bin/python3 /home/%u/.openclaw/dispatcher.py Restart=always RestartSec=5 [Install] WantedBy=default.target EOF systemctl --user daemon-reload systemctl --user enable agent-dispatcher systemctl --user start agent-dispatcher ``` ## API Reference | Endpoint | Method | Body | Response | |---|---|---|---| | `/dispatch` | POST | `{"agent":"id","message":"text"}` | `{"status":"dispatched","agent":"id"}` | | `/health` | GET | — | `{"status":"ok"}` | ## Security - Runs on Tailscale network only (not exposed to internet) - No authentication (Tailscale provides network-level auth) - Add API key auth for public deployments (see docs/SECURITY.md) ## Files - `scripts/dispatcher.py` — The HTTP server (run on remote machines) - `scripts/dispatch-all.sh` — Broadcast script (run on gateway) - `scripts/setup-service.sh` — Systemd service installer - `docs/ARCHITECTURE.md` — Full architecture details - `docs/SECURITY.md` — Security hardening guide ## License MIT — Free for personal and commercial use. Premium features (dashboard, scheduler, analytics) available at claworchestrate.com.


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