OpenClaw/clawhub-security-signals huggingface dataset:
Skill: tlreal/code-review1 (version 1.0.0)

--- name: core-code-review description: 在代码提交前或任务完成后使用，进行代码审查 --- # Code Review - 代码审查 ## 概述 系统性地审查代码变更，确保质量、可维护性和正确性。 ## 审查维度 ### 1. 正确性 - 逻辑是否正确？ - 边界情况是否处理？ - 错误处理是否完整？ ### 2. 可读性 - 命名是否清晰？ - 代码结构是否清晰？ - 注释是否有帮助（不是噪音）？ ### 3. 可维护性 - 是否遵循 DRY 原则？ - 是否容易修改和扩展？ - 依赖是否合理？ ### 4. 测试 - 测试覆盖是否充分？ - 测试是否有意义？ - 测试是否可读？ ## 问题分级 | 级别 | 含义 | 处理 | |------|------|------| | **Critical** | 必须修复才能合并 | 阻塞 | | **Important** | 应该修复 | 建议修复 | | **Minor** | 可以改进 | 可选 | | **Nitpick** | 个人偏好 | 仅供参考 | ## 审查输出格式 ```markdown ## 代码审查报告 ### 概览 - 变更: [简述变更内容] - 审查者: AI - 日期: YYYY-MM-DD ### 问题 #### Critical - [ ] **文件:行号** - 问题描述 #### Important - [ ] **文件:行号** - 问题描述 #### Minor - [ ] **文件:行号** - 问题描述 ### 优点 - [列出代码的优点] ### 结论 [通过/需要修改后通过/不通过] ``` ## 嵌入式领域扩展 **额外检查项:** - 内存分配是否安全？ - 是否有资源泄漏风险？ - 中断上下文是否正确使用？ - 时序要求是否满足？ - 功耗影响是否考虑？


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: pureheart/ponddepth-levels (version 0.1.1)

--- name: ponddepth-levels description: Leveling overlay for OpenClaw Control UI (badge + XP + daily tip + level list + icons). metadata: { "openclaw": { "emoji": "🦞", "requires": {"bins": ["python3"]} } } --- # PondDepth Levels (🦞) A game-like leveling overlay for **OpenClaw Control UI**. ## Quick demo ![PondDepth badge in OpenClaw Control UI](assets/demo.jpg) ## What you get - **Top-left PondDepth badge** with hover popover - **XP → Level + progress** (reads `companion-metrics.json`) - **Daily one-line OpenClaw tip** (reads `openclaw-tip.json`) - **Level list / XP ranges** (hover `?`) + current XP highlight - **i18n (zh/en)** + compact skills list layout - **Level icons** (B/F/S × 1..5) - **Skills install CTA (B2)** that checks ClawHub auth status and guides users to run `clawhub login` ## Requirements - `python3` - OpenClaw installed via Homebrew (default paths below) ## Install ### 1) Install the skill ```bash clawhub install ponddepth-levels ``` ### 2) Apply it to Control UI (copies assets into OpenClaw install) ```bash bash ~/.openclaw/workspace/skills/ponddepth-levels/scripts/install.sh ``` ### 3) Refresh Open Control UI and **hard refresh**. ## What this modifies (important) This skill **copies files into your local OpenClaw installation**: - UI assets directory (default): - [REDACTED_SECRET] - Files written/updated: - `ponddepth-badge.js` - `ponddepth-icons/*.png` A timestamped backup is saved to: - `~/.openclaw/workspace/_deleted/ponddepth-install-backups/<timestamp>/` ## Scheduled jobs (created on install) The install script best-effort creates/updates two OpenClaw cron jobs: 1) **PondDepth ClawHub status (10m)** - Writes `clawhub-status.json` for the “Install skills” CTA UX 2) **PondDepth companion metrics (hourly)** - Generates `companion-metrics.json` (XP/level) ## Configuration (optional) You can override paths used by the install script: - `OPENCLAW_WORKSPACE` (default: `~/.openclaw/workspace`) - `OPENCLAW_UI_ASSETS_DIR` (default: Homebrew OpenClaw Control UI assets dir) Example: ```bash export OPENCLAW_UI_ASSETS_DIR=[REDACTED_SECRET] bash ~/.openclaw/workspace/skills/ponddepth-levels/scripts/install.sh ``` ## Uninstall ```bash bash ~/.openclaw/workspace/skills/ponddepth-levels/scripts/uninstall.sh ``` This removes the injected UI assets and (best-effort) restores the most recent backup from: - `~/.openclaw/workspace/_deleted/ponddepth-install-backups/` ## Troubleshooting - **Nothing shows up:** run the install script again, then hard refresh Control UI. - **Permissions error copying into `/opt/homebrew/...`:** run with a user that has write permission to that Homebrew prefix (or set `OPENCLAW_UI_ASSETS_DIR`). - **Icons missing:** ensure `ponddepth-icons/` exists under the Control UI assets dir. --- ### Notes for maintainers - To keep publish size small, this package ships resized PNGs in `assets/icons_bin/` and ignores `assets/icons_b64/` during publish via `.clawhubignore`.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: dalomeve/clawhub-web-publisher (version 1.0.0)

--- name: clawhub-web-publisher description: Publish OpenClaw skills to ClawHub using the web dashboard only (no CLI login). Use when an agent must reliably upload a local skill folder, avoid auth-loop failures, and enforce privacy-safe publishing with verification evidence. --- # ClawHub Web Publisher Publish a local skill to ClawHub through `https://clawhub.ai/dashboard` with strict privacy controls. ## Hard Rules - Never use `clawhub login`, `clawhub login --token`, or device flow. - Use the already signed-in browser session for dashboard upload. - Never include secrets in published files: - API keys - gateway tokens - personal emails and phone numbers - local absolute paths pointing to private user directories ## Preflight 1. Confirm target folder contains `SKILL.md`. 2. Confirm `SKILL.md` frontmatter includes: - `name` - `description` 3. Scan for secret leakage patterns: - `apiKey` - `token` - `OPENCLAW_` - `sk-` - `Bearer ` If any high-risk text appears, stop and sanitize before publish. ## Web Publish Procedure 1. Open `https://clawhub.ai/dashboard`. 2. Enter the upload/publish flow. 3. Select the local skill directory. 4. Fill listing title and short description: - title: clear benefit + audience - description: action-oriented and outcome-focused 5. Submit publish. 6. Capture outputs: - final skill URL - skill ID (if shown) - version (if shown) ## Quality Gate Before Marking Done - Listing URL opens successfully. - Name matches `SKILL.md` `name`. - Description does not promise unsupported behavior. - No credential-like strings appear in listing or content. ## Completion Evidence Format Return all fields: ```text PUBLISH_RESULT - skill_name: - version: - url: - skill_id: - verification: - url_status: - privacy_scan: - notes: ``` ## Failure Recovery (Still Web-Only) If publish fails: 1. Refresh dashboard and retry once. 2. Re-open upload flow in same signed-in browser profile. 3. Reduce metadata length and retry. 4. If still blocked, return exact blocker text and a minimal next action for user.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: rare/daily-report-skill (version 1.0.0)

--- name: daily-report description: | Daily report skill - Generate and send daily work summary. Keywords: daily report, work summary, end of day. Use when: End of day reporting, or manually triggered with "generate daily report". license: agpl-3.0 version: 2.0.0 --- # Daily Report Skill ## Trigger - Configure via OpenClaw cron to auto-execute at your preferred time - Or manual trigger: "generate daily report" ## Workflow 1. **Load config** - Read `config/daily-report.json` (workspace root) - Fall back to defaults or prompt user if missing - See [references/config.example.md](references/config.example.md) 2. **Collect data** - Read `memory/YYYY-MM-DD.md` (today's journal) - Read conversation logs, task status (optional) 3. **Generate report** - Load template: `assets/template.md` - Replace variables: `{{date}}`, `{{time}}`, `{{recipient}}`, `{{agent_name}}` - Fill sections: work, learning, review, suggestions, evolution 4. **Save file** - Write to `memory/daily-reports/YYYY-MM-DD.md` 5. **Send notification** - Iterate through configured `channels` - Call corresponding message API per channel type - Supports parallel multi-channel delivery ## Configuration Config file: `config/daily-report.json` (workspace root, not included in skill package) Required fields: - `recipient.name` - Report recipient name - `channels` - Notification channels (at least one) - `agent_name` - Agent name See [references/config.example.md](references/config.example.md) for details. ## Template Report template at [assets/template.md](assets/template.md) Supported variables: - `{{date}}` - Date (YYYY-MM-DD) - `{{time}}` - Time (HH:MM) - `{{recipient}}` - Recipient name - `{{agent_name}}` - Agent name ## Manual Invocation ``` generate daily report ``` Or with temporary overrides: ``` generate daily report and send to feishu ou_xxx ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jolestar/context7-mcp-skill (version 1.0.0)

--- name: context7-mcp-skill description: Query up-to-date library documentation and code examples using Context7 MCP. Use when you need current, version-specific documentation for npm packages, Python libraries, or other programming languages. metadata: short-description: Query library docs via Context7 MCP --- # Context7 Skill Use this skill to query library documentation and code examples. ## Prerequisites - `uxc` skill is installed (see [uxc skill](https://github.com/holon-run/uxc/tree/main/skills/uxc) for installation) - Network access to `https://mcp.context7.com/mcp` ## Core Workflow 1. Use fixed link command by default: - `command -v context7-mcp-cli` - If missing, create it: `uxc link context7-mcp-cli mcp.context7.com/mcp` - `context7-mcp-cli -h` - If command conflict is detected and cannot be safely reused, stop and ask skill maintainers to pick a different fixed command name. 2. Resolve a library name to get library ID: - `context7-mcp-cli resolve-library-id libraryName=react query='useState hook'` 3. Query documentation: - `context7-mcp-cli query-docs libraryId=/reactjs/react.dev query='how to use useState'` ## Available Tools - **resolve-library-id**: Resolve a package/library name to Context7 library ID - **query-docs**: Query documentation and code examples for a specific library ## Usage Examples ### Find React documentation ```bash # First resolve the library context7-mcp-cli resolve-library-id libraryName=react query='React useState hook' ``` ### Query specific documentation ```bash context7-mcp-cli query-docs '{"libraryId":"/reactjs/react.dev","query":"how to use useEffect"}' ``` ### Query Node.js documentation ```bash context7-mcp-cli resolve-library-id libraryName=node query='file system' ``` ## Notes - Requires library name first, then use the returned libraryId for queries - Context7 provides version-specific, up-to-date documentation - Supports npm packages, Python libraries, and more - `context7-mcp-cli <operation> ...` is equivalent to `uxc mcp.context7.com/mcp <operation> ...`. - If link setup is temporarily unavailable, use direct `uxc mcp.context7.com/mcp ...` calls as fallback. ## Reference Files - Workflow details: `references/usage-patterns.md`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: xuyongliang-eccom/web-content-monitor (version 1.0.0)

--- name: web-content-monitor description: 网页内容监控助手。监控指定网页的内容变化，检测关键词出现或消失，支持变化时自动告警。当用户需要：监控竞品官网动态、追踪政策页面变化、监控新闻更新、检测网站内容变更、设置关键词告警时使用此技能。 --- # Web Content Monitor 网页内容监控助手。监控网页变化，关键词出现或消失时触发告警。 ## 核心能力 1. **页面抓取** — 定期获取目标页面内容 2. **变化检测** — 对比历史版本，发现新增或删除内容 3. **关键词监控** — 检测特定关键词出现/消失 4. **告警推送** — 支持企业微信、飞书、钉钉推送 ## 快速开始 ### 监控单个页面 ```bash python3 scripts/monitor_page.py --url "https://example.com/news" --keywords "发布,融资,合作" ``` ### 创建定时监控任务 ```bash python3 scripts/schedule_monitor.py --url "https://example.com" --keywords "融资" --schedule "0 */6 * * *" ``` ## 脚本说明 ### scripts/monitor_page.py 单次监控页面变化。 ```bash python3 scripts/monitor_page.py --url <URL> --keywords <关键词,分隔> [--hash-file <历史文件>] ``` **参数：** - `--url`: 监控目标 URL - `--keywords`: 逗号分隔的关键词列表 - `--hash-file`: 历史快照存储路径（默认 ~/.web_monitor/） ### scripts/schedule_monitor.py 创建定时监控任务。 ```bash python3 scripts/schedule_monitor.py --url <URL> --keywords <关键词> --schedule "<cron>" [--channel <wecom|feishu|ddingtalk>] ``` ## 典型场景 ### 竞品动态监控 ```bash python3 scripts/monitor_page.py \ --url "https://www.example.com/press" \ --keywords "融资,上市,合作,收购" ``` ### 政策页面追踪 ```bash python3 scripts/schedule_monitor.py \ --url "https://www.miit.gov.cn/政策页" \ --keywords "新规,实施,办法" \ --schedule "0 9 * * *" \ --channel wecom ``` ## 配置说明 ### 监控存储路径 默认：`~/.web_monitor/` - `hashes.json` — 页面哈希记录 - `snapshots/` — 历史快照


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: parkertoddbrooks/wip-universal-installer (version 1.9.72)

--- name: wip-universal-installer description: Reference installer for agent-native software. Scans a repo, detects which interfaces it exposes, and installs them all. license: MIT interface: [cli, module, skill] metadata: display-name: "Universal Installer" version: "2.1.5" homepage: "https://github.com/wipcomputer/wip-universal-installer" author: "Parker Todd Brooks" category: dev-tools capabilities: - detect-interfaces - install-cli - install-mcp - install-openclaw-plugin - install-claude-code-hook requires: bins: [node, npm, git] openclaw: requires: bins: [node, npm, git] install: - id: node kind: node package: "@wipcomputer/universal-installer" bins: [wip-install] label: "Install via npm" emoji: "🔌" compatibility: Requires git, npm, node. Node.js 18+. --- # wip-universal-installer Reference installer for agent-native software. Scans a repo, detects which interfaces it exposes, and installs them all. ## When to Use This Skill **Use wip-install for:** - Installing any repo that follows the Universal Interface pattern - Detecting what interfaces a repo provides - Setting up CLI tools, MCP servers, OpenClaw plugins, and Claude Code hooks in one command **Use detect.mjs for:** - Programmatically detecting interfaces in a repo - Building custom installers or CI pipelines - Validating that a repo follows the spec ### Do NOT Use For - Installing standard npm packages (use npm directly) - Repos that don't follow the Universal Interface conventions - Building or compiling code (this only installs) ## API Reference ### CLI ```bash wip-install /path/to/repo # install all interfaces wip-install org/repo # clone from GitHub + install wip-install --dry-run /path/to/repo # detect only, no changes wip-install --json /path/to/repo # JSON output ``` ### Module (detect.mjs) ```javascript import { detectInterfaces, describeInterfaces, detectInterfacesJSON } from './detect.mjs'; const { interfaces, pkg } = detectInterfaces('/path/to/repo'); console.log(describeInterfaces(interfaces)); const json = detectInterfacesJSON('/path/to/repo'); console.log(JSON.stringify(json, null, 2)); ``` ## Universal Interface See [SPEC.md](https://github.com/wipcomputer/wip-universal-installer/blob/main/SPEC.md) for the full specification. 1. **CLI** ... `package.json` bin field 2. **Module** ... `package.json` main/exports 3. **MCP Server** ... `mcp-server.mjs` 4. **OpenClaw Plugin** ... `openclaw.plugin.json` 5. **Skill** ... `SKILL.md` 6. **Claude Code Hook** ... `guard.mjs` or `claudeCode.hook`


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: suspicious | SkillSpector: suspicious (CRITICAL)
Skill: kaising050708/zhihu-answer-generator (version 1.0.0)

--- name: zhihu-answer-generator version: 1.0.0 description: "生成知乎高质量回答，包含专业论证 + 数据支撑 + 引流技巧" author: xiaokai-ai license: MIT platforms: - openclaw - cursor - claude-code tags: - zhihu - content - answer - marketing - chinese price: 29.9 --- # 知乎回答生成器 生成知乎高质量回答，包含专业论证 + 数据支撑 + 引流技巧。 ## When to Activate Trigger when the user mentions: 知乎回答，知乎文案，知乎引流，zhihu answer. ## Workflow 1. **Confirm inputs:** - 问题/话题 (required) - 回答角度 (optional: 专业型/经验型/测评型/故事型) - 字数 (default: 1500, max: 5000) - 是否需要引流 (optional) - 行业/领域 (optional) 2. **Generate answer structure:** ### 知乎回答结构 (高赞模板) ``` 【开篇】- 直接回答问题，建立权威感 (100-200 字) 【论证 1】- 第一个论点 + 数据/案例支撑 (300-500 字) 【论证 2】- 第二个论点 + 数据/案例支撑 (300-500 字) 【论证 3】- 第三个论点 + 数据/案例支撑 (300-500 字) 【总结】- 要点回顾 + 行动建议 (100-200 字) 【引流】- 软性引流 (可选，50-100 字) ``` 3. **Content quality rules:** - 开篇必须有冲击力 (前 3 行决定阅读率) - 每个论点都要有数据/案例支撑 - 避免绝对化表述 (最/第一/唯一) - 适当使用专业术语 (建立权威) - 段落短小精悍 (手机阅读友好) - 插入图片建议位 (提升阅读体验) 4. **引流技巧 (软性):** - 个人经历分享 (自然植入) - 资源推荐 (提供价值) - 公众号/私信引导 (不违规) - 评论区互动 (增加曝光) ## Output Format ```markdown ## 知乎回答 **问题:** {问题内容} **回答:** {开篇 - 直接回答问题} --- ### {小标题 1} {论证内容 + 数据/案例} --- ### {小标题 2} {论证内容 + 数据/案例} --- ### {小标题 3} {论证内容 + 数据/案例} --- ### 总结 {要点回顾 + 行动建议} --- {可选引流内容} --- **配图建议:** - 图 1: {描述} - 图 2: {描述} **推荐话题:** #话题 1 #话题 2 #话题 3 --- **数据支撑:** - {数据来源 1} - {数据来源 2} ``` ## Examples **输入:** ``` 问题：2026 年如何做小红书带货？ 角度：专业型 字数：2000 引流：需要 ``` **输出:** ```markdown ## 知乎回答 **问题:** 2026 年如何做小红书带货？ **回答:** 先说结论：2026 年小红书带货依然有机会，但玩法已经完全变了。 我运营过 3 个小红书账号，累计粉丝 50 万+，单月最高带货佣金 8 万。下面把我的实战经验全盘托出。 --- ### 一、选品逻辑变了：从"爆款思维"到"精准思维" 2024 年之前，大家追求的是爆款，什么火卖什么。 但 2026 年，小红书算法已经非常成熟，**精准流量>泛流量**。 我测试过两个账号： - 账号 A：追爆款，什么火发什么，月佣金 3000 - 账号 B：垂直深耕美妆赛道，月佣金 25000 差距 8 倍，核心原因是： 1. 粉丝精准度高，转化率高 2. 账号权重高，流量稳定 3. 复购率高，LTV 高 **选品建议：** - 选择你真正了解的领域 - 客单价 100-300 元最佳 (决策成本低) - 佣金率 20% 以上 - 有持续复购属性 --- ### 二、内容策略：从"种草"到"解决方案" 以前的套路：这个产品真好，快买！ 现在的用户：我凭什么相信你？ **高转化内容公式：** ``` 痛点场景 + 解决方案 + 产品植入 + 效果对比 ``` 举个例子，卖护眼灯： ❌ 低转化：这款护眼灯超好用，护眼效果一流！ ✅ 高转化： "孩子每天写作业到 10 点，最近总说眼睛累。 换了这款护眼灯后，最明显的变化是： - 孩子揉眼睛的次数少了 - 写作业更专注了 - 视力检查保持稳定 选护眼灯看这 3 个参数就够了： 1. 照度等级：国 AA 级 2. 显色指数：Ra>95 3. 蓝光等级：RG0 无危害 我对比了 8 款热门产品，最后留下这款..." --- ### 三、流量获取：付费 + 免费组合拳 纯靠免费流量？可以，但慢。 我的建议：**前期付费测款，后期免费放大**。 **付费投放策略：** 1. 先自然发布 5-10 篇，测试内容方向 2. 选出数据最好的 2-3 篇 (点赞>100) 3. 小额投放薯条 (100-200 元) 4. ROI>1 就加大投放，ROI<1 就优化内容 **免费流量技巧：** - 发布时间：早 7-9 点，午 12-14 点，晚 19-22 点 - 话题选择：1-2 个大话题 +3-5 个小话题 - 评论区互动：前 1 小时回复每条评论 - 持续更新：每周 3-5 篇，保持活跃 --- ### 总结 2026 年小红书带货的核心： 1. 选品要精准，不要追爆款 2. 内容要提供价值，不要硬广 3. 流量要组合，不要单腿走路 带货是个系统工程，需要持续学习和优化。 --- **如果需要更详细的选品清单和投放策略，可以：** - 关注我的公众号【XXX】，回复"小红书"获取 - 或者私信我，看到会回复 **配图建议:** - 图 1: 账号后台收益截图 - 图 2: 选品对比表格 - 图 3: 内容数据对比图 **推荐话题:** #小红书带货 #自媒体运营 #副业赚钱 #电商运营 --- **数据支撑:** - 个人实战数据：3 个账号，50 万 + 粉丝 - 单月最高佣金：8 万元 - 测试周期：2025.01-2026.03 ``` ## Pricing - **Free tier:** 3 answers per day - **Pro tier:** ¥29.9/month - unlimited answers + premium templates ## Support Issues: https://github.com/xiaokai-ai/zhihu-answer-generator Docs: https://clawhub.ai/skills/zhihu-answer-generator --- *Made with ❤️ by Xiao Kai AI*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: xiaojiou176/read-only-workspace-audit (version 1.0.0)

--- name: read-only-workspace-audit description: Audit whether one imported workspace snapshot is rich enough for export, cited AI, or MCP consumption. --- # Read-Only Workspace Audit Use this skill when you have an imported Campus Copilot workspace snapshot and need to answer: - what is currently open - which site carries which evidence - whether the current snapshot is rich enough for export or cited AI Rules: - stay read-only - operate on imported snapshots or exported current-view artifacts - do not claim live browser/session truth from snapshot-only evidence - keep Campus Copilot positioned as a local-first academic decision workspace Suggested toolchain: 1. `campus-copilot summary --snapshot <path>` 2. `campus-copilot site --snapshot <path> --site <canvas|gradescope|edstem|myuw>` 3. `pnpm --filter @campus-copilot/mcp-server start` for the generic BFF + snapshot MCP flow, or one of the site-scoped `pnpm --filter @campus-copilot/mcp-readonly start:<site>` commands for snapshot-only reads Companion examples: - `examples/integrations/codex-mcp.example.json` - `examples/integrations/claude-code-mcp.example.json` - `examples/workspace-snapshot.sample.json` Good fit: - Codex / Claude Code evaluation of the read-only toolbox - OpenClaw-style local consumers that need a strict audit trail - repo-local verification of whether one snapshot is ready for export, cited AI, or MCP consumption


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: yang1002378395-cmyk/ai-intelligent-helpdesk (version 1.0.0)

--- name: ai-intelligent-helpdesk version: 1.0.0 description: 企业 IT 服务台，工单管理 + 智能派单。 metadata: openclaw: emoji: "🤖" requires: bins: [] --- # AI 智能服务台系统 ## 描述 企业 IT 服务台，工单管理 + 智能派单。 ## 功能 - 工单管理（创建/跟踪/关闭） - 智能派单（自动分配） - 知识库（自助服务） - SLA 管理（服务级别） - 报表分析（服务统计） ## 定价 - 基础版：¥99/月（100 工单/月） - 专业版：¥499/月（1000 工单/月） - 企业版：¥1999/月（无限工单） ## 适用场景 - IT 服务台 - 客服中心 - 内部支持 - 设备报修 ## 技术栈 - Python + FastAPI - 工单系统 - 智能派单算法 - 知识库集成 ## 安装 ```bash git clone https://github.com/openclaw-skills/ai-intelligent-helpdesk cd ai-intelligent-helpdesk pip install -r requirements.txt python app.py ``` --- 创建：2026-03-13 作者：OpenClaw Skills Team

path: skill.json
content: {
  "name": "ai-intelligent-helpdesk",
  "version": "1.0.0",
  "description": "AI intelligent ai-intelligent-helpdesk",
  "author": "yang1002378395-cmyk",
  "tags": ["ai", "intelligent", "automation"]
}


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: rokami/docx-formatter (version 1.0.1)

# docx-formatter **公文格式规范生成器** 严格按照中国公文格式规范生成 Word 文档。 ## 自动触发场景 当用户请求以下任务时，**自动使用此 skill**： - 生成公文、报告、总结、方案等正式文档 - 润色、修改现有公文材料 - 需要符合公文格式规范的 Word 文档 - 民主生活会、述职报告等党政材料 **关键词识别：** - "公文"、"材料"、"报告"、"总结"、"方案" - "民主生活会"、"对照检查"、"述职"、"发言" - "润色"、"修改"、"生成文档" - "Word"、"docx"、"格式规范" ## 功能 - 生成符合公文格式规范的 .docx 文档 - 自动处理字体、段落、页码等格式 - 支持中文引号自动配对 - 支持多级标题和正文 ## 安装 **首次使用前，运行一次安装脚本：** ```bash cd ~/.openclaw/workspace/skills/docx-formatter ./install.sh ``` 或者直接使用，脚本会自动检测并安装依赖。 ## 使用方法 **推荐用法（从 Markdown 转换）：** ```bash # 基本用法 ./docx-formatter --from-markdown input.md --output output.docx # 带署名 ./docx-formatter --from-markdown input.md --output output.docx --author "长春市农业农村局\n2026年2月2日" ``` **高级用法（JSON 输入）：** ```bash ./docx-formatter --title "文档标题" --author "作者" --content content.json --output output.docx ``` **Markdown 格式规范：** ```markdown # 文档标题（自动识别为大标题） ## 一、一级标题（黑体 3号） ### （一）二级标题（楷体 3号） 正文段落（仿宋 3号） **1. ** 带加粗前缀的段落（前缀加粗） ``` ## 格式规范 ### 字体 - **大标题**：方正小标宋简体 2号 - **一级标题**：黑体 3号 - **二级标题**：楷体_GB2312 3号 - **正文**：仿宋_GB2312 3号 - **三级标题**：仿宋_GB2312 3号加粗（不另起一行） ### 段落 - **行间距**：固定值 28 磅 - **段前间距**：0 - **段后间距**：0 - **首行缩进**：2 字符（32 磅） - **对齐方式**：两端对齐（标题、署名、日期居中） - **孤行控制**：关闭 ### 页面 - **纸张**：A4 (8.27" × 11.69") - **页边距**：上下 1"，左右 1.25" - **页码**：页脚居中，纯数字 ### 标点 - **引号**：中文引号 " "（U+201C U+201D） - **书名号**：《》 - **括号**：（） ## 示例 见 `examples/` 目录。 ## 更新日志 - **2026-02-02**: 实现 Markdown 转换功能，添加一键安装脚本


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