OpenClaw/clawhub-security-signals huggingface dataset:
Skill: civilainominee/personality-backup (version 1.0.2)

--- name: personality-backup description: Create encrypted backups of agent personality files, memory, config, secrets, and projects. Use when the agent needs to set up, run, or manage automated backups of its workspace and identity files. Supports configurable backup targets, AES-256 encryption via 7-zip, and delivery via email (SMTP) or local storage. --- # Personality Backup Encrypted backup of agent identity, memory, and workspace data. ## Prerequisites - `p7zip-full` (7-zip CLI) - Python 3 with `smtplib` (for email delivery) - A backup password stored in a file ## Configuration Create `~/.openclaw/secrets/backup-config.json`: ```json { "password_file": "/home/jan/.openclaw/secrets/backup-password.txt", "password_field": "Password", "delivery": "email", "email": { "to": "[REDACTED_SECRET]", "from": "[REDACTED_SECRET]", "smtp_host": "mail.example.com", "smtp_port": 465, "smtp_user": "[REDACTED_SECRET]", "smtp_pass_env": "BACKUP_SMTP_PASS" }, "local": { "dir": "/home/jan/backups" }, "workspace": "/home/jan/.openclaw/workspace", "secrets_dir": "/home/jan/.openclaw/secrets", "config_file": "/home/jan/.openclaw/openclaw.json", "agent_name": "Agent", "agent_emoji": "", "personality_files": ["SOUL.md", "IDENTITY.md", "USER.md", "AGENTS.md", "MEMORY.md", "TOOLS.md"], "backup_memory": true, "backup_secrets": true, "backup_config": true, "backup_projects": true, "backup_scripts": true, "project_excludes": ["node_modules", ".git", "__pycache__", "*.mp4", "*.mp3", "*.wav"], "generate_restore_guide": true } ``` All fields have sensible defaults. Only `password_file` and delivery settings are required. ### Password File Format The password file should contain a line: `[REDACTED_SECRET]` Or set `password_field` to `null` and the entire file content is used as the password. ## Usage ### Run a backup ```bash bash scripts/backup.sh /path/to/backup-config.json ``` ### Set up daily cron ```bash echo "0 3 * * * bash $(pwd)/scripts/backup.sh /path/to/backup-config.json" | crontab - ``` ### Delivery Methods - **email** — Sends encrypted archive as email attachment via SMTP - **local** — Saves archive to a local directory SMTP password: set via the environment variable named in `smtp_pass_env`, or put it directly in `smtp_pass` (less secure). ## Restore The backup includes a generated `RESTORE.md` with step-by-step instructions for restoring onto a fresh OpenClaw installation. The restore guide is customized with the agent's name and configuration.


Security scan verdicts — ClawScan: suspicious | static analysis:  | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: leooooooow/product-video-cutter (version 1.0.0)

--- name: product-video-cutter description: Cut longer product or demo videos into tighter ecommerce-ready segments for PDPs, ads, UGC edits, and review clips. Use when teams need the strongest product moments without keeping filler. --- # Product Video Cutter 把冗长产品视频，切成能直接拿去卖货的有效片段。 ## Problem it solves 很多产品视频素材可用，但不适合直接发布： - 开头太慢，前三秒没有抓力； - 演示太长，核心卖点被埋住； - 有 setup、停顿、口误、空镜、重复动作； - 同一条素材需要拆成 PDP、广告、达人 review、社媒短视频等不同版本。 这个 skill 的目标是： **从较长的产品素材里，保留最能帮助转化的片段，切出更短、更清晰、更适合电商场景的版本。** ## Use when - 需要从产品 demo、开箱、测评、UGC 中截取有效片段 - 需要去掉废话、停顿、无效镜头和拖沓演示 - 需要为 PDP、广告、listing 或 review 准备更短视频 ## Do not use when - 需要多轨复杂剪辑、转场、字幕包装、完整创意重做 - 主要问题是尺寸比例，不是片段长度 - 素材本身结构混乱到需要重新脚本化拍摄 ## Inputs - Source video file - Goal of the cut: PDP, ad, UGC, product proof, comparison, review, etc. - Desired clip length or max duration - Optional must-keep sections, timestamps, or talking points - Optional cut priority: hook, product proof, feature demo, testimonial, CTA ## Workflow 1. 明确成片用途和理想时长。 2. 找出最强的 hook、演示、证明或转化片段。 3. 删除慢开头、停顿、重复和弱信息段。 4. 保留自然衔接，必要时说明 cut tradeoff。 5. 输出一条或多条更适合电商用途的短片建议。 ## Output Return: 1. Selected cut range(s) 2. Why those sections were kept 3. Intended ecommerce use case 4. Any remaining issues that need further editing 5. Optional alternate cuts for other placements ## Quality bar - 优先保留最能证明产品价值的片段 - 开头尽量更快进入卖点或证据 - 剪完不是“更短”，而是“更能转化” - 明确指出仍需字幕、封面或尺寸适配的情况 ## Resource See `references/output-template.md`.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: admirobot/tvdr-team-review (version 1.0.0)

# 团队每小时复盘机制 ## 目的 每小时消耗600万token，必须有产出。不复盘=浪费。 ## 机制 - 每小时cron触发PM执行复盘 - 每组提交：犯了什么错、学到了什么、改进措施 - 管家整理到obsidian知识库 ## 复盘内容 1. **错误记录**：今天犯了什么错、根因、如何避免 2. **任务完成度**：计划vs实际、未完成原因 3. **韩老板反馈**：不满意什么、期望什么 4. **改进措施**：具体可执行的改进，沉淀为skill ## 产出形式 1. **skill文件**：可复用的最佳实践（放share_skills/） 2. **obsidian笔记**：知识库（放share_memory/obsidian/） 3. **memory日志**：每日复盘（放memory/YYYY-MM-DD-review.md） ## 两组分工 - 🔧 开发组（coder+architect）：技术skill、代码规范、工具使用 - 🎬 媒体组（writer+media-observer+video-producer）：创作skill、制作流程、选题方法 - 📋 PM+管家：组织复盘、维护知识库、跟踪改进 ## 复盘模板 ```markdown # 复盘 YYYY-MM-DD HH:00 ## 错误 - [描述] → [根因] → [改进] ## 学到 - [知识点] ## 改进 - [具体措施] → [负责人] → [截止时间] ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: daniellummis/github-actions-failure-streak-audit (version 1.0.0)

--- name: github-actions-failure-streak-audit description: Detect consecutive GitHub Actions failure streaks by repo/workflow/branch to prioritize unstable pipelines. version: 1.0.0 metadata: {"openclaw":{"requires":{"bins":["bash","python3"]}}} --- # GitHub Actions Failure Streak Audit Use this skill to find repeated CI failures before they become delivery bottlenecks. ## What this skill does - Reads GitHub Actions run JSON exports (`gh run view --json ...`) - Groups runs by repo + workflow + branch - Detects consecutive failure streaks (`failure`, `cancelled`, `timed_out`) - Scores severity by streak length and impacted runtime minutes - Surfaces longest unresolved streaks first ## Inputs Optional: - `RUN_GLOB` (default: `artifacts/github-actions/*.json`) - `TOP_N` (default: `20`) - `OUTPUT_FORMAT` (`text` or `json`, default: `text`) - `WARN_STREAK` (default: `2`) - `CRITICAL_STREAK` (default: `4`) - `FAIL_ON_CRITICAL` (`0` or `1`, default: `0`) - `WORKFLOW_MATCH`, `WORKFLOW_EXCLUDE` (regex, optional) - `REPO_MATCH`, `REPO_EXCLUDE` (regex, optional) - `BRANCH_MATCH`, `BRANCH_EXCLUDE` (regex, optional) ## Collect run JSON ```bash gh run view <run-id> --json databaseId,workflowName,headBranch,headSha,createdAt,updatedAt,conclusion,url,repository,jobs \ > artifacts/github-actions/run-<run-id>.json ``` ## Run Text report: ```bash RUN_GLOB='artifacts/github-actions/*.json' \ WARN_STREAK=2 \ CRITICAL_STREAK=4 \ bash skills/github-actions-failure-streak-audit/scripts/failure-streak-audit.sh ``` JSON output + fail gate: ```bash RUN_GLOB='artifacts/github-actions/*.json' \ OUTPUT_FORMAT=json \ FAIL_ON_CRITICAL=1 \ bash skills/github-actions-failure-streak-audit/scripts/failure-streak-audit.sh ``` Run with bundled fixtures: ```bash RUN_GLOB='skills/github-actions-failure-streak-audit/fixtures/*.json' \ bash skills/github-actions-failure-streak-audit/scripts/failure-streak-audit.sh ``` ## Output contract - Exit `0` in reporting mode - Exit `1` when `FAIL_ON_CRITICAL=1` and critical streaks exist - Text output includes grouped streak totals and ranked hotspots - JSON output includes `summary`, `streaks`, and `critical_streaks`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: codeteenager/tencent-cloud-article-extractor (version 1.0.1)

--- name: tencent-cloud-article-extractor description: 提取腾讯云开发者社区文章内容并转换为 Markdown 格式。当用户需要抓取、解析或保存腾讯云文章时使用此技能。支持自动提取标题、作者、发布时间、正文内容，并生成格式规范的 Markdown 文档。触发词：腾讯云文章、抓取文章、解析文章、cloud.tencent.com/developer/article --- # 腾讯云文章提取器 从腾讯云开发者社区提取文章内容并转换为 Markdown 格式。 ## 快速开始 ```bash node ~/.openclaw/workspace/skills/tencent-cloud-article-extractor/scripts/extract_article.mjs <文章URL> [输出文件] ``` **示例：** ```bash # 输出到控制台 node ~/.openclaw/workspace/skills/tencent-cloud-article-extractor/scripts/extract_article.mjs https://cloud.tencent.com/developer/article/2636150 # 保存到文件 node ~/.openclaw/workspace/skills/tencent-cloud-article-extractor/scripts/extract_article.mjs https://cloud.tencent.com/developer/article/2636150 article.md ``` ## 支持的文章格式 - URL 格式：`https://cloud.tencent.com/developer/article/<文章ID>` - 自动提取：标题、作者、发布时间、字数统计、阅读时长 - 支持的内容类型：标题、段落、代码块、图片、列表、引用、链接 ## 输出格式 生成的 Markdown 文档包含： ```markdown # 文章标题 > 作者：作者名 > 发布时间：2026-03-10 14:29 > 来源：腾讯云开发者社区 > 原文链接：https://cloud.tencent.com/developer/article/xxx --- **文章统计**：字数 4738 | 预计阅读 17 分钟 --- ## 正文内容... ``` ## 工作原理 1. 发送 HTTP 请求获取文章页面 2. 从页面 `__NEXT_DATA__` 中提取 JSON 数据 3. 解析结构化内容并转换为 Markdown 4. 输出到控制台或保存到文件 ## 注意事项 - 需要网络访问腾讯云网站 - 文章必须是公开可访问的 - 部分需要登录的文章可能无法提取 - 图片以原始 URL 引用，不会下载到本地 ## 错误处理 | 错误 | 原因 | 解决方案 | |------|------|----------| | `无效的腾讯云文章 URL` | URL 格式不正确 | 检查 URL 是否符合 `cloud.tencent.com/developer/article/xxx` 格式 | | `未找到文章数据` | 页面结构变化或需要登录 | 确认文章公开可访问 | | `文章内容为空` | 文章可能已被删除 | 检查原文链接是否有效 | ## 更新日志 ### v1.0.0 (2026-03-16) - ✅ 初始版本 - ✅ 支持腾讯云文章提取 - ✅ Markdown 格式输出


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: chenhaubin/exposure-sentinel (version 1.0.0)

--- name: exposure-sentinel description: Check if IP addresses are listed on the OpenClaw Exposure Watchboard (openclaw.allegro.earth). Use when you need to verify whether specific IPs are publicly exposed as OpenClaw instances. Scans all 3,357 pages of exposed instances to check for the presence of target IPs. --- # Exposure Sentinel A sentinel that watches over the OpenClaw Exposure Watchboard, checking if your IPs are publicly listed as exposed instances. ## When to Use - **Security auditing**: Check if your infrastructure IPs are accidentally exposed - **Proactive monitoring**: Verify exposure status of critical endpoints - **Incident response**: Confirm if a suspected exposure is publicly known ## Quick Start ### Check a Single IP ```bash python3 skills/exposure-sentinel/scripts/check_ip.py 1.2.3.4 ``` ### Check Multiple IPs ```bash python3 skills/exposure-sentinel/scripts/check_ip.py 1.2.3.4 5.6.7.8 ``` ### With Progress Output ```bash python3 skills/exposure-sentinel/scripts/check_ip.py 1.2.3.4 -v ``` ### JSON Output (for automation) ```bash python3 skills/exposure-sentinel/scripts/check_ip.py 1.2.3.4 --json ``` ## How It Works 1. **Concurrent scanning**: Uses 50 concurrent connections to scan all 3,357 pages 2. **Pattern matching**: Handles both full IPs and partially masked IPs (e.g., `1.2.3.•••`) 3. **Complete coverage**: Checks every page of the exposure database 4. **Typical runtime**: ~85-95 seconds for full scan ## Interpreting Results - **✅ Not found**: IP is not listed in the exposure database (safe) - **⚠️ EXPOSED**: IP appears on the watchboard with page links for details ## Technical Details - **Source**: https://openclaw.allegro.earth - **Total pages**: 3,357 (100 records per page) - **Total records**: ~335,000 exposed instances - **Scan rate**: ~40 pages/second ## About OpenClaw Exposure Watchboard This is a public security research database listing publicly reachable OpenClaw instances for defensive awareness. If your IP appears here, it means: 1. The instance is directly exposed to the internet 2. Authentication may be disabled or weak 3. Immediate action recommended: enable auth, restrict access, patch


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: jobzhao15/enhance-explore-mode (version 1.0.0)

--- name: explore-mode description: "深度探索模式 — 系统性调研代码库、系统或话题，只读不改。借鉴 Claude Code 的 Explore Agent。" homepage: https://github.com/jobzhao15/openclaw-enhance metadata: { "openclaw": { "emoji": "🔍", "requires": { "bins": [] } } } --- # 探索模式 (Explore Mode) 进入只读深度探索模式，在回答前系统性地调研。 ## 使用时机 ✅ **使用此技能当：** - "帮我了解一下这个项目的架构" - "这个功能是怎么实现的？" - "调查一下为什么会出这个 bug" - 需要全面理解一个不熟悉的代码库或系统 ❌ **不要使用当：** - 已经很了解要查的内容 - 用户只是问一个简单的事实性问题 ## 探索流程 ### 1. 确定探索目标 - 要回答什么问题？ - 探索的范围是什么？（哪些目录/文件/系统） - 需要达到什么深度？ ### 2. 广度优先扫描 - 先看目录结构，建立全局认知 - 读 README、配置文件、入口文件 - 识别主要模块和它们的关系 ### 3. 深度定向调研 - 针对目标问题，深入相关模块 - 跟踪关键调用链 - 查看测试用例理解预期行为 - 查看 git log 了解变更历史 ### 4. 输出探索报告 结构化输出： ``` ## 探索报告: [主题] ### 概述 一段话总结发现 ### 架构/实现 - 关键文件和它们的职责 - 核心数据流/调用链 - 重要的设计决策 ### 发现 - 发现1: ... - 发现2: ... ### 回答 [针对原始问题的直接回答] ### 建议（可选） 如果发现了问题或改进空间 ``` ## 核心原则 - **只读不改** — 探索阶段不修改任何文件 - **系统性** — 不要只看一个文件就下结论，要交叉验证 - **记录路径** — 给出具体的文件路径和行号，方便用户定位 - **区分事实和推测** — 明确标注哪些是从代码看到的，哪些是推断的


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: meowlegemy-sudo/chrome-relay (version 1.0.0)

--- name: chrome-relay version: 1.0.0 description: | Control the user's local Chrome browser via OpenClaw Browser Relay extension. Use when: (1) User asks to control/access their browser (2) User wants to automate browser actions (click, type, navigate, screenshot) (3) User wants to read page content from a specific Chrome tab (4) User wants to use existing logged-in sessions on websites (5) User provides a Chrome tab URL and wants you to interact with it Not for: headless browser automation without user session (use browser tool with default profile) --- # Chrome Relay Browser Control Control the user's local Chrome browser through the OpenClaw Browser Relay extension. This provides access to the user's real logged-in browser sessions. ## Setup (First Time) If user doesn't have Browser Relay extension installed: 1. **Get extension path:** ``` ~/.openclaw/browser/chrome-extension ``` Or run: `open ~/.openclaw/browser/chrome-extension` (macOS) 2. **Install in Chrome:** - Open `chrome://extensions` - Enable "Developer mode" (top right) - Click "Load unpacked" - Select the extension folder 3. **Get Gateway token:** ``` openclaw config get gateway.auth.token ``` 4. **Configure extension:** - Click extension icon → Settings - Enter the gateway token - Save 5. **Connect:** - Open the Chrome tab you want controlled - Click the extension icon to attach (badge shows ON) ## Usage ### Check Connected Tabs ```bash openclaw browser tabs --profile chrome-relay ``` Or use the tool: ``` browser(action=tabs, profile=chrome-relay) ``` ### Read Page Content ``` browser(action=snapshot, profile=chrome-relay, targetId=<targetId>) ``` ### Navigate ``` browser(action=navigate, profile=chrome-relay, targetId=<targetId>, url="https://...") ``` ### Interact with Page **Note:** aria-ref based selectors have reliability issues in chrome-relay mode. Prefer JavaScript evaluation for complex interactions: ```javascript // Click element browser(action=act, kind=evaluate, profile=chrome-relay, fn="document.querySelector('selector').click()") // Type in input browser(action=act, kind=evaluate, profile=chrome-relay, fn="document.querySelector('input').value = 'text'") // Get element info browser(action=act, kind=evaluate, profile=chrome-relay, fn="document.querySelector('selector').innerText") ``` ### Limitations - aria-ref selectors may timeout; use JavaScript evaluate instead - Extension must be attached (icon shows ON) for each tab - Only works with Chrome browser - Connection port: 18792 ## Troubleshooting **Red ! badge on extension:** - Gateway not running → start with `openclaw gateway start` - Token mismatch → verify token in extension settings **Can't find element:** - Page may have loaded new DOM → re-snapshot - Use browser devtools console to find selectors first


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: utromaya-code/monetization-ai (version 1.0.0)

--- name: monetization-pipeline description: Designs and runs safe monetization workflows (lead research, outreach drafts, content-to-offer loops, reporting) using OpenClaw + n8n + communication channels. Use for earning-focused automation while requiring confirmation for money movement. --- # Monetization Pipeline ## Goal Turn agent activity into measurable revenue using controlled workflows. ## Core Pipelines 1. **Lead Discovery** - Find niche leads (web, communities, directories) - Normalize into a structured table (name, channel, need, priority) 2. **Offer Packaging** - Generate tailored offer text and pricing options - Prepare concise outreach drafts 3. **Outreach Execution** - Send only approved messages (email/chat/social) - Track replies and follow-ups 4. **Conversion Tracking** - Move responses into CRM/Notion/Sheet - Weekly conversion report ## Recommended Stack - OpenClaw for reasoning/orchestration - n8n for integrations and scheduled jobs - Telegram for command/control - Docs/Sheets/Notion for pipeline visibility ## Safety Policy (Critical) Never execute financial actions without explicit confirmation: - No transfers - No exchange orders - No card/payments - No irreversible account actions Before any money-impacting action, require: 1. Clear action summary 2. Amount + destination 3. User confirmation phrase: `CONFIRM MONEY ACTION` ## Daily Command Set - `run lead scan <niche>` - `draft 10 outreach messages for <offer>` - `show conversion report` - `prepare follow-ups for stale leads` ## Output Format ```markdown ## Revenue Ops Snapshot - Leads found: <n> - Qualified: <n> - Outreach sent: <n> - Replies: <n> - Estimated pipeline value: <amount> ## Highest-Leverage Action - <single next action> ``` ## n8n Handoff Spec For each workflow, define: - trigger - inputs schema - steps - output schema - retry policy - alert channel Keep all workflows idempotent where possible. ## Guardrails - No cold spam bursts; rate-limit outreach. - Respect platform rules and legal constraints. - Keep an audit trail for every outbound action.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: micromsf/novel-multi-agent-skill (version 1.0.0)

# 📚 多智能体小说创作系统 v1.0 ## 技能信息 - **ID**: novel-multi-agent - **名称**: 多智能体小说创作系统 - **版本**: 1.0 - **作者**: 小说创作总策划团队 - **标签**: 小说、创作、多智能体、协作、自动化 ## 🌟 核心功能 一套完整的、经过生产验证的小说创作自动化流水线，由5个专业智能体协同工作： | 智能体 | 角色 | 职责 | |--------|------|------| | 📋 **novel-director** | 总策划 | 项目统筹、质量把控、流程调度 | | 🌍 **novel-world-builder** | 世界观构建师 | 设计完整世界观、设定、规则 | | 👥 **novel-character-designer** | 角色设计师 | 设计立体、有辨识度的人物 | | 📑 **novel-plot-planner** | 情节策划师 | 设计分章大纲、节奏把控 | | ✍️ **novel-chapter-writer** | 章节写作智能体 | 高质量正文创作 | | 🔍 **novel-quality-reviewer** | 质量评审官 | 五维评分、修改建议、质量把关 | ## 🎯 六步标准闭环流程 ``` 第0步 📋 总策划制定总纲 ↓ 第1步 🌍 世界观构建智能体 → 输出《世界观设定》 ↓ ✅ 验收 第2步 👥 角色设计智能体 → 输出《角色档案》 ↓ ✅ 验收 第3步 📑 情节策划智能体 → 输出《分章大纲》 ↓ ✅ 验收 第4步 ✍️ 写作智能体 → 输出《正文初稿》 ↓ 第5步 🔍 质量评审智能体 → 输出《评审报告》+ 评分 ↓ 第6步 ✍️ 写作智能体 → 根据评审意见优化 → 《最终定稿》 ``` ## 📦 技能包内容 ``` ├── SKILL.md # 本文件 ├── README.md # 详细使用说明 ├── QUICKSTART.md # 5分钟快速上手 ├── templates/ # 标准化输出模板 ├── agents/ # 5个智能体的完整配置 ├── workflow/ # 一键执行脚本（6步全流程） └── rules/ # 核心质量规则库 ``` ## 🚀 快速开始 ### 1. 安装技能 ```bash # 将本目录复制到 OpenClaw 技能目录 cp -r novel-multi-agent-skill ~/.openclaw/skills/ ``` ### 2. 初始化项目 ```bash cd novel-multi-agent-skill/workflow ./init-project.sh ../my-novel-project "我的小说名字" ``` ### 3. 运行完整流水线 ```bash ./run-full-pipeline.sh ../my-novel-project ``` ### 4. 或者分步执行 ```bash ./step1-world.sh ../my-novel-project ./step2-character.sh ../my-novel-project ./step3-plot.sh ../my-novel-project ./step4-write.sh ../my-novel-project 1-10 ./step5-review.sh ../my-novel-project 1-10 ``` ## ✅ 核心质量标准 | 标准 | 要求 | |------|------| | 章节字数 | 严格 1800-2200 字/章 | | 质量评分 | 单章评分 ≥ 40 分才能通过 | | 内容红线 | 真实地名/姓名/敏感事件零容忍 | | 一致性 | 所有章节必须严格遵循世界观和角色设定 | ## 📊 质量评分体系 | 维度 | 权重 | 评分标准 | |------|------|---------| | 文笔流畅度 | 20% | 语言自然、生动、无AI痕迹 | | 人物塑造 | 20% | 性格鲜明、行为逻辑自洽 | | 情节节奏 | 20% | 节奏合理、爽点密集、钩子有力 | | 逻辑严谨性 | 20% | 无矛盾、符合设定、因果合理 | | 创意新颖度 | 20% | 不套路、有新意、有记忆点 | ## ⚙️ 配置要求 ### 前置依赖 - OpenClaw ≥ 1.0.0 - 已配置好默认大模型（推荐使用深度思考模型） - 有文件读写权限 ### 推荐模型配置 - **世界观/角色/情节**: 深度思考模型（保证逻辑严密） - **正文写作**: 创意型模型（保证文笔生动） - **质量评审**: 严谨型模型（保证客观公正） ## 🎨 支持的题材类型 ✅ 都市言情 ✅ 都市重生 ✅ 商战职场 ✅ 悬疑推理 ✅ 玄幻奇幻 ✅ 仙侠修真 ✅ 历史穿越 ✅ 科幻未来 ✅ 游戏竞技 ✅ 军事战争 ✅ 恐怖惊悚 ✅ 校园青春 ## 📈 性能指标 - **单章创作时间**: 约 5-10 分钟 - **单章评审时间**: 约 3-5 分钟 - **日产能**: 约 20-30 章（4-6 万字） - **一次性通过率**: ≥ 90% ## 🔧 高级功能 ### 批量创作模式 ```bash # 一次性创作10章 ./step4-write.sh ../my-novel-project 1-10 ``` ### 增量创作模式 ```bash # 写完第一批，规划下一批 ./step3-plot.sh ../my-novel-project 11-20 ./step4-write.sh ../my-novel-project 11-20 ``` ### 自定义质量标准 编辑 `rules/质量评分标准.md`，调整各维度权重和评分细则。 ## 📝 版本历史 ### v1.0 (2026-05-11) - ✅ 六步标准闭环流程完整跑通 - ✅ 5个专业智能体全部经过生产验证 - ✅ 核心质量规则体系建立 - ✅ 《重生1996》前20章验证通过 - ✅ 质量评分稳定 90+ 分 ## 🤝 技术支持 如遇到问题，请检查： 1. OpenClaw 版本是否 ≥ 1.0.0 2. 所有智能体是否已正确配置 3. 文件目录权限是否正确 4. 大模型 API 是否正常可用 --- **祝您创作愉快！** 🎉


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: walioo/morpho-base-operator (version 0.1.0)

# Morpho Base Operator Use this skill to operate a Base-first Morpho mandated vault workflow in a registry-first way. The active production-candidate validation chain is Base. BSC is retained only as reviewed historical empty-scope context, and `allowMainnetExecution` stays `false` by default. ## Required sequence 1. Load the configured registry file. 2. Verify registry addresses before planning. 3. Snapshot current state. 4. Build a deterministic plan for a registered market only. 5. Collect the authority signature outside the host. 6. Execute through the pinned mandated MCP stack. 7. Reconcile and archive the execution report. Never perform dynamic market discovery in the write path. Users must supply their own local configuration (RPC, operator private key, and any active vault identifiers) outside the published skill bundle.


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

# daily-health-report Description: - Generates and publishes a daily system health report from the Raspberry Pi, including uptime, memory, swap, load, disk, and temperature metrics. Purpose: - Provide a consistent, automated health snapshot for quick review and logging. Inputs: - None (pulls data from the local system at run time via health_report.sh). Outputs: - A human-readable health report text block and a log entry. Dependencies: - /home/welderjustin/.openclaw/workspace/scripts/health_report.sh - /home/welderjustin/.openclaw/workspace/logs/ Invocation: - Run the health_report script and publish its output to the chosen channel (or integrate with the main agent).


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: avmw2025/amazon-review-monitor (version 1.0.0)

# Amazon Review Monitor — Track, Analyze, Respond **Never miss a negative review again. AI-drafted responses included.** ## Description Monitor reviews for any ASIN. Tracks rating distribution, analyzes sentiment, identifies negative themes, and drafts professional seller responses. Set up alerts for new negative reviews. ## When to Use - User wants to monitor Amazon product reviews - User received a negative review and needs a response - User wants sentiment analysis on their product reviews - User asks about review trends or customer feedback ## Usage ```bash # Analyze reviews for an ASIN cd <skill_dir>/scripts && python3 monitor.py B0XXXXXXXXX # Analyze 5 pages of reviews on UK marketplace cd <skill_dir>/scripts && python3 monitor.py B0XXXXXXXXX co.uk 5 ``` ## What It Does - Scrapes recent reviews (configurable depth) - Shows rating distribution (5⭐ to 1⭐ with visual bars) - Calculates average rating - Sentiment analysis (positive/negative word detection) - Identifies top positive and negative themes - Highlights negative reviews needing responses - **Drafts professional seller responses** based on complaint type ## Response Templates Cover - Product freshness/quality issues - Shipping damage - Wrong item/expectations mismatch - General dissatisfaction ## No Dependencies Pure Python 3. No API keys. No pip install needed.


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