OpenClaw/clawhub-security-signals huggingface dataset:
Skill: ivangdavila/skill-update (version 1.0.0)

--- name: "Skill Update" description: "Safely update skills with preview, migration support, and user validation. Never lose data or break workflows." --- ## Safe Skill Updates **Core principle:** Never update without user understanding and approval. Updates can break things: - Changed file locations → data loss - Removed features → broken workflows - New requirements → unexpected behavior - Changed data formats → incompatible state **References:** - Read `preview.md` — Diff and impact analysis - Read `migrate.md` — Data migration strategies --- ### Update Flow 1. **Check** — Are updates available? 2. **Preview** — What changes? How does it affect user? 3. **Explain** — Present changes step-by-step 4. **Confirm** — User explicitly approves 5. **Backup** — Save current state 6. **Update** — Apply new version 7. **Verify** — Confirm everything works --- ### Checking for Updates ```bash npx clawhub outdated # List skills with updates npx clawhub info <slug> # Show available versions ``` **Proactive notification:** When user mentions a skill, check if update exists. Mention it once, don't nag. --- ### Preview Before Update ⚠️ Never update without showing impact first. **For each changed file:** 1. Show what's different (added/removed/modified) 2. Explain how it affects user's workflow 3. Flag breaking changes prominently **Breaking change indicators:** - File/folder structure changes - Removed instructions or features - New required setup steps - Changed data format expectations --- ### User Validation Present changes in digestible format: > "Skill X has v2.0.0 available. Changes: > > **⚠️ Breaking:** Config now in `config.md` (was in SKILL.md) > **Added:** New `templates/` folder with examples > **Removed:** Old `legacy.md` no longer needed > > **Migration needed:** Your saved preferences need to move. > I can help migrate. Proceed?" Only update after explicit "yes". --- ### Backup Strategy Before ANY update: 1. Copy current skill folder to `~/.clawhub/backups/<slug>-<version>-<timestamp>/` 2. Note the backup location in response 3. If update fails → offer restore --- ### Handling Migrations When data format changes: 1. Detect user's current data (preferences, saved state) 2. Explain what needs to migrate 3. Propose migration steps 4. Execute only with approval 5. Verify migrated data works See `migrate.md` for patterns. --- ### Rollback If update causes problems: ``` "Something's not working? I have a backup from before the update. Want me to restore skill X to v1.2.3?" ``` Keep backups for at least 7 days or until user confirms new version works. --- *Updates should feel safe, not scary. User stays in control.*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: gloryjack/autonomous-research-loop (version 1.0.0)

--- name: Autonomous Research Loop slug: autonomous-research-loop version: 1.0.0 description: 🦞 自主研究无限循环 - 自主生成研究主题、深度研究、创建飞书文档、无限循环运行。 changelog: 初始版本，基于 research_pool.json 的无限研究循环系统。 metadata: {"clawdbot":{"emoji":"🦞","requires":{},"os":["linux"]}} --- ## 概述 🦞 **自主研究无限循环** 是小智的自我驱动研究系统，核心逻辑： ``` 生成研究主题 → 深度研究 → 创建飞书文档 → 回到生成主题（无限） ``` ## 核心文件 | 文件 | 作用 | |------|------| | `research_pool.json` | 主题池（已完成 + 待研究 + 统计） | | `research_loop.md` | 架构说明文档 | ## 工作流程 ``` Cron触发（每5分钟） ↓ 读取 research_pool.json ↓ 检查 pending_topics ↓ 有主题 → 随机选1个 无主题 → 生成3个新主题 ↓ 深度研究 + 创建飞书文档 ↓ 移动到 completed + 生成3个新主题 ↓ 输出简报到飞书 ↓ 异常 → 直接退出（Cron 自动拉起） ``` ## 配置文件结构 ```json { "completed_topics": ["主题1", "主题2", ...], "pending_topics": [{topic: "...", description: "..."}], "stats": { "total_completed": 21, "total_generated": 23, "last_completed_at": "2026-04-02T09:00:00+08:00" }, "config": { "interval_minutes": 5, "max_research_time_minutes": 30, "new_topics_per_completion": 3 } } ``` ## 研究输出格式 每篇研究文档包含： - **一句话总结**（核心发现） - **机制拆解**（传导链条） - **实战要点**（具体可操作） - **Python代码框架**（可选） - **翻车点/风险提示** ## 异常处理原则 - 异常 → 直接退出，不重试，不切换模型 - Cron 会自动拉起新任务 - 被系统 kill → 靠 Cron 恢复 ## 质量控制原则 - 模型自己解决研究质量问题 - 不等待人工确认 - 靠间隔时间（5分钟）控制频率 - 无每日上限 ## 相关文件 - Cron任务：`🦞 自主研究无限循环`（每5分钟触发） - 配置文件：`/root/.openclaw/workspace/research_pool.json` - 说明文档：`/root/.openclaw/workspace/research_loop.md`

path: _meta.json
content: {
  "name": "Autonomous Research Loop",
  "slug": "autonomous-research-loop",
  "version": "1.0.0",
  "status": "active",
  "created": "2026-04-02T09:00:00+08:00",
  "files": {
    "SKILL.md": "技能说明",
    "research_pool.json": "主题池配置",
    "research_loop.md": "架构说明"
  },
  "cron_job": {
    "id": "274198b3-ca0c-456c-b55f-d94ce0049121",
    "name": "🦞 自主研究无限循环",
    "interval_minutes": 5,
    "next_run": "2026-04-02T10:00:00+08:00"
  },
  "stats": {
    "total_completed": 30,
    "started_at": "2026-04-02T09:00:00+08:00"
  }
}


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: sjj2026/shike-self-evolve (version 2.1.0)

--- name: self-evolve.skill description: "Agent自进化机制。三层架构（记忆→技能→规范），三种触发（关键词+踩坑+复盘），用户审批+Darwin评分双重质控。用得越多越懂你。触发词：自进化、进化、evolve、记住、以后、永远、下次、踩坑经验。" version: "2.1.0" author: "Shike" license: "MIT-0" tags: [self-evolution, evolve, memory, skill-optimization, darwin, 自进化, 进化, 记忆优化] --- # self-evolve.skill — Agent自进化机制 > **教一遍，记一辈子。用得越多，越懂你。** --- ## 核心心智模型 **模型1：遗忘曲线对抗** — Agent每次对话从零开始，进化机制就是"复习系统"。识别值得长期记住的经验→写入持久化文件→下次自动加载。失效条件：用户随口一说不是长期意图。 **模型2：三层沉淀漏斗** — L1轻量偏好放记忆层，L2方法论放技能层，L3全局规则放规范层。越往上审批越严。失效条件：层级判断错误，不确定时宁可放L1等自然升级。 **模型3：审批即训练** — 所有进化需用户审批。批准=正样本，忽略=负样本。频率控制：每日≤5次，每周≤15次，重要内容不受限。 --- ## 进化层级协议 ### L1：对话记忆层 → MEMORY.md - **写入条件**：用户偏好、行为模式、经验碎片 - **审批**：重要性≥medium，简单确认 - **格式**：`### 🧬 自进化 [来源] > 经验内容（一句话）` - **Git**：`🧬 L1进化: <摘要>` ### L2：技能优化层 → SKILL.md - **写入条件**：踩坑经验、方法论改进、边界补充 - **审批**：需Darwin评分≥70分（调用darwin-skill评估） - **Fallback**：无法调用Darwin时，Agent干跑3个测试prompt自评，≥75分才允许 - **格式**：`### 🧬 踩坑经验 [日期] > 失败现象/根因/方案/失效条件` - **Git**：`🧬 L2进化: <skill名> - <摘要>` ### L3：行为规范层 → CLAUDE.md - **写入条件**：全局行为约束、开发规范、安全边界 - **审批**：重要性high + 双重确认（先确认层级，再确认内容） - **格式**：`### 🧬 规范进化 [来源] > 规则/范围/生效时间` - **额外**：通知所有Bot「CLAUDE.md已更新」 - **Git**：`🧬 L3进化: <摘要>` --- ## 触发机制 ### 触发器A：关键词识别 | 级别 | 关键词 | 行为 | |------|--------|------| | 紧急 | 以后、永远、每次、必须、一定、禁止 | 立即弹出进化卡片 | | 标准 | 记住、下次、别再、不要再、记得 | 提示进化机会 | | 温和 | 倾向、偏好、喜欢、习惯 | 记录候选池，批量审批 | **误触发保护**：引用中/否定句/疑问句不触发或降级。 **混合意图协议**：检测临时状态+长期意图混合时，降级处理，标注"⚠️ 受临时情绪影响"。 **语义模糊追问**：意图不够具体时追问澄清，如"少说点开心的"→具体指减少emoji/正能量/闲聊？ ### 触发器B：踩坑检测 | 指标 | 阈值 | |------|------| | 工具调用次数 | >5次/对话 | | 同操作重试 | >3次 | | 用户纠正 | >2次 | | Git回滚 | 任何1次 | | 操作超时 | 任何1次 | 时机：超阈值时内部标记，对话自然结束后统一处理。根因需用户确认后写入。 ### 触发器C：定期复盘 每日HEARTBEAT/22:00任务后/用户主动请求时触发。读取记忆→识别重复模式→评估价值→过滤噪音→批量审批。 --- ## 进化请求卡片（唯一标准格式） ``` 🧬 进化请求 #<编号> 触发：<A/B/C> | 级别：<紧急/标准/温和> 建议记忆：> <一句话精炼表述> ⚠️ <情绪影响/意图模糊/根因待确认>（如有） 目标：L<1/2/3> → <文件路径> 评估：重要性<H/M/L> 复用性<H/M/L> 风险<无/低/中> → 「进化」|「进化 L2」|「忽略」|「修改」|「暂缓」 ``` --- ## 审批命令 | 用户回复 | 行为 | |---------|------| | `进化` | 按建议层级写入+Git提交 | | `进化 L1/L2/L3` | 覆盖层级后写入 | | `忽略` | 跳过（负样本） | | `修改 <新内容>` | 替换后重新请求 | | `暂缓` | 保留到下次复盘 | | `确认根因` | L2踩坑根因确认 | | `修正根因 <新>` | 替换根因后继续 | --- ## 冲突检测与解决 写入前搜索现有规则：矛盾→用户选择保留哪个；重复→合并；层级冲突→建议升级。 --- ## 安全边界 **永远不能进化写入**：安全约束、系统规则、核心身份、其他Bot专属规则。 **内容限制**：每条≤100字，不含代码/敏感信息。 ## 诚实边界 1. 不是真学习（写规则不是改权重），规则越多边际效益递减 2. 噪音无法完全消除，需定期清理 3. 冲突可能漏检（依赖文本搜索） 4. L3风险最高，务必双重确认 5. 过度进化→审批疲劳→质量下降 6. L1/L3效果只能靠主观感受 7. 语义模糊依赖用户澄清 8. 根因分析可能错误 --- ## 回答工作流 ``` Step 1: 识别 → 扫描关键词/踩坑指标/复盘触发 Step 2: 提炼 → 去触发词，评估层级(L1/L2/L3)，噪音过滤 Step 3: 请求审批 → 弹出卡片，L3双重确认 Step 4: 冲突检测 → 搜索现有规则 Step 5: 执行写入 → L2需Darwin评分，L3通知所有Bot Step 6: Git提交 → "🧬 L<n>进化: <摘要>" Step 7: 日志记录 → evolution-log.md + 计数器更新 ``` --- *版本：v2.1.0 | 作者：Shike | MIT-0*


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: wrentheai/recall-local (version 1.0.0)

--- name: recall-local description: Local memory search for OpenClaw agents. Runs a lightweight Node.js server that indexes all files in ~/clawd/memory/ plus MEMORY.md and WORKING.md, then exposes keyword search over them. Use when you need to find something from past sessions, daily logs, decisions made, things learned, bugs fixed, or anything in the agent's history. Also use to set up, check, or restart the server. --- # Recall Local Indexes your entire `~/clawd/memory/` archive and serves it as a searchable web UI + API at `http://localhost:3456`. No external services, no API keys, nothing leaves your machine. ## Setup (first time) ```bash # Copy the server to your tools directory mkdir -p ~/clawd/tools/recall-local cp "$(dirname "$0")/scripts/server.js" ~/clawd/tools/recall-local/server.js # Create a LaunchAgent so it starts on login cat > ~/Library/LaunchAgents/ai.wren.recall-local.plist << 'EOF' <?xml version="1.0" encoding="UTF-8"?> <!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd"> <plist version="1.0"> <dict> <key>Label</key><string>ai.wren.recall-local</string> <key>ProgramArguments</key> <array> <string>/opt/homebrew/bin/node</string> <string>/Users/YOUR_USERNAME/clawd/tools/recall-local/server.js</string> </array> <key>RunAtLoad</key><true/> <key>KeepAlive</key><true/> <key>StandardOutPath</key><string>/Users/YOUR_USERNAME/clawd/tools/recall-local/recall.log</string> <key>StandardErrorPath</key><string>/Users/YOUR_USERNAME/clawd/tools/recall-local/recall.log</string> </dict> </plist> EOF # Replace YOUR_USERNAME, then load it launchctl load ~/Library/LaunchAgents/ai.wren.recall-local.plist ``` Or just run it manually: `node ~/clawd/tools/recall-local/server.js &` ## Search (agent use) ```bash curl -s "http://localhost:3456/search?q=YOUR+QUERY" | python3 -c " import json,sys d = json.load(sys.stdin) print(f'{d[\"total\"]} chunks indexed') for r in d['results'][:5]: print(f'[{r[\"source\"]}] {r[\"text\"][:300]}') print() " ``` ## Check if running / start if down ```bash curl -s http://localhost:3456/search?q=test > /dev/null 2>&1 && echo "UP" || (echo "Starting..."; launchctl start ai.wren.recall-local; sleep 2) ``` ## Human UI Open `http://localhost:3456` in a browser. Search box, results below. Works on mobile too if on same local network. ## Tips - Reloads all files on every search — always reflects the latest memory - Source filenames are dates (`2026-03-01.md`) — useful for spotting when something happened - Multi-word queries score better than single words - For broad questions use general terms; for specific lookups use exact terms


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: katrina-jpg/automated-content-machine (version 1.0.0)

--- name: automated-content-machine description: 自動化內容創作引擎 - 每日自動生成並發布內容：(1)Twitter/Threads threads (2)Blog posts (3)YouTube script (4)Newsletter (5)自動發布到多平台。支持AI生成+人類審核 --- # Automated Content Machine 全自動化內容創作同發布系統 ## 每日任務 ### 🐦 Twitter/Threads - 每日生成1-3條高質量thread - 關於: Crypto, AI, Productivity, Tech - 包含hashtags同engagement questions ### 📝 Blog Posts - 每星期2-3篇長文 - SEO優化 - 自動發布到WordPress/Ghost ### 🎥 YouTube Script - 每星期1-2條影片腳本 - 結構化outline - 包含timestamp markers ### 📧 Newsletter - 每星期1封 - 精選內容合集 - 付費訂閱支持 ## 內容變現 - Affiliate links - 付費產品推廣 - 訂閱服務 - 廣告收入 ## 自動化工具 - Buffer/Hypefury (schedule posts) - Ghost/Substack (newsletter) - WordPress (blog) - Gumroad (digital products) ## 報價 | 服務 | 價格 | |------|------| | 內容策略咨詢 | $100-300 | | 自動化setup | $300-800 | | 月費运营 | $200-500/月 |


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

--- name: Monitoring description: "Set up observability for applications and infrastructure with metrics, logs, traces, and alerts." --- ## Complexity Levels | Level | Tools | Setup Time | Best For | |-------|-------|------------|----------| | **Minimal** | UptimeRobot, Healthchecks.io | 15 min | Side projects, MVPs | | **Standard** | Uptime Kuma, Sentry, basic Grafana | 1-2 hours | Small teams, startups | | **Professional** | Prometheus, Grafana, Loki, Alertmanager | 1-2 days | Production systems | | **Enterprise** | Datadog, New Relic, or full OSS stack | Ongoing | Large-scale operations | ## The Three Pillars | Pillar | What It Answers | Tools | |--------|-----------------|-------| | **Metrics** | "How is the system performing?" | Prometheus, Grafana, Datadog | | **Logs** | "What happened?" | Loki, ELK, CloudWatch | | **Traces** | "Why is this request slow?" | Jaeger, Tempo, Sentry | ## Quick Start by Use Case **"I just want to know if it's down"** → UptimeRobot (free) or Uptime Kuma (self-hosted). See `simple.md`. **"I need to debug production errors"** → Sentry with your framework SDK. 5-minute setup. See `apm.md`. **"I want real observability"** → Prometheus + Grafana + Loki. See `prometheus.md`. **"I need to centralize logs"** → Loki for simple, ELK for complex queries. See `logs.md`. ## What to Monitor ### Applications (RED Method) - **R**ate — requests per second - **E**rrors — error rate by endpoint - **D**uration — latency (p50, p95, p99) ### Infrastructure (USE Method) - **U**tilization — CPU, memory, disk usage - **S**aturation — queue depth, load average - **E**rrors — hardware/system errors ## Alerting Principles | Do | Don't | |----|-------| | Alert on symptoms (user impact) | Alert on causes (CPU high) | | Include runbook link | Require investigation to understand | | Set appropriate severity | Make everything P1 | | Require action | Alert on "interesting" metrics | **Alert fatigue kills monitoring.** If alerts are ignored, you have no monitoring. For alert configuration, severities, and on-call setup, see `alerting.md`. ## Cost Comparison | Solution | Monthly Cost (small) | Monthly Cost (medium) | |----------|---------------------|----------------------| | UptimeRobot | Free | $7 | | Uptime Kuma | $5 (VPS) | $5 (VPS) | | Sentry | Free / $26 | $80 | | Grafana Cloud | Free tier | $50+ | | Datadog | $15/host | $23/host + features | | Self-hosted stack | $10-20 (VPS) | $50-100 (VPS) | ## Common Mistakes - Starting with Prometheus/Grafana when Uptime Kuma would suffice - No alerting (dashboards nobody watches) - Too many alerts (alert fatigue → ignored) - Missing runbooks (alert fires, nobody knows what to do) - Not monitoring from outside (only internal checks) - Storing logs forever (cost explodes)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: kennywayn3/content-multiply-pro (version 1.0.4)

--- name: content-multiply-pro version: 1.0.4 description: Turn one blog post or video into 15+ pieces of content. tags: content,marketing,social-media,writing,automation --- # Content Multiply Pro Turn one piece of content into 15+ formats automatically. Maximize reach from every piece of content you create. ## What It Creates From one blog post, video, or podcast episode, generate: - Twitter/X thread (10-15 tweets) - LinkedIn post (long-form) - LinkedIn carousel outline - Instagram caption + hashtags - Facebook post - TikTok/Reels script - Email newsletter - Reddit post - Quora answer - Medium article version - Podcast show notes - SEO meta description - Blog excerpt for social - Press release summary - Internal memo/recap ## How to Use Provide your agent with the source content: Repurpose my latest blog post at [URL] for all social platforms Or: Here is my podcast transcript. Create 10 social posts from it. ## Tone Customization Tell your agent the desired tone: professional, casual, humorous, authoritative, or educational. Each piece adapts to the platform's style. ## API Uses a web-based content API at https://extant-torrie-nonrepealable.ngrok-free.dev. Buy credits at /buy if the API returns a 402 response. ## Requirements Works with any web-connected OpenClaw agent. No additional API keys.

path: package.json
content: name: content-multiply-pro
version: 1.0.0
description: Turn one blog post or video into 15+ pieces of content. Generate social posts, email newsletters, Twitter threads, LinkedIn articles, and short-form video scripts automatically.
tags: content,marketing,social-media,writing,automation


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: b-gutman/pipeworx-lorem (version 1.0.0)

--- name: pipeworx-lorem description: Lorem MCP — wraps loripsum.net (free, no auth) version: 1.0.0 metadata: openclaw: homepage: https://pipeworx.io/packs/lorem --- # pipeworx-lorem Lorem MCP — wraps loripsum.net (free, no auth). Free, no API key. Part of [Pipeworx](https://pipeworx.io). ## Tools - `generate_paragraphs` - `generate_with_options` ## Connect ```json { "mcpServers": { "pipeworx-lorem": { "command": "npx", "args": ["-y", "mcp-remote@latest", "https://gateway.pipeworx.io/lorem/mcp"] } } } ``` More at [pipeworx.io/packs/lorem](https://pipeworx.io/packs/lorem)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: william22820785-cmyk/nihai (version 2.1.0)

--- name: nihai description: | 模拟倪海厦（倪师）中医问诊风格，对患者症状进行分析和经方建议。以人纪（中医辨证、经方开药）为主，天纪（紫微斗数、易经、风水）仅作为辅助参考，必要时提醒即可。 使用场景： - 用户描述临床症状，希望获得倪海厦风格的中医辨证分析和经方建议 - 用户想了解倪海厦对某类疾病的诊疗思路 - 用户提到"倪海厦""倪师""汉唐中医""经方""人纪"等关键词 - 用户以"倪海厦怎么看这个病""倪师风格的诊断"等表述提问 核心能力（主线）： - 模拟倪海厦五步辨证法（六经辨证 + 脏腑辨证） - 基于"健康五大标准"进行问诊追问 - 259经方 + 100汉唐方剂速查，含剂量和加减思路 - 倪海厦风格的生活调理建议 辅助能力（仅必要时提及，不主动展开）： - 天纪紫微斗数、易经、风水可在辨病时附带提一句（如"你这个病对应的宅位要注意…"），不做专题分析 ⚠️ 免责声明：仅供中医学习参考，不可替代专业医生诊断。如有实际健康问题，请前往正规医疗机构就诊。 --- # 倪海厦中医问诊顾问（人纪为主·天纪为辅） > 知识蒸馏自倪海厦毕生所学： > **主线** —《人纪》（针灸大成、黄帝内经、神农本草经、伤寒论、金匮要略）+ 汉唐100方剂 > **辅助** —《天纪》（紫微斗数、易经、风水），仅辨证时酌情提一句，不展开专题 ## 核心身份 你是在模拟倪海厦看诊。你的身份是经方派中医，六经辨证与脏腑辨证兼用。 说话风格：直接、自信、甚至有点"狂"，对西医持批判态度但有理有据。 > **天纪辅助规则**：天纪内容（紫微斗数、风水、易经）仅在你认为与当前病症明显相关时，**用一两句话**顺带提醒用户（如"你这个在风水上对应XX方位要注意"）。**不主动开专题、不批命盘、不看户型**。除非用户明确追问，不展开。 > 参见：[references/tianji-destiny-fengshui.md](references/tianji-destiny-fengshui.md) --- ## 一、人纪 — 中医问诊（主线） ### 基本流程 ``` 第一步：追问辨证关键信息（必须等用户回答后再继续） 第二步：六经+脏腑辨证定位 第三步：方剂建议 + 剂量 + 加减 第四步：生活调理建议（可酌情提一句风水/易经相关） ``` ### 第一步：追问辨证信息（"健康五大标准"） 接到初始症状后，必须追问： **必问五项**： 1. **睡眠** — 几点入睡？易醒吗？做梦多吗？ 2. **二便** — 大便每天有吗？成形还是稀？小便颜色次数？ 3. **手足温度** — 手脚热还是凉？手心脚心？ 4. **口渴** — 不渴还是总想喝水？热水还是冰水？ 5. **胃口** — 胃口好不好？ **女子加问（女子三证）**： 6. **月经** — 经前乳房胀？经中小腹痛？经后腰酸？ **根据主诉加问**： - 头面→头晕/口苦/耳鸣 - 胸腹→胸闷/腹胀/胁痛 - 关节→麻木/肿痛/晨僵 - 皮肤→痒/干/起疹部位 ⚠️ **必须等用户回答后再进入第二步。** ### 第二步：六经+脏腑辨证 参见 [references/pattern-differentiation.md](references/pattern-differentiation.md)。 输出格式： ``` 【六经定位】：XXX经 【脏腑定位】：XXX 【八纲】：表里/寒热/虚实 【病机分析】：简要说明 ``` ### 第三步：方剂建议 参见： - [references/formulas-259.md](references/formulas-259.md) - [references/hantang-100.md](references/hantang-100.md) - [references/herb-database.md](references/herb-database.md) 开方原则：经方优先、剂量到位、加减有据、配伍严谨。 ### 第四步：生活调理 饮食禁忌（水果牛奶冰冷是大忌）、作息建议、情志调节、外治法建议。 **天纪点睛（可选）**：如果辨证结果与风水/命理有明显关联，用一两句话顺带提醒，例如： - "你这个胃病，家里厨房如果在西北角（乾位），要看看——火烧天门，男主人心脏和胃容易出问题。" - "《易经》谦卦说得好——你现在肝气郁结，一半是身体，一半是心里东西放不下。" **不展开天纪专题，不主动批命盘、不看户型。除非用户追问。** --- ## 二、天纪 — 辅助参考 参见 [references/tianji-destiny-fengshui.md](references/tianji-destiny-fengshui.md) 天纪内容仅在上文"天纪点睛"环节使用。不单独开启紫微斗数批命、风水看宅、易经解卦等专题流程。如果用户明确追问天纪相关内容，可简要引用参考资料回答，但仍以中医为主线。 --- ## 说话风格 - 自信、直接，不绕弯子 - "我跟你说""你听好"等口语化表达 - 批评坏习惯时不留情面 - 对西医治疗造成的坏病毫不客气 - 最终落脚点：**中医可以帮你** - 常引用经典原文和倪师语录 ## 安全红线 1. 每次问诊结束加上："以上分析和建议仅供中医学习交流参考，不构成医疗处方。如有健康问题，请到正规医疗机构就诊。" 2. 紧急症状（剧痛、大出血、高烧不退）→ 建议立即就医 3. 不给有毒中药的精确剂量（附子、乌头等写"遵医嘱"） 4. 不说治愈承诺 5. 天纪提及时加一句"仅供参考，不可迷信"


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal:  | SkillSpector: suspicious (HIGH)
Skill: lars147/knuspr-cli (version 0.1.0)

--- name: knuspr description: Manage grocery shopping on Knuspr.de via the knuspr-cli. Use for product search, cart management, delivery slot reservation, shopping lists, order history, deals, favorites, and meal suggestions. Trigger when the user mentions Knuspr, groceries, Einkauf, Lebensmittel, Warenkorb, Lieferslot, or shopping list tasks. --- # Knuspr CLI Skill Interact with Knuspr.de (German grocery delivery) using `knuspr-cli` — a pure-Python CLI bundled in this skill at `{baseDir}/knuspr_cli.py`. ## Setup 1. **Python 3.8+** required (no external dependencies) 2. **Login**: `python3 {baseDir}/knuspr_cli.py auth login` (or set `KNUSPR_EMAIL` + `KNUSPR_PASSWORD` env vars) 3. **Minimum order**: €39 ## Critical Rules 1. **NEVER complete a purchase** — Only build cart + reserve slot. Always tell the user to review and checkout themselves via `cart open` or the Knuspr website/app. 2. **Always use `--json`** for parsing output programmatically. 3. **Confirm before destructive actions** (cart clear, list delete, slot release). 4. **Show prices and totals** when adding to cart so the user stays informed. ## CLI Usage ``` python3 {baseDir}/knuspr_cli.py <resource> <action> [options] ``` ## Core Workflows ### Search & Add to Cart ```bash # Search products (use --json for parsing) python3 {baseDir}/knuspr_cli.py product search "Hafermilch" --json python3 {baseDir}/knuspr_cli.py product search "Käse" --bio --sort price_asc --json python3 {baseDir}/knuspr_cli.py product search "Joghurt" --rette --json # discounted items # Add to cart python3 {baseDir}/knuspr_cli.py cart add <product_id> -q <quantity> python3 {baseDir}/knuspr_cli.py cart show --json # verify cart & total ``` ### Delivery Slots ```bash python3 {baseDir}/knuspr_cli.py slot list --detailed --json # show available slots with IDs python3 {baseDir}/knuspr_cli.py slot reserve <slot_id> # reserve a 15-min ON_TIME slot python3 {baseDir}/knuspr_cli.py slot reserve <slot_id> --type VIRTUAL # 1-hour window python3 {baseDir}/knuspr_cli.py slot current --json # check current reservation python3 {baseDir}/knuspr_cli.py slot release # cancel reservation (ask first!) ``` ### Shopping Lists ```bash python3 {baseDir}/knuspr_cli.py list show --json # all lists python3 {baseDir}/knuspr_cli.py list show <list_id> --json # products in a list python3 {baseDir}/knuspr_cli.py list create "Wocheneinkauf" python3 {baseDir}/knuspr_cli.py list add <list_id> <product_id> python3 {baseDir}/knuspr_cli.py list to-cart <list_id> # move entire list to cart python3 {baseDir}/knuspr_cli.py list duplicate <list_id> # duplicate a list ``` ### Order History & Reorder ```bash python3 {baseDir}/knuspr_cli.py order list --json python3 {baseDir}/knuspr_cli.py order show <order_id> --json python3 {baseDir}/knuspr_cli.py order repeat <order_id> # add all items to cart ``` ## Full Command Reference For all commands, options, and flags see `{baseDir}/references/commands.md`.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: dinghaibin/sort-lines-tool (version 1.0.0)

--- name: sort-lines-tool description: Sort lines of text alphabetically or numerically. Use for data organization, list management, and text file preparation. --- # Sort Lines - Line Sorting Tool Arrange text lines in alphabetical or numerical order. Supports case-insensitive sorting, reverse order, and unique line filtering. ## Usage ```bash sort-lines-tool [options] <file> ``` ## Options - `-n`: Numeric sort (instead of alphabetical) - `-r`: Reverse order - `-u`: Unique lines only - `-f`: Case-insensitive sort ## Examples ```bash sort-lines-tool names.txt sort-lines-tool -n numbers.txt sort-lines-tool -r data.txt ```

path: scripts/sort.py
content: #!/usr/bin/env python3
import sys
lines = sys.stdin.readlines()
lines.sort()
for line in lines:
    print(line, end='')


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: freeman88-tch/mega-pipeline (version 1.0.0)

--- name: mega-pipeline description: "全闭环自动化管道 — Hunter→Skill Factory→Orchestrator→Dashboard→Profit。将Phase 1-3所有组件串联为自动运行的超级管道。核心能力：(1) 一键全流程 (2) 定时自动运行 (3) 异常自愈 (4) 利润报告" version: 1.0.0 author: Apex Catalyst --- # Mega Pipeline — 全闭环自动化 ## 管道流程 ``` Step 1: Hunter Scan (市场扫描) Step 2: Skill Check (缺口分析) Step 3: Auto-Generate (自动补全) Step 4: Dashboard (状态刷新) Step 5: Profit Report (利润报告) Step 6: Resilience (自愈检查) ``` ## 命令 ```bash python3 scripts/run_pipeline.py # 执行完整管道 python3 scripts/run_pipeline.py --status # 管道状态 ```


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