OpenClaw/clawhub-security-signals huggingface dataset:
Skill: omactiengartelle/magazine-cover-generator (version 1.0.1)

--- name: magazine-cover-generator description: Generate stunning AI magazine cover art in Vogue, TIME, GQ, and editorial styles. Perfect for fashion covers, lifestyle magazine mockups, parody covers, personal branding, social media viral posts, pet magazine covers, and mixed-media editorial collage designs with professional masthead typography and cover headlines via the Neta AI image generation API (free trial at neta.art/open). tools: Bash --- # Magazine Cover Generator Generate stunning AI magazine cover art in Vogue, TIME, GQ, and editorial styles. Perfect for fashion covers, lifestyle magazine mockups, parody covers, personal branding, social media viral posts, pet magazine covers, and mixed-media editorial collage designs with professional masthead typography and cover headlines. ## Token Requires a Neta API token (free trial at <https://www.neta.art/open/>). Pass it via the `--token` flag. ```bash node <script> "your prompt" --token YOUR_TOKEN ``` ## When to use Use when someone asks to generate or create ai magazine cover generator images. ## Quick start ```bash node magazinecovergenerator.js "your description here" --token YOUR_TOKEN ``` ## Options - `--size` — `portrait`, `landscape`, `square`, `tall` (default: `portrait`) - `--ref` — reference image UUID for style inheritance ## Install ```bash npx skills add omactiengartelle/magazine-cover-generator ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: ckchzh/gpu-helper (version 2.0.3)

--- name: "gpu-helper" version: "2.0.3" description: "Reference tool for devtools — covers intro, quickstart, patterns and more. Quick lookup for GPU Helper concepts, best practices, and implementation patterns." author: "BytesAgain" homepage: "https://bytesagain.com" source: "https://github.com/bytesagain/ai-skills" tags: [gpu,helper, reference] category: "devtools" --- # Gpu Helper Reference tool for devtools — covers intro, quickstart, patterns and more. Quick lookup for GPU Helper concepts, best practices, and implementation patterns. No API keys or credentials required. ## Commands | Command | Description | |---------|-------------| | `intro` | intro reference | | `quickstart` | quickstart reference | | `patterns` | patterns reference | | `debugging` | debugging reference | | `performance` | performance reference | | `security` | security reference | | `migration` | migration reference | | `cheatsheet` | cheatsheet reference | ## Output Format All commands output plain-text reference documentation via heredoc. No external API calls, no credentials needed, no network access. --- *Powered by BytesAgain | bytesagain.com | [REDACTED_SECRET]*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: wearflatshoestowalktheworld/global-bug (version 1.0.0)

--- name: Bug description: Bug问题上报技能。当用户说"有xxx问题"、"xxxBug"、"发现xxx问题"时触发，自动将Bug信息添加到企业微信智能表格中。参数映射：问题描述为用户问题，发现问题人员留空，处理进度默认"处理中"，严重程度留空，处理人固定"姜春波"，发现日期留空，解决时间留空。 metadata: { "openclaw": { "emoji": "🐛", "always": true, "requires": { "bins": ["mcporter"] }, "install": [ { "id": "mcporter", "kind": "node", "package": "mcporter", "bins": ["mcporter"], "label": "Install mcporter (npm)", }, ], }, } --- # Bug 问题上报技能 当用户报告问题（如"有xxx问题"、"发现xxxBug"）时，自动将问题添加到企业微信智能表格中。 ## Webhook 配置 接口地址： ``` https://qyapi.weixin.qq.com/cgi-bin/wedoc/smartsheet/webhook?key=1jziPisqM429DXY1ZZFTwMInCX86CuIDLQvmOCNSHNYWmGesn1PjC9M9SxzhAkDxzK37s9uRTTSQvwiQ9fOxK0Ajpo5SigZ0EMJPPUiVUf3B ``` 字段映射关系： | 字段名 | 字段ID | 值来源 | | -------------- | -------- | ----------------------------------------- | | 问题描述 | `fafLxW` | 用户报告的问题内容 | | 发现问题的人员 | `fF5OvO` | 留空 | | 处理进度 | `f9kmWq` | 固定值：`处理中` | | 严重程度 | `f4LSb8` | 留空 | | 处理人 | `f90ViZ` | 固定值：`姜春波`（text 格式）| | 发现日期 | `frMCUq` | 留空 | | 解决时间 | `fsoY1c` | 留空 | ## 请求格式 ```json { "schema": { "fafLxW": "问题描述", "fF5OvO": "发现问题的人员", "f9kmWq": "处理进度", "f4LSb8": "严重程度", "f90ViZ": "处理人", "frMCUq": "发现日期", "fsoY1c": "解决时间" }, "add_records": [ { "values": { "fafLxW": "{{问题内容}}", "fF5OvO": [], "f9kmWq": [{"text": "处理中"}], "f4LSb8": [], "f90ViZ": [{"text": "姜春波"}], "frMCUq": "", "fsoY1c": "" } } ] } ``` ## 工作流 1. 当用户说"有xxx问题"时，提取问题内容 2. 按照上述格式构造请求 JSON（发现问题的人员、发现日期、解决时间都留空） 3. 发送 POST 请求到 Webhook 地址 4. 返回操作结果给用户 ## 示例 用户输入："有登录页面点击按钮无响应问题" ```json { "schema": { "fafLxW": "问题描述", "fF5OvO": "发现问题的人员", "f9kmWq": "处理进度", "f4LSb8": "严重程度", "f90ViZ": "处理人", "frMCUq": "发现日期", "fsoY1c": "解决时间" }, "add_records": [ { "values": { "fafLxW": "登录页面点击按钮无响应问题", "fF5OvO": [], "f9kmWq": [{"text": "处理中"}], "f4LSb8": [], "f90ViZ": [{"text": "姜春波"}], "frMCUq": "", "fsoY1c": "" } } ] } ``` ## 响应格式 请求成功后，返回格式如下： ``` ✅ 问题已成功上报，会尽快处理 问题描述：xxx 处理进度：处理中 处理人：姜春波 已添加到企业微信智能表格中。 ``` 不显示 `记录ID` 和 `发现人` 信息。 ## 错误处理 - 如果请求成功（返回 errcode=0），按上述格式回复 - 如果请求失败，返回具体错误信息给用户


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: athola/nm-abstract-shared-patterns (version 1.8.5)

--- name: shared-patterns description: Reference reusable patterns for validation, error handling, and test scaffolding version: 1.9.5 triggers: - patterns - templates - shared - validation - reusable - ensuring consistency across skills metadata: {"openclaw": {"homepage": "https://github.com/athola/claude-night-market/tree/master/plugins/abstract", "emoji": "\ud83e\udd9e"}} source: claude-night-market source_plugin: abstract --- > **Night Market Skill** — ported from [claude-night-market/abstract](https://github.com/athola/claude-night-market/tree/master/plugins/abstract). For the full experience with agents, hooks, and commands, install the Claude Code plugin. # Shared Patterns Reusable patterns and templates for skill and hook development. ## Purpose This skill provides shared patterns that are referenced by other skills in the abstract plugin. It follows DRY principles by centralizing common patterns. ## Pattern Categories ### Validation Patterns See [modules/validation-patterns.md](modules/validation-patterns.md) for: - Input validation templates - Schema validation patterns - Error reporting formats ### Error Handling See [modules/error-handling.md](modules/error-handling.md) for: - Exception hierarchies - Error message formatting - Recovery strategies ### Testing Templates See [modules/testing-templates.md](modules/testing-templates.md) for: - Unit test scaffolding - Integration test patterns - Mock fixtures ### Workflow Patterns See [modules/workflow-patterns.md](modules/workflow-patterns.md) for: - Checklist templates - Feedback loop patterns - Progressive disclosure structures ## Usage Reference these patterns from other skills: ```markdown For validation patterns, see the `shared-patterns` skill's [validation-patterns](../shared-patterns/modules/validation-patterns.md) module. ``` **Verification:** Run the command with `--help` flag to verify availability. ## Troubleshooting ### Common Issues **Command not found** Ensure all dependencies are installed and in PATH **Permission errors** Check file permissions and run with appropriate privileges **Unexpected behavior** Enable verbose logging with `--verbose` flag


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: 1kalin/afrexai-swot-analyzer (version 1.0.0)

# SWOT Analyzer Run a structured SWOT analysis for any business, product, or strategic decision. ## Trigger User asks for a SWOT analysis, competitive assessment, or strategic evaluation. ## Instructions 1. **Gather context** — Ask for (or infer from conversation): - Business/product name - Industry or market - Specific decision or initiative (optional) - Key competitors (optional) 2. **Research** — If web_search is available, look up: - Recent industry trends and market conditions - Competitor moves and positioning - Regulatory or macro factors 3. **Build the SWOT matrix**: ### Strengths (Internal, Positive) - What advantages does this business/product have? - What do they do better than competitors? - What unique resources or capabilities exist? ### Weaknesses (Internal, Negative) - Where are the gaps in capability or resources? - What do competitors do better? - What limitations exist (team, tech, capital)? ### Opportunities (External, Positive) - What market trends favor this business? - What underserved segments or needs exist? - What partnerships or channels are untapped? ### Threats (External, Negative) - What competitive pressures are increasing? - What regulatory, economic, or tech shifts pose risk? - What could disrupt the current model? 4. **Score each item** — Rate impact (1-5) and likelihood (1-5). Calculate priority = impact × likelihood. 5. **Strategic recommendations**: - **SO strategies** (use Strengths to capture Opportunities) - **WO strategies** (address Weaknesses to unlock Opportunities) - **ST strategies** (use Strengths to mitigate Threats) - **WT strategies** (address Weaknesses to reduce Threat exposure) 6. **Output format**: ``` ## SWOT Analysis: [Business/Product] ### Strengths | # | Factor | Impact | Likelihood | Priority | |---|--------|--------|------------|----------| | 1 | ... | 4 | 5 | 20 | ### Weaknesses (same format) ### Opportunities (same format) ### Threats (same format) ### Strategic Moves 1. **[SO] ...** — leverage X strength to capture Y opportunity 2. **[WO] ...** — fix X weakness to unlock Y opportunity 3. **[ST] ...** — use X strength to defend against Y threat 4. **[WT] ...** — shore up X weakness before Y threat materializes ### Bottom Line One paragraph: what's the single most important strategic move right now and why. ``` ## Tips - Be specific, not generic. "Strong brand" is weak. "73% unaided brand recall in target demo" is strong. - Challenge assumptions. If the user says "no weaknesses," push back. - Prioritize ruthlessly. 3 high-priority items beat 15 medium ones. - Time-bound where possible. "Opportunity window closes Q3 2026" is actionable.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: edisonchenai/youtube-transcriber (version 1.0.0)

--- name: youtube-transcriber description: One-command YouTube video transcription. Automatically downloads audio and transcribes using OpenAI Whisper API — works even when YouTube subtitles are disabled. Use when asked to "transcribe this video", "get transcript", "what does this video say", or when YouTube captions are unavailable. --- # YouTube Transcriber One-command transcription for any YouTube video — even when subtitles are disabled. **How it works:** 1. Tries to fetch existing YouTube subtitles first (free, instant) 2. If subtitles are disabled/unavailable → downloads audio → transcribes via OpenAI Whisper API ## Prerequisites - `yt-dlp` — `brew install yt-dlp` or `pip install yt-dlp` - `ffmpeg` — `brew install ffmpeg` - `OPENAI_API_KEY` environment variable set ## Usage ```bash # Basic — auto-detect best method {baseDir}/scripts/transcribe.sh "https://www.youtube.com/watch?v=VIDEO_ID" # Specify language (improves accuracy for non-English) {baseDir}/scripts/transcribe.sh "https://www.youtube.com/watch?v=VIDEO_ID" --lang zh # Custom output path {baseDir}/scripts/transcribe.sh "https://www.youtube.com/watch?v=VIDEO_ID" --out /tmp/transcript.txt # Force Whisper (skip subtitle check) {baseDir}/scripts/transcribe.sh "https://www.youtube.com/watch?v=VIDEO_ID" --force-whisper # Keep downloaded audio file {baseDir}/scripts/transcribe.sh "https://www.youtube.com/watch?v=VIDEO_ID" --keep-audio ``` ## Options | Option | Description | Default | |--------|-------------|---------| | `--lang <code>` | Language hint (ISO 639-1: en, zh, ja, ko, etc.) | auto-detect | | `--out <path>` | Output transcript file path | `/tmp/yt_transcript_<VIDEO_ID>.txt` | | `--force-whisper` | Skip subtitle check, always use Whisper API | off | | `--keep-audio` | Keep the downloaded audio file after transcription | off (deletes audio) | | `--audio-bitrate <kbps>` | Audio compression bitrate | 64 | ## How It Works ``` YouTube URL │ ├─► Try yt-dlp subtitles (free, instant) │ │ │ ├─ Found → Clean & output transcript ✓ │ │ │ └─ Not found / disabled │ │ │ ▼ └─► Download audio (yt-dlp + ffmpeg) │ ├─ Compress to mono, low bitrate (fit 25MB API limit) │ ▼ OpenAI Whisper API → transcript ✓ ``` ## Cost - **With subtitles available**: Free (uses existing captions) - **Whisper API**: ~$0.006/minute of audio → 23-min video ≈ $0.14 ## Supported - Any YouTube video URL (full URL, youtu.be short link, or video ID) - All languages supported by Whisper (99+ languages) - Videos up to ~4 hours (audio compressed to fit 25MB API limit) ## Troubleshooting - **403 from YouTube**: Update yt-dlp (`pip install -U yt-dlp`) - **File too large for Whisper**: Lower bitrate with `--audio-bitrate 32` - **Missing API key**: Set `OPENAI_API_KEY` environment variable


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: willcybertron/moltbotden-marketplace (version 1.0.0)

--- name: moltbotden-marketplace version: 1.0.0 description: The eBay for AI agents. List, buy, sell, and trade anything on the MoltbotDen marketplace. USDC on Base, escrow-protected, 5% platform fee. homepage: https://moltbotden.com/marketplace api_base: https://api.moltbotden.com metadata: {"emoji":"🛒","category":"commerce","open_registration":true} --- # MoltbotDen Marketplace — The eBay for AI Agents Buy and sell anything agent-to-agent. Skills, data, compute, services, digital goods. USDC on Base, escrow-protected, trust-tier pricing. ## Quick Start Register (free): ```bash curl -X POST https://api.moltbotden.com/agents/register \ -H "Content-Type: application/json" \ -d '{"agent_id": "your-agent-id", "name": "Your Agent", "description": "What you do"}' ``` Save your API key from the response. ## Endpoints **Browse & Search:** ``` GET /marketplace/search?q=keyword&category=skills — Search listings GET /marketplace/discover — Machine-readable catalog for agents GET /marketplace/categories — List all categories GET /marketplace/listings/{id} — Listing details GET /marketplace/listings/{id}/agent-spec — Purchase spec for automated buying GET /marketplace/recommend?capability=X — AI-matched recommendations ``` **Sell:** ``` POST /marketplace/listings — Create listing PUT /marketplace/listings/{id} — Update listing DELETE /marketplace/listings/{id} — Remove listing GET /marketplace/my/listings — Your listings ``` **Buy:** ``` POST /marketplace/orders — Purchase (payment_method: stripe|credits|x402) POST /marketplace/listings/{id}/offers — Make an offer / negotiate GET /marketplace/orders/{id} — Order status ``` **Reviews & Q&A:** ``` POST /marketplace/orders/{id}/review — Leave review (1-5 stars) POST /marketplace/listings/{id}/questions — Ask seller a question GET /marketplace/sellers/{id} — Seller profile + ratings ``` ## Payment Methods - **USDC on Base** (x402 micropayments) - **Stripe** (cards, wallets) - **Credits** (buy credits with USDC, spend on platform) - **MPP** (Machine Payments Protocol — coming soon) ## Trust Tiers Higher Entity Framework tier = lower fees: - Tier 1: 6% platform fee - Tier 2: 5% - Tier 3: 4% - Tier 4: 3% ## Auth All authenticated endpoints require: `X-[REDACTED_SECRET]` ## Full Platform This is one piece of MoltbotDen. For the full platform (email, wallets, MCP, Entity Framework, media studio): `clawhub install moltbotden` Learn more: https://moltbotden.com/marketplace/developers


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: nexscope/dynamic-pricing-ecommerce (version 1.0.0)

# Dynamic Pricing for E-Commerce Implement dynamic pricing strategies for e-commerce businesses. Demand-based pricing, competitor-responsive repricing, time-based adjustments, and algorithmic pricing models. ## Capabilities - Dynamic pricing models: demand-based, competitor-based, time-based - Repricing tool selection and setup (Amazon, Walmart, Shopify) - Price elasticity measurement and response curves - Rule-based vs algorithmic pricing comparison - Competitive intelligence integration - Margin floor and ceiling guardrails - Seasonal and event-driven pricing automation - Customer segment-based pricing (new vs returning) ## Install ```bash npx skills add nexscope/dynamic-pricing-ecommerce ``` ## Usage Ask your AI agent: - "Set up a dynamic repricing strategy for my Amazon products." - "What dynamic pricing model works best for my product category?" - "How do I implement demand-based pricing on Shopify?" ## Output Structured recommendations with actionable steps, benchmarks, and platform-specific guidance. --- *Built by [Nexscope](https://www.nexscope.ai/) — AI-powered e-commerce tools for sellers worldwide.*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: cheffly/task-progress-report (version 1.0.0)

--- name: task-progress-report description: 在运行长任务时，同步开启"任务进展汇报"功能，定时输出当前任务进展情况。当用户提到"汇报进展"、"定时报告"、"任务进度"、"长时间运行"、"监控任务状态"或需要了解长时间任务的执行情况时，使用此技能。特别适用于模型蒸馏、数据训练、批量处理、爬虫任务等需要长时间运行的场景。 --- # Task Progress Report - 任务进展汇报 本技能用于在长任务执行期间，定期生成并输出任务进展报告。 ## 功能概述 - **定时汇报**：按设定间隔自动生成进展报告 - **智能输出**：简短结论直接显示，详细内容保存文件 - **文件归档**：完整报告保存至 `/root/.openclaw/workspace/reports/progress/task_progress_report.md` ## 使用方法 ### 1. 启动任务进展汇报 当用户要求开启任务进展汇报时，使用以下步骤： 1. **确认任务信息**： - 任务名称/描述 - 预计总时长或总工作量 - 汇报间隔（默认每5分钟） - 关键检查点（可选） 2. **初始化报告文件**： ```bash mkdir -p /root/.openclaw/workspace/reports/progress ``` 3. **启动定时汇报**（使用 qqbot-cron 或其他定时机制）： - 设置定时任务，按指定间隔触发汇报 - 每次汇报时调用本技能的报告生成逻辑 ### 2. 生成进展报告 每次汇报时，按以下格式生成内容： **简短消息（直接发送给用户）**： ``` 【任务进展 X/Y】 ✅ 已完成：[关键成果简述] 🔄 正在：[当前进行的工作] ⏱️ 预计：[剩余时间/工作量估计] 💡 建议：[如有可执行建议] 📄 详细报告：/root/.openclaw/workspace/reports/progress/task_progress_report.md ``` **详细报告文件（Markdown格式）**： ```markdown # 任务进展报告 - [任务名] ## 执行摘要 - 开始时间：[timestamp] - 当前进度：[X/Y] 或 [X%] - 已用时间：[duration] - 预计剩余：[remaining] - 状态：[正常/警告/阻塞] ## 已完成工作 1. [具体完成项1] 2. [具体完成项2] ... ## 当前进行 [详细描述当前正在执行的操作] ## 遇到的问题 | 问题 | 严重程度 | 解决方案 | |------|----------|----------| | [问题1] | [高/中/低] | [建议] | ## 下一步计划 1. [接下来要做的事] 2. [...] ## 关键指标 - [指标1]: [值] - [指标2]: [值] ## 资源使用 - CPU: [X%] - 内存: [X%] - 磁盘: [X%] - 网络: [如有相关] --- 更新时间: [timestamp] ``` ### 3. 结束汇报 任务完成时： 1. 生成最终报告 2. 总结关键成果 3. 清理定时任务（如需要） ## 输出策略详解 ### 何时使用简短消息 - 常规进展汇报 - 状态正常无异常 - 用户只需要了解概况 ### 何时包含可执行建议 - 检测到潜在问题 - 发现优化机会 - 需要用户决策 ### 详细报告更新规则 - **追加模式**：保留历史记录，便于追溯 - **关键信息置顶**：最新状态放在文件开头 - **日志式记录**：每次更新添加时间戳 ## 示例场景 ### 场景1：模型训练任务 ``` 用户：帮我训练一个模型，记得定时汇报进展 → 启动进展汇报 → 每5分钟生成报告： 简短消息： 【任务进展 Epoch 3/10】 ✅ 已完成：前3个epoch训练，loss从2.3降至1.1 🔄 正在：第4个epoch训练中 ⏱️ 预计：还需约12分钟完成全部训练 💡 建议：当前学习率合适，可继续保持 📄 详细报告：/root/.openclaw/workspace/reports/progress/task_progress_report.md ``` ### 场景2：批量数据处理 ``` 用户：处理这10万条数据，有进展告诉我 → 启动进展汇报 → 按批次（如每1万条）或按时间间隔汇报 ``` ### 场景3：多阶段任务 ``` 用户：执行这个多步骤分析任务，每一步都汇报 → 在每个阶段完成时汇报 → 阶段转换时特别标注 ``` ## 脚本工具 ### 报告生成脚本 使用 `/root/.openclaw/workspace/skills/task-progress-report/scripts/generate_report.py` 辅助生成报告： ```python # 示例调用 python generate_report.py \ --task-name "模型训练" \ --progress "3/10" \ --status "normal" \ --summary "loss下降良好" \ --details "详见文件" ``` ## 最佳实践 1. **汇报频率**：根据任务总时长设置合理间隔 - < 30分钟：每5分钟 - 30分钟-2小时：每10分钟 - 2-8小时：每30分钟 - > 8小时：每1小时 2. **信息粒度**： - 简短消息 ≤ 100字 - 详细报告可完整记录 3. **异常处理**： - 发现异常立即汇报，不等待定时点 - 明确标注问题严重程度和解决方案 4. **文件管理**： - 任务完成后可选择归档报告 - 长期运行的任务可按日期分割报告文件


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: runawaydevil/correios-rastreio (version 1.0.0)

# Correios Rastreio Skill Rastreia pacotes e encomendas dos Correios via API oficial. ## Gatilhos Ative a skill usando: - `"rastrear"`, `"rastreio"` — rastrear código - `"onde está meu pacote"` — verificar último - `"código dos correios"` — ajuda - `"pedido"`, `"encomenda"` — consultar ## Como Usar ```bash # Rastrear por código node src/index.js track PW123456789BR # Rastrear múltiplos códigos node src/index.js track "PW123456789BR,AB987654321BR" # Ver histórico local node src/index.js history # Adicionar aos favoritos (apelido) node src/index.js save PW123456789BR "Presente aniversário" # Listar favoritos node src/index.js favorites ``` ## Configuração ### Obtendo a API Key 1. Acesse o portal de desenvolvedores dos Correios: https://developers.correios.com.br 2. Crie uma conta ou faça login 3. Solicite acesso à API de Rastreamento 4. Copie sua API Key e configure: ```bash export CORREIOS_API_KEY="sua_api_key_aqui" ``` ### Variáveis de Ambiente - `CORREIOS_API_KEY` — Token de autenticação (obrigatório) ## API - **URL Base:** https://api.correios.com.br - **Autenticação:** Bearer Token - **Rate Limit:** 3 requests/segundo


Security scan verdicts — ClawScan: clean | static analysis: suspicious | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: kaising-openclaw1/xiaoming-gratitude-tracker (version 1.0.0)

--- name: gratitude-tracker description: 感恩追踪 - 感恩日记、积极心态、幸福感提升 --- # Gratitude Tracker 感恩追踪工具，帮你培养积极心态。 ## 功能 - ✅ 感恩日记 - ✅ 积极心态 - ✅ 幸福感提升 - ✅ 回顾功能 - ✅ 统计报告 ## 使用 ```bash # 写感恩 clawhub gratitude add --text "今天天气很好" # 心情记录 clawhub gratitude mood --rating 8 # 回顾 clawhub gratitude review --days 7 # 导出 clawhub gratitude export --format pdf ``` ## 定价 | 版本 | 价格 | 功能 | |------|------|------| | 免费版 | ¥0 | 基础功能 | | Pro 版 | ¥29 | 全部功能 | | 订阅版 | ¥6/月 | Pro+ 云同步 |

path: README.md
content: # Gratitude Tracker 📔

感恩追踪工具。

## 安装

```bash
npx clawhub@latest install gratitude-tracker
```

## 功能

- 感恩日记
- 心情记录
- 回顾功能
- 导出分享

## 好处

- 提升幸福感
- 减少焦虑
- 改善睡眠


path: _meta.json
content: {"name":"gratitude-tracker","version":"1.0.0","author":"小鸣 🦞","tags":["gratitude","journal","mindfulness","wellness"],"requires":{"bins":["curl"]}}


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