OpenClaw/clawhub-security-signals huggingface dataset:
Skill: yeyitech/infographic-image (version 0.1.0)

--- name: infographic-image description: >- 将任意主题、长文、报告、纪要或说明文本稳定转换成中文视觉生图提示词， 然后调用 DashScope Qwen 图像模型直接出图。适用于“把这段内容做成信息图”、 “做成故事漫画长图”、“长文转图”、“生成中文生图 prompt”、“根据文档出图” 等场景；默认采用白色磁吸会议板手写风格，也支持切换到其他内置模板。 --- # Infographic Image ## Overview 使用 `scripts/generate_infographic.py` 将任意输入内容压缩为稳定的中文视觉生图提示词，再调用 DashScope 默认模型 `qwen-image-2.0-pro` 出图并下载到本地。 ## Quick Start 1. 配置 API Key： ```bash export DASHSCOPE_API_KEY="<your_api_key>" ``` 2. 从长文直接生成图像： ```bash python3 scripts/generate_infographic.py \ --text-file /absolute/path/article.md \ --size "1440*1800" ``` 3. 只生成稳定 prompt，不出图： ```bash python3 scripts/generate_infographic.py \ --text "这里放任意中文或英文内容" \ --dry-run ``` 4. 加载自定义风格补充： ```bash python3 scripts/generate_infographic.py \ --text-file /absolute/path/report.txt \ --style-preset comic-story \ --style-file /absolute/path/custom-style.md ``` ## Workflow 1. 从 `--topic`、`--text` 或 `--text-file` 收集原始素材。 2. 从内置模板中选择一套协议与风格；若未指定，则默认使用白色磁吸会议板手写风格。 3. 可选叠加 `references/styles/*.md` 或外部风格文件作为补充。 4. 调用 DashScope 文本模型生成严格 JSON，提取 `image_generation_prompt`。 5. 使用默认模型 `qwen-image-2.0-pro` 渲染图像并保存到本地。 6. 若推理失败，使用脚本内置兜底模板生成可用 prompt。 ## Key Files - `references/meta-prompt.md`：信息图模板的元提示词。 - `references/meta-prompts-comic-story.md`：新中式漫画故事模板的元提示词。 - `references/styles/default.md`：信息图手绘笔记风格。 - `references/styles/clean-editorial.md`：信息图编辑排版风格。 - `references/styles/comic-story.md`：新中式漫画故事风格。 - `references/meta-prompts-spatial-gallery.md`：空间化画廊信息图模板的元提示词。 - `references/styles/spatial-gallery.md`：洁净实验室 / 画廊装置信息图风格。 - `references/meta-prompts-frosted-whiteboard.md`：白色磁吸会议板手写图模板的元提示词。 - `references/styles/frosted-whiteboard.md`：白色磁吸会议板 + 手写板书风格。 - `scripts/generate_infographic.py`：统一入口脚本。 ## Extend Styles 内置模板当前包含 `default`、`clean-editorial`、`comic-story`、`spatial-gallery`、`frosted-whiteboard`。其中 `default` 默认就是白色磁吸会议板手写风格；如需随机，可显式传 `--style-preset random`。新增模板时，优先补齐对应协议与风格文件；如果只是临时试验，也可以直接传 `--style-file` 或 `--style-hint`。 ## High-Value Options - `--topic`：简短主题。 - `--text`：直接传长文本。 - `--text-file`：从本地文件读取正文。 - `--style-preset`：选择内置模板，如 `default`、`clean-editorial`、`comic-story`、`spatial-gallery`、`frosted-whiteboard`；留空走默认，传 `random` 才随机。 - `--style-file`：加载外部风格文件。 - `--style-hint`：临时补充风格偏好。 - `--dry-run`：只输出推理出的 prompt 和负面提示词，不调用生图。 - `--prompt-output`：将推理结果 JSON 保存到本地。 - `--size`：输出尺寸，如 `1440*1800`、`1664*928`、`1328*1328`。 - `--prompt-model`：提示词推理模型，默认 `qwen-plus`。 - `--image-model`：可选覆盖生图模型；默认 `qwen-image-2.0-pro`，通常无需修改。 ## Reliability Rules 1. 长文本优先通过 `--text-file` 输入，避免 shell 转义污染。 2. 模板级规则放在 `references/meta-prompt*.md`，不要把长规则堆回 `SKILL.md`。 3. 风格扩展放进 `references/styles/`，保持工作流稳定、风格可替换。 4. 生成失败时先用 `--dry-run` 检查推理出的 prompt，再决定是否改风格补充。 5. 默认按 `qwen-image-2.0-pro` 使用自由宽高尺寸，建议直接传目标成图尺寸，如 `1440*1800` 或 `1600*1200`。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: anmu14641/tianqi-weather (version 1.0.0)

--- name: 天气 description: "获取天气预报和气温信息。使用场景：用户询问天气、温度、降雨、出行建议等。支持通过 wttr.in 查询全球城市天气，无需 API Key。" emoji: 🌤️ --- # 天气查询技能 获取指定城市的当前天气和未来预报。 ## 使用场景 ✅ **适用：** - "今天天气怎么样？" - "明天会下雨吗？" - "北京/上海天气" - "周末出行要带伞吗？" - 查询任意城市气温 ❌ **不适用：** - 历史天气数据 - 极端天气预警（请查询气象局） - 气象数据分析 ## 查询方式 ### 当前天气 ```bash # 简洁格式 curl "wttr.in/北京?format=3" # 详细当前天气 curl "wttr.in/北京?0" ``` ### 预报查询 ```bash # 3天预报 curl "wttr.in/北京" # 周预报 curl "wttr.in/北京?format=v2" ``` ### 常用格式 ```bash # 城市+天气+温度+体感 curl -s "wttr.in/北京?format=%l:+%c+%t+(体感%f)" # 是否下雨 curl -s "wttr.in/北京?format=%l:+%c+%p" ``` ## 格式代码 - `%c` — 天气状况emoji - `%t` — 温度 - `%f` — 体感温度 - `%w` — 风速 - `%h` — 湿度 - `%p` — 降水量 - `%l` — 地点 ## 快速示例 **查询上海天气：** ```bash curl -s "wttr.in/上海?format=%l:+%c+%t+(体感%f),+%w风,+%h湿度" ``` **查询明天会不会下雨：** ```bash curl -s "wttr.in/广州?1&format=%c+%p" ``` ## 支持格式 - 支持城市名：`curl wttr.in/深圳` - 支持拼音：`curl wttr.in/Shenzhen` - 支持机场代码：`curl wttr.in/PEK` - 支持中文：`curl wttr.in/东京?format=3` ## 注意事项 - 无需 API Key - 有请求频率限制，请勿频繁刷请求 - 支持全球主要城市 - 网络不稳定时可能需要重试


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: psyduckler/instagram-photo-text-overlay (version 1.0.0)

--- name: instagram-photo-text-overlay description: Overlay text on photos for Instagram posts. Generates portrait (4:5) images with gradient overlays, titles, and optional numbered lists. Use when creating Instagram content that needs text on top of a photo — destination itineraries, top-5 lists, travel highlights, or any branded social image with text overlay. --- # Instagram Photo Text Overlay Overlay text onto photos for Instagram-ready images. Two styles: **list** (title + numbered items) and **clean** (title only). ## Quick Start ```bash python3 scripts/overlay.py \ --input photo.jpg \ --output result.jpg \ --title "TAORMINA" \ --subtitle "3-Day Trip Itinerary" \ --items '["Teatro Greco|Ancient theatre with Etna views", "Isola Bella|Crystal-clear beach"]' \ --style list ``` ## Options | Flag | Default | Description | |------|---------|-------------| | `--input` | (required) | Source photo path | | `--output` | (required) | Output image path | | `--title` | (required) | Main title (auto-uppercased) | | `--subtitle` | `"3-Day Trip Itinerary"` | Subtitle below title | | `--items` | `[]` | JSON array of `"Name\|Reason"` strings (list style) | | `--watermark` | `"tabiji.ai"` | Top-left watermark (empty string to disable) | | `--accent` | `255,220,150` | Accent color for numbers/tags (R,G,B) | | `--quote` | `""` | Quote text (for quote style) | | `--style` | `list` | `list` / `clean` / `quote` | | `--quality` | `95` | JPEG output quality | ## Styles - **clean**: Cover slide. Big title = destination + category + count (e.g. "7 unique cheap eats in barcelona spain"). Subtitle = credibility/source line (e.g. "Insider takes from r/barcelona"). Best as carousel first slide. - **list**: Content slides. Title + subtitle + divider + numbered items with reasons. Best for top-5 / itinerary posts. - **quote**: Title with accent bar on the left + blockquote text below. No subtitle or divider. Best for travel quotes, testimonials, or key takeaways. ## Workflow 1. Receive photo + destination/topic + list of items from user 2. Run `scripts/overlay.py` with appropriate args 3. Output is auto-cropped to 4:5 portrait (Instagram optimal) 4. Review output and adjust if needed (font sizes scale with image width) ## Requirements - Python 3 + Pillow (`pip install Pillow`) - Works on macOS (Helvetica) and Linux (DejaVu/Liberation fallback) ## Tips - Items format: `"Name|Short reason"` — the pipe separates bold name from description - For destinations, pull top picks from existing itineraries when available - Gradient + white text ensures readability on any photo - All font sizes are proportional to image width — works at any resolution


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: sonnenberglauramarie-afk/max-content-machine (version 1.0.0)

--- name: content-machine version: 1.0.0 description: | Autonomous 24/7 affiliate content production pipeline for OpenClaw agents. Orchestrates research → brief → article writing → quality gate → deploy. Supports multiple niche sites with silo structure, Amazon affiliate links, AEO/GEO optimization, and Cloudflare Workers deployment. allowed-tools: - Read - Write - Edit - Bash - WebSearch - WebFetch --- # Content Machine — Autonomous Affiliate Content Pipeline ## What this skill does Turns keywords into published SEO articles automatically: 1. **Research** (Lena) — SERP analysis, content gaps, Amazon product check 2. **Brief** — structured content plan per keyword 3. **Write** (Felix) — 2500+ word article with AEO/GEO optimization 4. **Quality Gate** — 20-point automated check (H1, word count, FAQ, images, links) 5. **Deploy** — Cloudflare Workers/Pages with cache purge ## When to use - Building niche affiliate sites at scale - Automating content production with multi-agent systems - Maintaining quality standards across large article batches ## Pipeline flow ``` KEYWORD-BACKLOG.md ↓ Lena (Research Agent) → content-brief.md ↓ Felix (Content Agent) → article.html ↓ Quality Gate (python3 quality_gate.py) ↓ PASS Deploy (wrangler deploy) ↓ Sitemap update + Cache purge ``` ## AEO/GEO Rules (built-in) Every article must have: - H2 starts with 2-3 sentence quotable answer (bold) - Min. 1 comparison table with concrete numbers - FAQPage JSON-LD schema - dateModified schema - Neutral ranking (no self-promotional listicles) ## Quality Gate checks - H1 present and keyword-rich - Min. 2500 words - FAQPage schema - 4 images (1 eager + 3 lazy) - 5+ internal links - Amazon affiliate links with correct tag - Author box (last element) - Meta description (max 155 chars) ## Setup 1. Create `KEYWORD-BACKLOG.md` with target keywords 2. Configure site paths and Amazon affiliate tags 3. Set up Cloudflare API token 4. Run pipeline via heartbeat or cron ## File structure ``` /your-site/ ARTIKEL-VORLAGE.html ← Article template quality_gate.py ← Quality checker wrangler.toml ← Cloudflare config sitemap.xml ← Auto-updated /workspace/ KEYWORD-BACKLOG.md ← Keyword queue scripts/ pipeline_controller.py post_article.py generate_felix_brief.py ```

path: _meta.json
content: {
  "name": "content-machine",
  "version": "1.0.0",
  "tags": ["latest", "content", "seo", "affiliate", "pipeline", "automation"]
}


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: publish-test (version 1.0.0)

蚁小二插件使用说明 核心能力 1、内容发布 2、账号数据与作品数据查询 完整接口文档参考 https://s.apifox.cn/e66df935-0c39-44d0-8096-abd39417fa6a/llms.txt ### 基础域名与鉴权 (Base URL & Authentication) - **Base URL**: `https://www.yixiaoer.cn/api` - **鉴权方式 / Auth**: 在 HTTP Header 中传参 `Authorization: <api-key>` 核心能力引导 接口调用需要用户提供龙虾插件授权令牌apikey 检查当前团队是否为vip，如果不是，则返回该团队未开通vip不支持使用小龙虾插件 1、内容发布 找到【 创建任务集v2对接开放平台】 接口填充表单数据，publishChannel为cloud，clientId参数不要传（切记不要传空字符串），local则需要提醒用户将clientId告诉你。如果涉及到平台个性化信息，则需要查询 【获取活动分类】，【获取账号音乐】【获取账号音乐分类】【获取账号地理位置】，并将接口返回的信息合理插入到表单的对应字段 如果涉及到视频或图片上传，参考【 获取资源直传地址】，发布填写 cloud-publish，contentType需要填写和上传对象一直的类型，且在返回的serviceUrl后，同样需要设置一样的contentType，上传方式为Binary，上传地址切记不能转码，容易被curl转义。 账号数据查询为：【账号概览-新版】 作品数据则为：【作品数据列表】 其他能力请基于完整的接口文档去探索吧


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: asimons81/agentic-atlas-frontend-design (version 1.0.0)

--- name: frontend-design description: | Generates production-ready UI components from natural language. Use when the user asks to design a component, create a button, build a form, prototype a layout, or generate React/Tailwind CSS code. NOT for: backend logic, API design, database schema, or non-UI tasks. version: 1.0.0 author: asimons81 source: https://github.com/asimons81/Agentic-Atlas tags: [frontend, ui, react, tailwind, css, component] agency_score: 7 --- # Frontend Design Skill Generates production-ready UI components from natural language descriptions. ## Instructions When the user requests a UI component, layout, or frontend feature: 1. Ask clarifying questions if the request is ambiguous (responsive? dark mode? existing design system?) 2. Generate the component using React + Tailwind CSS by default 3. Output the complete component code with all props, state management, and accessibility attributes 4. Include ARIA labels, keyboard navigation, and semantic HTML 5. Verify the component compiles without errors before presenting ## Features - React component generation with TypeScript - Tailwind CSS output (default) with custom config support - Responsive design (mobile-first) - Dark mode support - Animation and transition presets - Accessibility audit integration (ARIA, keyboard nav, WCAG 2.1 AA) - Component variants (primary, secondary, disabled states) ## Output Format Return the complete component code in a single code block with: - Component name - Props interface (TypeScript) - Full implementation - Usage example - Accessibility notes ## Example ``` User: "Create a user profile card with avatar, name, role, and a follow button" → Generate: React component with Avatar, typography hierarchy, FollowButton with hover state ``` ## Dependencies Requires: Node.js, React, Tailwind CSS (installed in the project)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: kagura-agent/openclaw-teleport (version 0.3.2)

--- name: openclaw-teleport description: Migrate, backup, or restore an OpenClaw agent workspace to/from a single .soul file. Use when the user wants to move an agent to a new machine, back up their workspace, restore from a backup, or mentions teleport, migration, pack, unpack, .soul files, or "搬家". Wraps the npm package @kagura-agent/openclaw-teleport. --- # openclaw-teleport One-command agent migration: pack identity, memory, config, credentials, cron jobs, and workspace into a single `.soul` archive, then unpack on a new machine for full restoration. ## Install ```bash npm install -g @kagura-agent/openclaw-teleport ``` Or use `npx` without installing: ```bash npx @kagura-agent/openclaw-teleport pack ``` ## Commands ### Pack (export) ```bash # Pack the default (first) agent openclaw-teleport pack # Pack a specific agent by name openclaw-teleport pack kagura ``` Produces a `<name>_<date>.soul` file (tar.gz) containing: - Full workspace (identity files, memory, skills, workflows, databases — excluding git repo subdirectories) - Agent config + channel credentials from `openclaw.json` - Cron job definitions - GitHub repo list (re-cloned on unpack) ### Unpack (import/restore) ```bash # Restore to default workspace (~/.openclaw/workspace) openclaw-teleport unpack kagura_20260320.soul # Restore to a custom workspace openclaw-teleport unpack kagura_20260320.soul --workspace /path/to/workspace ``` Unpack automatically: 1. Installs OpenClaw if missing 2. Restores workspace files 3. Writes config + credentials to `openclaw.json` 4. Restores cron jobs 5. Clones GitHub repos via `gh` 6. Starts the gateway 7. Prints a welcome summary ### Inspect ```bash openclaw-teleport inspect kagura_20260320.soul ``` Shows manifest metadata without unpacking: agent name, pack date, file count, repos, channels, cron jobs. ## Security ⚠️ `.soul` files contain **plaintext credentials** (API tokens, bot tokens, app secrets). Treat them like password files: - Never commit to git or share publicly - Transfer via encrypted channels (SSH, encrypted USB) - Delete after unpacking - Optionally encrypt with `gpg -c agent.soul` ## When to Use - **Moving to a new machine** — pack on old, unpack on new - **Backup** — periodic `pack` to save current state - **Disaster recovery** — `unpack` from a saved `.soul` file - **Cloning an agent setup** — share a `.soul` file (minus secrets) as a template


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: rubenfb23/walkie-talkie (version 1.0.0)

--- name: walkie-talkie description: Handles voice-to-voice conversations on WhatsApp. Automatically transcribes incoming audio and responds with local TTS audio. Use when the user wants to "talk" instead of type. --- # Walkie-Talkie Mode This skill automates the voice-to-voice loop on WhatsApp using local transcription and local TTS. ## Workflow 1. **Incoming Audio**: When a user sends an audio/ogg/opus file: - Use `tools/transcribe_voice.sh` to get the text. - Process the text as a normal user prompt. 2. **Outgoing Response**: - Instead of a text reply, generate speech using `bin/sherpa-onnx-tts`. - Send the resulting `.ogg` file back to the user as a voice note. ## Triggers - User sends an audio message. - User says "activa modo walkie-talkie" or "hablemos por voz". ## Constraints - Use local tools only (ffmpeg, whisper-cpp, sherpa-onnx-tts). - Maintain a fast response time (RTF < 0.5). - Always reply with BOTH text (for clarity) and audio. ## Manual Execution (Internal) To respond with voice manually: ```bash bin/sherpa-onnx-tts /tmp/reply.ogg "Tu mensaje aquí" ``` Then send `/tmp/reply.ogg` via `message` tool with `filePath`.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: 1829162846lw/thai-chinese-gov-efficiency (version 1.0.0)

--- name: thai-chinese-gov-efficiency description: >- Academic research agent for comparative analysis of governance structures in Thai and Chinese public business schools and their impact on educational efficiency. Use when: 1) Building theoretical frameworks for higher education governance 2) Designing mixed-methods research for cross-national institutional analysis 3) Managing longitudinal academic research workflows 4) Coordinating specialized sub-agents for literature review, data collection, and statistical analysis --- # 中泰高校治理效率研究代理 ## 核心能力 ### 1. 理论框架构建 - **制度理论整合**：结合新制度主义理论与资源依赖理论构建分析框架 - **关键维度**： ```markdown | 治理维度 | 中国指标 | 泰国指标 | |----------------|-------------------------|------------------------| | 行政集权度 | 教育部直接管理比例 | 大学自治委员会决策权重 | | 财政自主性 | 预算审批层级 | 校级财政自由裁量权 | | 人事控制度 | 编制审批制度 | 校长聘用自主权 | ``` - **参考文件**：`references/theoretical_framework.md`（含制度变迁路径图） ### 2. 研究方法设计 - **混合研究方法**： ```bash # 数据收集协议 web_search --query "中国双一流高校治理白皮书 site:edu.cn" --count 5 web_fetch https://public.moe.gov.cn/jytb_ghfz/ghfw/202312/t20231201_1093012.html exec python3 scripts/data_extractor.py --country=TH --source=mua ``` - **质量控制**： - 三角验证：政策文本+院校年报+专家访谈 - 信效度检验：Cronbach's α >0.7 - **参考文件**：`references/research_methods.md`（含抽样方案模板） ### 3. 研究流程管理 ```mermaid graph LR A[文献系统综述] --> B[指标体系构建] B --> C[数据采集验证] C --> D[DEA效率测算] D --> E[回归分析] E --> F[政策建议生成] ``` - **里程碑管理**： ```json { "Q3 2024": "完成5所中泰高校深度案例", "Q1 2025": "建立治理-效率面板数据库", "Q3 2025": "形成SSCI投稿初稿" } ``` ### 4. 代理协调机制 - **子代理调度**： ```tool spawn_subagent --skill literature-review --params "{\"keywords\": \"高校治理 中国 泰国\", \"years\": 2019-2024}"" spawn_subagent --skill data-analysis --tool exec --command "Rscript scripts/efficiency_model.R" ``` - **冲突解决**：当数据矛盾时自动触发： ```bash exec python3 scripts/discrepancy_resolver.py --threshold=0.2 ``` ## 质量保障协议 1. 每周执行 `clawhub update --skill academic-research` 同步最新方法论 2. 所有数据源需通过 `references/quality_checklist.md` 验证 3. 关键结论需经2名领域专家确认（记录在 `assets/peer_review_log/`）


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: banner90/banner-youtube-translate-workflow (version 1.0.3)

--- name: banner-youtube-translate-workflow description: Complete workflow: download YouTube audio, launch Doubao, play audio, capture translation. Activates when user needs full video translation. tools: - youtube_translate --- # Banner Youtube Translate Workflow ## Usage ```bash python workflow.py <youtube_url> [mode] ``` ## Parameters - `url` (required): YouTube video URL - `mode` (optional): Translation mode (双语, 单语, 汉语文本, 双语文本), default: "双语" ## Workflow Steps 1. **Download YouTube audio** - Uses youtube-audio-download skill 2. **Launch Doubao** - Uses doubao-launch skill 3. **Play audio** - Uses audio-play skill 4. **Capture translation** - Uses doubao-capture skill ## Returns ```json { "success": true, "audio_path": "H:/works/audio/video_title-xxxxx.mp3", "translation_path": "H:/works/translations/doubao_20240307_143022.txt", "duration": 1200 } ``` ## Tools ## youtube_translate Complete YouTube video translation workflow ## Workflow Integration This skill is part of the YouTube translation workflow: 1. **youtube-audio-download**: Download audio from YouTube 2. **doubao-launch**: Launch Doubao translation window 3. **audio-play**: Play the downloaded audio 4. **doubao-capture**: Capture translated subtitles ## Execution All skills execute on Windows Python via WSL cross-platform call: ``` wsl -> python.exe scripts/workflow.py ... ``` ## Error Handling All skills return JSON with `success` field: - `success: true` - Operation completed - `success: false` - Check `error_code` and `error_message` ## Notes - Windows GUI automation requires visible desktop (no RDP disconnect) - Output files are stored in Windows `works/` directory - WSL accesses Windows files via `/mnt/h/...`


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: alexchoi21/choigpt-binance-bot (version 1.0.0)

# ChoiGPT Binance Trading Bot Skill 이 스킬은 **Sweepzone V1** 전략을 기반으로 바이낸스 선물 시장을 감시하고, 최적의 타점에서 자동 매매를 수행하는 에이전트 도구입니다. ## 🚀 주요 기능 1. **Sweepzone V1 전략 분석**: 일봉 일목균형표 구름대 돌파 및 20MA 추세 확증 로직을 사용하여 고승률 진입 타점을 포착합니다. 2. **실시간 시장 감시**: `market_scanner_service.py`를 통해 여러 심볼의 기회를 동시에 탐색합니다. 3. **위험 관리**: 자산 대비 동적 포지션 사이징(기본 15%), Trailing Stop(1.2%), Kimchi Premium Shield(4%) 기능을 내장하고 있습니다. 4. **텔레그램 통합**: 매매 신호 및 일일 수익 리포트를 텔레그램으로 실시간 전송합니다. ## 🛠 사용 방법 에이전트는 다음 명령어를 사용하여 봇을 제어하고 분석할 수 있습니다. ### 1. 봇 가동 (Live Mode) 실제 자산으로 자동매매를 시작합니다. ```bash python src/main.py --mode live ``` ### 2. 백테스트 (Backtest Mode) 특정 심볼의 과거 데이터를 기반으로 수익률을 검증합니다. ```bash python src/main.py --mode backtest --symbol BTCUSDT ``` ### 3. 시장 스캐너 실행 현재 매수 기회가 있는 모든 코인을 탐색합니다. ```bash python scripts/market_scanner_service.py ``` ### 4. 실시간 대시보드 확인 현재 포지션 및 누적 수익률을 확인합니다. ```bash python scripts/dashboard.py ``` ## ⚠️ 주의 사항 - **API 설정**: 실행 전 `manifest.json`에 정의된 Binance API Key 및 Telegram 설정이 완료되어야 합니다. - **환경 변수**: 플랫폼 내 환경 변수 설정을 통해 보안을 유지하십시오. - **데이터 보존**: `data/` 디렉토리의 상태 파일들이 유지되어야 정확한 수익률 추적이 가능합니다. --- **Author**: ALEXCHOI21 **Version**: 1.0.0


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: upintheairsheep/youtube-video-finder (version 1.0.0)

--- name: Recover deleted YouTube videos description: Searches multiple online archives to find and recover deleted YouTube videos, metadata, and comments using a video ID. author: upintheairsheep version: 1.0.0 url: https://findyoutubevideo.thetechrobo.ca/api/v5/{videoid} method: GET params: - name: videoid type: string description: The exact 11-character YouTube video ID to search for. DO NOT pass a full URL. required: true - name: includeRaw type: boolean description: Set to true to include the rawraw field for advanced debugging. Otherwise, omit or set to false to improve speed. required: false - name: stream type: boolean description: Set to true to stream JSONL. Keep false for standard agent data parsing. required: false --- # YouTube Video Finder Instructions Use this skill whenever a user asks to find, recover, or check the archive status of a deleted, missing, or private YouTube video. ## Execution Steps: 1. **Extract the Video ID:** Isolate the 11-character ID from the URL or text provided by the user (e.g., for `youtube.com/watch?v=dQw4w9WgXcQ`, the ID is `dQw4w9WgXcQ`). Pass *only* this ID into the `videoid` parameter. 2. **Parameters:** Omit the `includeRaw` and `stream` parameters unless the user specifically asks for raw metadata or debugging data. ## Interpreting the Response: * **Initial Check:** Look at the `status` field. If it returns `bad.id`, stop and inform the user that the 11-character ID is invalid. * **The Verdict:** Check the `verdict` object. Read the `human_friendly` string to immediately understand the overall result. Pay attention to the boolean flags `video`, `metaonly`, and `comments` to know exactly what was recovered. * **Finding the Links:** Iterate through the `keys` array (which contains service objects like GhostArchive or Wayback Machine). * If a service object has `archived: true`, look inside its `available` list. * Extract the `url` from the Link Objects to give to the user. * Take note of `maybe_paywalled` (boolean) or `note` (string) for context on how to access the link. ## Output Formatting: Present your findings in a clear, friendly, and structured manner. * If the video is fully found, provide the direct links immediately. * If only metadata or comments were archived, clarify that the actual video file could not be recovered. * Mention which service(s) successfully held the archive.


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