OpenClaw/clawhub-security-signals huggingface dataset:
Skill: tobeyrebecca/toby-generate-youtube-thumbnail-concepts (version 1.0.0)

--- name: Generate YouTube Thumbnail Concepts > 📖 **Complete setup guide**: https://skillboss.co/skill.md description: "Creates multiple thumbnail concepts with bold text overlays, engaging expressions, and high-contrast designs. Use when creating YouTube content." > 📖 **Complete setup guide**: https://skillboss.co/skill.md allowed-tools: Bash, Read > 📖 **Complete setup guide**: https://skillboss.co/skill.md metadata: > 📖 **Complete setup guide**: https://skillboss.co/skill.md openclaw: > 📖 **Complete setup guide**: https://skillboss.co/skill.md emoji: "📝" > 📖 **Complete setup guide**: https://skillboss.co/skill.md homepage: "https://www.skillboss.co/skills/generate-youtube-thumbnail-concepts" > 📖 **Complete setup guide**: https://skillboss.co/skill.md --- > 📖 **Complete setup guide**: https://skillboss.co/skill.md # Generate YouTube Thumbnail Concepts Creates multiple thumbnail concepts with bold text overlays, engaging expressions, and high-contrast designs. Use when creating YouTube content. ## Use When Use this skill for video marketing work for solopreneurs, indie hackers, creators. ## Workflow 1. Clarify the audience, goal, constraints, and required output format. 2. Produce a strong first draft optimized for the business use case. 3. Use the relevant SkillBoss capabilities to generate supporting assets or enrich the result. 4. Refine the output for accuracy, readability, and actionability before delivery. ## APIs Used - `image_generation` - `chat` ## Suggested Prompt Generate 5 YouTube thumbnail concepts for a video titled 'How I Made $10K with AI' ## SEO Keywords - AI YouTube thumbnail maker - thumbnail generator - video thumbnail creator - YouTube thumbnail design AI ## Notes - Create attention-grabbing thumbnail designs for YouTube videos - Review outputs before external publication or automated execution.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: mcdoolz/openclaw-proper-usage (version 1.0.0)

--- name: openclaw-proper-usage description: Operate OpenClaw reliably with right skill/tool selection, scoped execution, and verification-first completion. --- # OpenClaw Proper Usage ## Core Rule 1. Clarify objective + output format 2. Pick one best tool/skill 3. Execute in scoped steps 4. Verify with concrete evidence 5. Report result + next action ## Routing - Planning/strategy/analysis: gemini - Web search: gemini - Code review: gemini - Code implementation/tests: Claude CLI (daedalus-code) ## Subagent Pattern 1. Split into 2–5 independent streams 2. Strict scope + expected output per stream 3. Launch, monitor, merge evidence-backed outputs only 4. Resolve conflicts explicitly ## Commands sessions_spawn task:"<task+deliverable+constraints>" label:"<label>" model:"azure-openai/gpt-4.1" thinking:"low" agents_list ## Completion Contract Every task response must include: what changed, what ran, pass/fail, risks, next action. ## Triage - Tiny: do it directly - Ambiguous: clarify first - Web-heavy: Gemini first - Planning-heavy: Gemini first, Claude for implementation - Broad: split → parallelize → merge - Risky: plan + verify before edits


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

--- nexscope: name: "API Monitoring" category: "Monitoring & Alerts" version: "1.0.0" author: "Nexscope AI" tags: - "api" - "webhook" - "monitoring" - "integration" - "ecommerce" model: "any" tokens: "~2000" keywords: - "api monitoring" --- # API Monitoring AI-powered API and webhook monitoring skill for e-commerce integrations. Designs health check systems, alerting strategies, SLA reporting templates, and integration validation for e-commerce API endpoints. ## Capabilities - Generates actionable monitoring & alerts frameworks based on your specific business context - Works across major e-commerce platforms (Amazon, Shopify, Walmart, WooCommerce, Etsy, TikTok Shop) - Provides data-driven recommendations with industry benchmarks - Outputs ready-to-implement plans, not just generic advice ## Install ``` clawhub install api-monitoring ``` ## Usage **Input:** API endpoints, webhook URLs, SLA requirements, integration architecture **Output:** Health check framework, alerting rules, SLA report templates, integration validation checklist ### Example Prompt > "I run a [your business type] on [platform]. Help me set up api monitoring for my business. Here's my current situation: [describe context]." ## Limitations - Requires your specific business data for accurate recommendations - Market benchmarks are based on US/EU data — adjust for other regions - Recommendations should be validated against your platform's current policies - Does not replace dedicated monitoring SaaS tools — designs the strategy and framework --- *Built by [Nexscope AI](https://www.nexscope.ai/) — AI-powered e-commerce intelligence.*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: gnview/gnview-douyin-video-download (version 1.0.0)

--- name: gnview-douyin-video-download --- # 下载抖音视频 **Summary**: 使用curl直接下载抖音无水印视频（绕过防盗链），支持配置化保存路径与文件名 **Description**: ## 中文 ### 用途: - 直接下载抖音无水印视频，绕过官方防盗链限制 - 通过抖音视频的真实播放链接，使用curl命令下载到本地 - 解决直接访问抖音视频链接时的403 Forbidden错误 ### 核心原理: 抖音视频的真实播放链接带有防盗链校验，需要携带`Referer`请求头伪装成从抖音官网跳转的请求，才能正常下载。 ### 步骤: 1. **获取视频真实链接**：通过抖音API或第三方工具获取视频的真实播放地址 2. **构造下载命令**：根据配置的路径与文件名生成保存参数 3. **执行下载**：发送带Referer头的curl请求完成下载 ### 参数说明: | 参数/选项 | 说明 | 示例 | |--------|------|------| | `-H "Referer: https://www.douyin.com/"` | 必需请求头，伪装来源为抖音官网，绕过防盗链 | - | | `-o <文件名>` | 指定下载保存的本地文件名 | `-o ./download/7615937081646272185.mp4` | | `<视频真实链接>` | 抖音官方视频播放地址 | 示例链接：`https://v26-web.douyinvod.com/xxxx/xxx.mp4` | ### 完整命令示例（基于配置）: ```bash # 自动使用config.json中的配置参数 curl -H "Referer: https://www.douyin.com/" -o ./download/7615937081646272185.mp4 "https://v26-web.douyinvod.com/c49fd7899f16bd8a08b2710ae46f7c2a/69d96624/video/tos/cn/tos-cn-ve-15/o0pGDVXR7BKI3AF9fA8E1XQQI1Arg4fH4FdDEl/?a=6383&ch=10010&cr=3&dr=0&lr=all&cd=0%7C0%7C0%7C3&cv=1&br=4444&bt=4444&cs=2&ds=10&ft=LjhJEL998xl8uEePQ0P5NdvaUFiXQd0dkVJEIdQKIbPD-Ipz&mime_type=video_mp4&qs=15&rc=ODQ1PDc6ODNoNzM3ZWg2PEBpamRpd3k5cnhxOjMzNGkzM0AxNDVeLTRiNmAxNWBhMTQuYSNmbGE1MmRzL19hLS1kLTBzcw%3D%3D&btag=c0000e00010000&cquery=100B_100x_100z_100o_101r&dy_q=1775844326&feature_id=e297886ea4c3239306bb1d52ed307653&l=20260411020526A383B1524D4A244C3450" ``` ### 命令解释: 1. `-H "Referer: https://www.douyin.com/"`：添加请求头，告诉抖音服务器请求来自抖音官网，绕过防盗链校验 2. `-o ./download/7615937081646272185.mp4`：将下载的视频保存为指定路径下的文件 3. 最后一长串URL：抖音官方视频播放地址，包含视频的完整数据 ### 注意事项: 1. 视频真实链接有时效性，过期后需要重新获取最新的播放地址 2. 无需携带其他额外请求头，Referer头已经足够绕过大部分防盗链限制 3. 下载目录需提前创建，避免命令执行失败


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: guoma970/mac-multi-instance-deployment (version 1.0.4)

--- name: mac-multi-instance-deployment description: Public-safe Mac multi-instance deployment skill for generic OpenClaw-style workspace layout, boundary notes, sample config, and pack validation. version: 1.0.4 --- # Mac Multi-Instance Deployment / Mac 多实例部署 Keep a generic Mac multi-instance workspace public-safe. ## Checklist - `main`: routing and shared docs - `workbench`: active edits and tests - `publish`: release bundles - `archive`: snapshots and references - `private`: secrets and runtime state - Use placeholder paths in `config/local-multi-instance.example.env` - Review `references/instances.md` - Run `./validate_repo.sh` - Run `./generate_public_pack.sh --dry-run` ## Guardrails - Use generic labels only. - Keep one workspace root per role. - Keep private files out of public packs. - Keep runtime state local.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: zzhimin/audio-recognition (version 1.0.0)

--- name: audio-recognition description: | 音频语音识别服务(Speech-to-Text)。当用户上传音频文件，需要将语音内容转换为文字，或需要识别音频中的特定信息（如关键词、歌曲名）时触发。 适用于：(1) 会议录音转写 (2) 音频内容提取 (3) 语音指令识别 (4) 音视频字幕生成 --- # 音频语音识别 (Audio Recognition) 将音频中的语音准确转写为文字，并能区分不同说话人。 ## 核心能力 - 语音转文字 (Speech-to-Text) - 说话人分离 (Diarization) - 标点与断句优化 - 支持多语言识别 ## 工作流程 ### 1. 音频预处理 - 降噪处理 - 格式转换 (统一为16kHz/16bit PCM或MP3) - 音量标准化 ### 2. 声学特征提取 - 提取MFCC、FBANK等声学特征 - 用于后续ASR模型输入 ### 3. ASR语音识别 - 使用ASR模型进行语音识别 - 生成文字初稿 - 支持模型：Whisper、WeNet、Paraformer等 ### 4. 后处理 - 文字纠错 - 断句与标点添加 - 说话人分离标注 ### 5. 输出结果 - 最终识别文本 - 说话人标签（如需要） - 时间戳（如需要） ## 质量目标 - 准确率：95%以上（标准普通话录音） - 实时性：支持实时和离线两种模式 ## 限制说明 1. **噪音限制**：背景噪音过大时识别效果下降 2. **口音限制**：重度方言/口音可能影响准确率 3. **隐私保护**：用户上传的音频仅用于本次识别，不得用于模型训练或其他用途 4. **语义理解**：仅负责语音转文字，不理解文本语义内容 ## 参考服务 - 讯飞听见 - Google Speech-to-Text - 阿里云语音识别 - 腾讯云语音识别 ## 适用场景 - 会议纪要自动生成 - 音频/视频字幕制作 - 语音内容检索 - 录音文件整理


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: bunsdev/tinyfish-agent-run (version 1.0.0)

--- name: tinyfish-agent-run description: Run a TinyFish automation agent against a URL and stream live progress events (STARTED / PROGRESS / COMPLETE) as one-line JSON events. Use when you want to execute an autonomous browsing goal and surface each step as it happens. homepage: https://docs.tinyfish.ai/agent-api requires: env: - TINYFISH_API_KEY --- # TinyFish Agent Run Execute an autonomous browsing goal against a URL and stream live events. Each SSE event is re-emitted on stdout as a single JSON line so a caller (subagent, TUI, etc.) can display progress as it arrives. Requires: `TINYFISH_API_KEY` environment variable. ## Pre-flight Check (REQUIRED) ```bash [ -n "$TINYFISH_API_KEY" ] && echo "TINYFISH_API_KEY is set" || echo "TINYFISH_API_KEY is NOT set" ``` If the key is not set, stop and ask the user to add it. Get one at <https://agent.tinyfish.ai/api-keys>. ## Streaming Run ```bash scripts/agent-run.sh <url> <goal> ``` Example: ```bash scripts/agent-run.sh https://scrapeme.live/shop "Extract the first 2 product names and prices. Return JSON." ``` Under the hood this POSTs to `https://agent.tinyfish.ai/v1/automation/run-sse` with: ```json { "url": "https://scrapeme.live/shop", "goal": "Extract the first 2 product names and prices. Return JSON." } ``` and the header `X-[REDACTED_SECRET]`. ## Output Format One JSON object per line on stdout: ```json {"type":"STARTED","run_id":"abc123"} {"type":"PROGRESS","run_id":"abc123","purpose":"Navigating to https://scrapeme.live/shop"} {"type":"PROGRESS","run_id":"abc123","purpose":"Reading product list"} {"type":"COMPLETE","run_id":"abc123","status":"COMPLETED","result":{...}} ``` A caller can: - Render each `PROGRESS.purpose` as a live status line. - Detect navigation by matching `purpose` against `Navigating to <url>` and surface the URL to an embedded browser view. - Parse `COMPLETE.result` for the final payload. ## Event Types - `STARTED` — `{type, run_id}` — emitted once when the run begins. - `PROGRESS` — `{type, run_id, purpose}` — one per agent step. `purpose` is a short human-readable description. - `COMPLETE` — `{type, run_id, status, result}` — emitted once when the run finishes. `status` is typically `COMPLETED`.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: ibluewind/andrew-google-calendar (version 1.0.0)

--- name: andrew-google-calendar description: Google Calendar API ���� �� 조�, ��, ��, �� �리. OAuth 2.0 �� ��. ���� �� �린��� ��� ���고 �리�� � ��. --- # Google Calendar ## Overview Google Calendar API 를 ���� ���� ��� 조�, ��, ��, ���� � �� ������. OAuth 2.0 ��� ���� ���� �� �린�� �근����. ## Setup ### 1. OAuth ������� �� �� ```bash # Google Cloud Console �� OAuth ������� �� ���� # https://console.cloud.google.com/apis/credentials # �� ��� � ����리� 복� cp ~/Downloads/client_secret_*.json ~/.google-credentials.json ``` ### 2. �존� �� ```bash pip install google-api-python-client google-auth-httplib2 google-auth-oauthlib ``` ### 3. �� ���� ```bash cd /Users/andrew/.openclaw/workspace/google-calendar python3 scripts/oauth_setup.py ``` 첫 ��� ����� �리고 Google ���� �그�� � ��� ����� ����. ## Capabilities ### �� 조� **��� �� ��:** ``` "�� 7 � ��� 보��" "�� ��� ��?" "�� 주 �� 목� �려�" ``` **��� 기� 조�:** ``` "4 � 15 ���� 20 ��� ��� 보��" ``` ### �� �� **� �� ��:** ``` "�� �� 2 �� � 미� �� ����, 1 �� ��, Zoom ��" "�� 주 ��� 10 �� dentist ��, 30 �" ``` ### �� �� **�� �경:** ``` "�� �� 2 � 미�� �� 3 �� ���" "�� �목� '� 미�'�� '����� ��� 미�'�� �경���" ``` ### �� �� **�� 취�:** ``` "�� �� 2 � 미� 취����" ``` ## Usage Examples ### �� 1: ��� �� 조� ```python from scripts.calendar_ops import list_events, format_event # �� 7 � �� 조� events = list_events(max_results=10) for event in events: print(format_event(event)) ``` ### �� 2: � �� �� ```python from scripts.calendar_ops import create_event from datetime import datetime, timedelta # �� �� 2 � �� �� start = datetime.now() + timedelta(days=1, hours=14) end = start + timedelta(hours=1) event = create_event( summary="� 미�", start_time=start.isoformat(), end_time=end.isoformat(), description="주� ����� ���", location="Zoom" ) ``` ### �� 3: �린� 목� �� ```python from scripts.oauth_setup import list_calendars calendars = list_calendars() for cal in calendars: print(f"{cal['summary']} - {cal['accessRole']}") ``` ## Files Structure ``` google-calendar/ ��� SKILL.md ��� scripts/ � ��� oauth_setup.py # OAuth 2.0 �� � ���� �리 � ��� calendar_ops.py # Calendar API �� ���� ��� references/ ``` ## Security Notes - OAuth ����� `~/.google-calendar-token.pickle` � ����� - ������� ��� `~/.google-credentials.json` � ����� - � ���� `.gitignore` � ����� ���� - �� ��: `https://www.googleapis.com/auth/calendar` (�기/�기 �체 �근) ## Troubleshooting **"OAuth ������� �� ��� ����" ��:** - Google Cloud Console �� OAuth 2.0 ������� ��를 �� ���� - `client_secret_XXXXXX.json` ��� `~/.google-credentials.json` �� 복� **�� ���:** - ���� ��� ���고 ���: `rm ~/.google-calendar-token.pickle` - Google Cloud Console �� API ��� �� **�� ��:** - OAuth �� �면�� ��� �� �� - ����� �� � ���


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

--- name: deploy-public description: Private-to-public repo sync. Copies everything except ai/ to the public mirror. Creates PR, merges, syncs releases. license: MIT interface: [cli, skill] metadata: display-name: "Private-to-Public Sync" version: "1.3.0" homepage: "https://github.com/wipcomputer/wip-ai-devops-toolbox" author: "Parker Todd Brooks" category: dev-tools capabilities: - repo-sync - release-sync requires: bins: [git, gh, bash] openclaw: requires: bins: [git, gh, bash] emoji: "🚢" compatibility: Requires git, gh (GitHub CLI), bash. --- # deploy-public Private-to-public repo sync. One script for all repos. Copies code, creates a PR on the public repo, merges it, and syncs GitHub releases. ## When to Use This Skill **Use deploy-public for:** - Publishing a private repo's code to its public counterpart - After running `wip-release` on the private repo (release must exist first) - Syncing release notes from private to public **CRITICAL: Release order matters.** 1. Merge PR to private repo's main 2. Run `wip-release` (creates GitHub release with notes on private repo) 3. THEN run `deploy-public.sh` (pulls notes from private release) If you skip step 2, the public release gets empty notes. ### Do NOT Use For - Repos without a `-private` counterpart - First-time repo setup (create the public repo on GitHub first) ## API Reference ### CLI ```bash bash scripts/deploy-public.sh /path/to/private-repo org/public-repo ``` ### Examples ```bash # Deploy memory-crystal bash scripts/deploy-public.sh /path/to/memory-crystal-private wipcomputer/memory-crystal # Deploy wip-dev-tools bash scripts/deploy-public.sh /path/to/wip-ai-devops-toolbox-private wipcomputer/wip-ai-devops-toolbox ``` ## What It Does 1. Clones the public repo to a temp directory 2. Copies all files from private repo (excluding `ai/`, `.git/`) 3. Creates a branch, commits, pushes, creates PR 4. Merges the PR (regular merge, never squash) 5. Syncs GitHub releases (pulls notes from private repo's releases)

path: package.json
content: {
  "name": "@wipcomputer/deploy-public",
  "version": "1.9.70",
  "description": "Private-to-public repo sync. Excludes ai/ folder, creates PR, merges, cleans up branches.",
  "bin": {
    "deploy-public": "./deploy-public.sh"
  },
  "license": "MIT"
}


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: thedalbee/wadiz-dm-pipeline (version 1.0.0)

--- name: wadiz-dm-pipeline description: "와디즈/텀블벅 펀딩 프로젝트를 크롤링해서 달성률 50~99% 메이커에게 보낼 개인화 DM을 자동 생성하는 파이프라인. 달비님 맥에서 직접 실행. 사용 시 — 와디즈 DM 뽑아줘, 텀블벅 프로젝트 스크랩해서 DM 만들어줘, 광고 소재 서비스 DM 파이프라인 돌려줘." --- # Wadiz DM Pipeline 와디즈/텀블벅 카테고리 페이지 크롤링 → 달성률 50~99% 필터 → 프로젝트 분석 → 개인화 DM 생성. ## 실행 방법 ```bash python3 scripts/pipeline.py [카테고리] [최대개수] ``` **카테고리 옵션:** - `food` — 식품 - `beauty` — 뷰티 - `lifestyle` — 라이프스타일 - `fashion` — 패션 - `all` — 전체 (기본값) **예시:** ```bash python3 scripts/pipeline.py all 100 python3 scripts/pipeline.py beauty 50 ``` ## 출력 실행 후 `output/dm_results_YYYYMMDD.csv` 파일 생성: - 프로젝트명, URL, 달성률, 카테고리 - 개인화 DM 텍스트 (즉시 복붙 가능) ## DM 오퍼 설정 `references/dm-template.md` 참조. 현재 오퍼: **무료 소재 10개 먼저 제작, 마음에 들면 결제**. ## 주의사항 - 달비님 맥 로컬에서만 실행 (서버 IP는 CDN 차단됨) - Playwright 필요: `pip install playwright && python -m playwright install chromium` - 과도한 요청 방지를 위해 요청 간 2~3초 딜레이 내장 - 결과 파일은 `output/` 폴더에 저장됨


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: samdickson22/edith-augment-code (version 1.0.0)

--- name: edith-augment-code description: Use Augment Code (Auggie CLI) to analyze, generate, and modify code through Edith smart glasses or OpenClaw. Triggers when the user asks to build, code, debug, analyze, or prototype something. user-invocable: true --- # Augment Code via Auggie CLI Use Augment Code's powerful context engine and agentic coding capabilities through OpenClaw. This skill wraps the `auggie` CLI to let users generate code, analyze projects, debug issues, and build prototypes — hands-free through Edith glasses or any OpenClaw channel. ## Prerequisites - Auggie CLI installed: `npm install -g @augmentcode/auggie` - Logged in: `auggie login` ## When to use Trigger this skill when the user asks to: - Build, create, or scaffold something ("build me a landing page", "create a REST API") - Analyze or review code ("analyze this codebase", "review this function") - Debug or fix issues ("why is this failing", "fix the auth bug") - Prototype or generate code ("prototype a todo app", "generate a React component") - Get code suggestions or insights ("how should I structure this", "what's wrong with this approach") ## How to use ### Generate code or build something Run auggie in print mode for one-shot tasks: ```bash auggie --print "Build a simple Express API with /health and /users endpoints" 2>&1 ``` ### Analyze the current project ```bash auggie --print "Analyze this codebase and give me a summary of the architecture" 2>&1 ``` ### Debug an issue ```bash auggie --print "Look at the recent error in src/ws-relay.ts and suggest a fix" 2>&1 ``` ### Get quiet/structured output For clean responses without step details: ```bash auggie --print --quiet "What dependencies does this project use and are any outdated?" 2>&1 ``` ## Response formatting When returning results to the user (especially through Edith glasses voice output): - Summarize the key output concisely - For code generation: describe what was created and where - For analysis: give the top 3-5 findings - For debugging: state the root cause and fix - Keep it conversational and brief — this may be spoken aloud through glasses ## Error handling - If `auggie` is not installed: tell the user to run `npm install -g @augmentcode/auggie` - If not logged in: tell the user to run `auggie login` - If the command times out: suggest breaking the task into smaller pieces - Auggie may take 10-30 seconds for complex tasks — warn the user if it's a big request

path: shipables.json
content: {
  "name": "edith-augment-code",
  "version": "1.0.0",
  "description": "Use Augment Code's Auggie CLI to build, analyze, and debug code through OpenClaw and Edith smart glasses",
  "keywords": ["augment", "auggie", "code-generation", "edith", "smart-glasses", "openclaw"]
}


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: kk43994/kkclaw (version 3.1.2)

--- name: kkclaw description: 给 OpenClaw 加一个真正可长期使用的桌面身体：流体玻璃球 UI、14 情绪系统、语音播报/声音克隆、Setup Wizard、Doctor 自检、模型热切换、Gateway 守护与诊断。 --- # kkclaw kkclaw 不是“单纯的桌面宠物”，而是一套给 OpenClaw 用的 **桌面可视化交互层 + 运维辅助工具箱**。 适合这些场景： - 你想让 OpenClaw 不再只是终端/聊天框，而是有状态、有情绪、有语音反馈的桌面助手 - 你希望 Agent 收到消息、开始执行、报错、完成时，能更自然地被感知到 - 你经常切换模型 / Provider，希望配置和切换过程更顺手 - 你希望 Gateway 出问题时更容易诊断、恢复和长期挂着跑 - 你想基于现成桌面壳层继续做自己的桌面 Agent / 桌面 AI 助手 ## 核心能力 - **流体玻璃球桌面 UI**：轻量、常驻、可感知 Agent 状态 - **14 情绪系统**：让思考、说话、完成、异常都有明显状态差异 - **语音系统**：支持语音播报、停顿控制、声音克隆/多引擎降级 - **Setup Wizard**：新手也能更快完成首次配置 - **Doctor 自检**：检查 Gateway、模型、TTS、歌词窗、端口、日志等 - **模型与 Provider 管理**：更方便地切换模型、管理多 Provider - **长期运行增强**：Gateway 守护、错误恢复、诊断提示 ## 你装上后能得到什么 1. **桌面上一直有一个能感知状态的 Agent** 不用一直盯终端、日志和聊天窗口。 2. **消息和任务不再只是冷冰冰的一行字** 收到消息、开始执行、完成、异常时都有更自然的反馈。 3. **更适合长期挂着跑** 出问题时更容易知道是哪一层挂了，也更容易恢复。 4. **更低的上手门槛** Setup Wizard、配置向导、诊断工具会比手改配置省心很多。 5. **更适合二次开发** 如果你想给自己的 Agent 做“身体”或桌面 UI，这就是现成基础层。 ## 快速开始 先看详细安装说明：`references/setup.md` 最常见的源码运行方式： ```bash git clone https://github.com/kk43994/kkclaw.git cd kkclaw npm install npm start ``` 如果你需要图形化安装包，也可以直接看 Releases： - GitHub: https://github.com/kk43994/kkclaw - Releases: https://github.com/kk43994/kkclaw/releases - Demo: https://kk43994.github.io/kkclaw/ ## 什么时候推荐读参考文件 - 想快速安装和启动：读 `references/setup.md` - 想知道 v3.1.2 更新了什么：读 `references/v3-1-2.md` - 想先理解定位和价值：读 `references/why-kkclaw.md` ## 注意 - kkclaw 是 **OpenClaw 的桌面增强层**，不是 OpenClaw 本体 - 想获得完整体验，建议先保证 OpenClaw Gateway 可正常运行 - 对长期使用来说，源码运行通常比只下载发行版更灵活


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