[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M778DX94K977RY24Y6EBPHFN":3,"skill-same:01M778DX94K977RY24Y6EBPHFN":47},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":19,"linkOnly":20,"markdownContent":21,"markdownBody":22,"frontMatter":23,"refName":24,"commitSha":25,"skillDirectory":26,"forksCount":27,"repositoryHtmlUrl":28,"repositoryHomepageUrl":6,"ownerHtmlUrl":29,"ownerBlogUrl":30,"ownerDescription":31,"updatedAt":32,"install":33,"resources":46},"01M778DX94K977RY24Y6EBPHFN","livekit",null,"Build voice AI agents with LiveKit. Use when developing realtime voice applications, voice agent pipelines (STT-LLM-TTS), WebRTC communication, or deploying conversational AI. Covers LiveKit Agents SDK, provider selection (Deepgram, OpenAI, ElevenLabs, Cartesia), cloud vs self-hosted deployment.","javimosch\u002Fopen-claw-skills","javimosch","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F12900508?v=4","01M6D3F2AS6PV75ET9PZ1QGP8J","Javier Leandro Arancibia","01M75B8NCTAJG9WH5YNZH7C3D8",0,"MIT","https:\u002F\u002Fgithub.com\u002Fjavimosch\u002Fopen-claw-skills\u002Fblob\u002Fmain\u002Fskills\u002Fzoroposkai\u002Flivekit\u002FSKILL.md",[],[],"2026-11-15 14:19:17",false,"---\nname: livekit\ndescription: Build voice AI agents with LiveKit. Use when developing realtime voice applications, voice agent pipelines (STT-LLM-TTS), WebRTC communication, or deploying conversational AI. Covers LiveKit Agents SDK, provider selection (Deepgram, OpenAI, ElevenLabs, Cartesia), cloud vs self-hosted deployment.\n---\n\n# LiveKit Voice AI Skill\n\nBuild production voice agents with LiveKit's open-source platform.\n\n## Quick Start\n\n```bash\n# Install SDK\npip install livekit-agents livekit-plugins-openai livekit-plugins-deepgram livekit-plugins-cartesia\n\n# Or Node.js\nnpm install @livekit\u002Fagents @livekit\u002Fagents-plugin-openai\n```\n\n## Minimal Agent (Python)\n\n```python\nfrom livekit.agents import AgentSession, JobContext, WorkerOptions, cli\nfrom livekit.plugins import deepgram, openai, cartesia\n\nasync def entrypoint(ctx: JobContext):\n    await ctx.connect()\n    \n    session = AgentSession(\n        stt=deepgram.STT(),\n        llm=openai.LLM(model=\"gpt-4.1-mini\"),\n        tts=cartesia.TTS(),\n    )\n    \n    session.start(ctx.room)\n    await session.say(\"Hello! How can I help?\")\n\nif __name__ == \"__main__\":\n    cli.run_app(WorkerOptions(entrypoint_fnc=entrypoint))\n```\n\n## Provider Selection\n\n| Component | Budget | Quality | Low Latency |\n|-----------|--------|---------|-------------|\n| **STT** | Deepgram Nova-3 | AssemblyAI | Deepgram Keychain |\n| **LLM** | GPT-4.1 mini | Claude Sonnet | GPT-4.1 mini |\n| **TTS** | Cartesia Sonic-3 | ElevenLabs | Cartesia Sonic-3 |\n\n## Voice Pipeline vs Realtime\n\n**STT-LLM-TTS Pipeline:**\n- More control, mix providers\n- Generally cheaper\n- Easier to debug\n\n**OpenAI Realtime API:**\n- Speech-to-speech, more expressive\n- Higher cost (~$0.10\u002Fmin)\n- Less control\n\n## Environment Variables\n\n```bash\nLIVEKIT_URL=wss:\u002F\u002Fyour-app.livekit.cloud\nLIVEKIT_API_KEY=your-api-key\nLIVEKIT_API_SECRET=your-api-secret\n\n# Provider keys (if not using LiveKit Inference)\nOPENAI_API_KEY=\nDEEPGRAM_API_KEY=\nCARTESIA_API_KEY=\nELEVENLABS_API_KEY=\n```\n\n## Tool Use\n\n```python\nfrom livekit.agents import function_tool\n\n@function_tool()\nasync def get_weather(location: str) -> str:\n    \"\"\"Get current weather for a location.\"\"\"\n    # Your implementation\n    return f\"Weather in {location}: 72°F, sunny\"\n\nsession = AgentSession(\n    stt=deepgram.STT(),\n    llm=openai.LLM(),\n    tts=cartesia.TTS(),\n    tools=[get_weather],\n)\n```\n\n## Telephony (SIP)\n\n```python\nfrom livekit import api\n\n# Outbound call\nawait lk_api.sip.create_sip_participant(\n    api.CreateSIPParticipantRequest(\n        sip_trunk_id=\"trunk-id\",\n        sip_call_to=\"+15551234567\",\n        room_name=\"my-room\",\n    )\n)\n```\n\n## Deployment\n\n**LiveKit Cloud:** `livekit-server-cli deploy --project my-project`\n\n**Self-hosted:** \n```bash\ndocker run -d \\\n  -p 7880:7880 -p 7881:7881 -p 7882:7882\u002Fudp \\\n  -e LIVEKIT_KEYS=\"api-key: api-secret\" \\\n  livekit\u002Flivekit-server\n```\n\n## Cost Estimates\n\n| Scenario | Monthly Cost |\n|----------|--------------|\n| Dev\u002Ftesting | Free tier |\n| 100 hrs\u002Fmo voice | ~$150-250 |\n| Production B2B | ~$300-500 |\n| High volume | Self-host |\n\n## Common Patterns\n\n### Turn Detection\n```python\nsession = AgentSession(\n    turn_detection=openai.TurnDetection(\n        threshold=0.5,\n        silence_duration_ms=500,\n    ),\n    ...\n)\n```\n\n### Interruption Handling\n```python\n@session.on(\"user_speech_started\")\nasync def handle_interruption():\n    session.stop_speaking()\n```\n\n### Multi-Agent Handoff\n```python\nawait session.transfer_to(specialist_agent)\n```\n\n## References\n\n- Docs: https:\u002F\u002Fdocs.livekit.io\u002Fagents\u002F\n- Examples: https:\u002F\u002Fgithub.com\u002Flivekit\u002Fagents\u002Ftree\u002Fmain\u002Fexamples\n- Playground: https:\u002F\u002Fagents-playground.livekit.io\n","# LiveKit Voice AI Skill\n\nBuild production voice agents with LiveKit's open-source platform.\n\n## Quick Start\n\n```bash\n# Install SDK\npip install livekit-agents livekit-plugins-openai livekit-plugins-deepgram livekit-plugins-cartesia\n\n# Or Node.js\nnpm install @livekit\u002Fagents @livekit\u002Fagents-plugin-openai\n```\n\n## Minimal Agent (Python)\n\n```python\nfrom livekit.agents import AgentSession, JobContext, WorkerOptions, cli\nfrom livekit.plugins import deepgram, openai, cartesia\n\nasync def entrypoint(ctx: JobContext):\n    await ctx.connect()\n    \n    session = AgentSession(\n        stt=deepgram.STT(),\n        llm=openai.LLM(model=\"gpt-4.1-mini\"),\n        tts=cartesia.TTS(),\n    )\n    \n    session.start(ctx.room)\n    await session.say(\"Hello! How can I help?\")\n\nif __name__ == \"__main__\":\n    cli.run_app(WorkerOptions(entrypoint_fnc=entrypoint))\n```\n\n## Provider Selection\n\n| Component | Budget | Quality | Low Latency |\n|-----------|--------|---------|-------------|\n| **STT** | Deepgram Nova-3 | AssemblyAI | Deepgram Keychain |\n| **LLM** | GPT-4.1 mini | Claude Sonnet | GPT-4.1 mini |\n| **TTS** | Cartesia Sonic-3 | ElevenLabs | Cartesia Sonic-3 |\n\n## Voice Pipeline vs Realtime\n\n**STT-LLM-TTS Pipeline:**\n- More control, mix providers\n- Generally cheaper\n- Easier to debug\n\n**OpenAI Realtime API:**\n- Speech-to-speech, more expressive\n- Higher cost (~$0.10\u002Fmin)\n- Less control\n\n## Environment Variables\n\n```bash\nLIVEKIT_URL=wss:\u002F\u002Fyour-app.livekit.cloud\nLIVEKIT_API_KEY=your-api-key\nLIVEKIT_API_SECRET=your-api-secret\n\n# Provider keys (if not using LiveKit Inference)\nOPENAI_API_KEY=\nDEEPGRAM_API_KEY=\nCARTESIA_API_KEY=\nELEVENLABS_API_KEY=\n```\n\n## Tool Use\n\n```python\nfrom livekit.agents import function_tool\n\n@function_tool()\nasync def get_weather(location: str) -> str:\n    \"\"\"Get current weather for a location.\"\"\"\n    # Your implementation\n    return f\"Weather in {location}: 72°F, sunny\"\n\nsession = AgentSession(\n    stt=deepgram.STT(),\n    llm=openai.LLM(),\n    tts=cartesia.TTS(),\n    tools=[get_weather],\n)\n```\n\n## Telephony (SIP)\n\n```python\nfrom livekit import api\n\n# Outbound call\nawait lk_api.sip.create_sip_participant(\n    api.CreateSIPParticipantRequest(\n        sip_trunk_id=\"trunk-id\",\n        sip_call_to=\"+15551234567\",\n        room_name=\"my-room\",\n    )\n)\n```\n\n## Deployment\n\n**LiveKit Cloud:** `livekit-server-cli deploy --project my-project`\n\n**Self-hosted:** \n```bash\ndocker run -d \\\n  -p 7880:7880 -p 7881:7881 -p 7882:7882\u002Fudp \\\n  -e LIVEKIT_KEYS=\"api-key: api-secret\" \\\n  livekit\u002Flivekit-server\n```\n\n## Cost Estimates\n\n| Scenario | Monthly Cost |\n|----------|--------------|\n| Dev\u002Ftesting | Free tier |\n| 100 hrs\u002Fmo voice | ~$150-250 |\n| Production B2B | ~$300-500 |\n| High volume | Self-host |\n\n## Common Patterns\n\n### Turn Detection\n```python\nsession = AgentSession(\n    turn_detection=openai.TurnDetection(\n        threshold=0.5,\n        silence_duration_ms=500,\n    ),\n    ...\n)\n```\n\n### Interruption Handling\n```python\n@session.on(\"user_speech_started\")\nasync def handle_interruption():\n    session.stop_speaking()\n```\n\n### Multi-Agent Handoff\n```python\nawait session.transfer_to(specialist_agent)\n```\n\n## References\n\n- Docs: https:\u002F\u002Fdocs.livekit.io\u002Fagents\u002F\n- Examples: https:\u002F\u002Fgithub.com\u002Flivekit\u002Fagents\u002Ftree\u002Fmain\u002Fexamples\n- Playground: https:\u002F\u002Fagents-playground.livekit.io\n",{"name":5,"description":7},"main","f9d3fe7cf9ac8f1ea63a0d96e98e1f510a3814db","skills\u002Fzoroposkai\u002Flivekit",1,"https:\u002F\u002Fgithub.com\u002Fjavimosch\u002Fopen-claw-skills","https:\u002F\u002Fgithub.com\u002Fjavimosch","intrane.fr","Building robust, open-source infrastructure for the commons. AI-leveraged, self-hosted, built to last.","2026-06-07 03:34:58",{"source":8,"skillName":5,"commands":34,"prompt":44,"zipAvailable":45},[35,38,41],{"tool":36,"command":37},"npx","npx skills add javimosch\u002Fopen-claw-skills --skill livekit",{"tool":39,"command":40},"bunx","bunx skills add javimosch\u002Fopen-claw-skills --skill livekit",{"tool":42,"command":43},"pnpm","pnpm dlx skills add javimosch\u002Fopen-claw-skills --skill livekit","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fjavimosch\u002Fopen-claw-skills\u002Fblob\u002Fmain\u002Fskills\u002Fzoroposkai\u002Flivekit\u002FSKILL.md",true,[],[48,55,62,69,76,83],{"skillNo":49,"name":50,"nameZh":6,"description":51,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":52,"categories":53,"keywords":54,"publishedAt":19},"01M778GGXG2VQ0YF31W2MKGMQZ","crowd-prompting","A marketplace where AI agents improve prompts, system instructions, tool descriptions, and other text-based content with domain expertise from real-world operations — and earn tokens for valuable contributions.","https:\u002F\u002Fgithub.com\u002Fjavimosch\u002Fopen-claw-skills\u002Fblob\u002Fmain\u002Fskills\u002Fzzadrian\u002Fcrowd-prompting\u002FSKILL.md",[],[],{"skillNo":56,"name":57,"nameZh":6,"description":58,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":59,"categories":60,"keywords":61,"publishedAt":19},"01M778G7BH8SBJ9FJ6C3G7CB1K","ceaser","Interact with the Ceaser privacy protocol on Base L2 using the ceaser-mcp MCP tools. This skill uses the ceaser-mcp npm package for ALL operations -- shield, unshield, note management, and protocol queries. All ceaser tool calls use CLI subcommands (npx -y ceaser-mcp \u003Csubcommand>). Ceaser is a privacy-preserving ETH wrapper using Noir\u002FUltraHonk zero-knowledge proofs on Base L2 (chain ID 8453).","https:\u002F\u002Fgithub.com\u002Fjavimosch\u002Fopen-claw-skills\u002Fblob\u002Fmain\u002Fskills\u002Fzyra-v21\u002Fceaser\u002FSKILL.md",[],[],{"skillNo":63,"name":64,"nameZh":6,"description":65,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":66,"categories":67,"keywords":68,"publishedAt":19},"01M778FYCJQZWFKKX5FYMK3S47","ceaser-send","Fully automated private ETH transfer via Ceaser Protocol on Base L2 using the ceaser-mcp MCP tools. This skill uses the ceaser-mcp npm package for ALL operations -- all ceaser tool calls use CLI subcommands (npx -y ceaser-mcp \u003Csubcommand>). WARNING -- creates observable on-chain links between user wallet and hot wallet (see Privacy Warning). Generates an ephemeral hot wallet with BIP-39 mnemonic recovery, user funds it, agent signs and broadcasts the Shield TX automatically. Exactly one manual step required (funding the hot wallet with ETH). Uses Noir\u002FUltraHonk zero-knowledge proofs.","https:\u002F\u002Fgithub.com\u002Fjavimosch\u002Fopen-claw-skills\u002Fblob\u002Fmain\u002Fskills\u002Fzyra-v21\u002Fceaser-send\u002FSKILL.md",[],[],{"skillNo":70,"name":71,"nameZh":6,"description":72,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":73,"categories":74,"keywords":75,"publishedAt":19},"01M778FQQNSEYA3HJKZBPQ4M9Z","dilemm-ai","Compete in DilemmAI, the prisoner's dilemma AI arena at dilemm.ai. Use when an OpenClaw agent wants to create an account, design and submit strategy prompts for their bot, enter matchmaking, analyze historical matches and leaderboards, and iterate on bot strategy. Requires headless browser automation (no API available yet).","https:\u002F\u002Fgithub.com\u002Fjavimosch\u002Fopen-claw-skills\u002Fblob\u002Fmain\u002Fskills\u002Fzyori\u002Fdilemm-ai\u002FSKILL.md",[],[],{"skillNo":77,"name":78,"nameZh":6,"description":79,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":80,"categories":81,"keywords":82,"publishedAt":19},"01M778FGVZX7QA2TF9BFMM37FY","moldium","Post and manage content on the Moldium blog platform. Triggered by \"post to Moldium\", \"write a blog post\", \"publish an article\", etc.","https:\u002F\u002Fgithub.com\u002Fjavimosch\u002Fopen-claw-skills\u002Fblob\u002Fmain\u002Fskills\u002Fzyom45\u002Fmoldium\u002FSKILL.md",[],[],{"skillNo":84,"name":85,"nameZh":6,"description":86,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":87,"categories":88,"keywords":89,"publishedAt":19},"01M778F88D8PQ9MQ0KNW2TJ8ZH","arxiv-paper-reviews","Interact with arXiv Crawler API to fetch papers, read reviews, submit comments, search papers, and import papers. Use when working with arXiv papers, fetching paper lists by date\u002Fcategory\u002Finterest, viewing paper details with comments, submitting paper reviews, searching papers by title, or importing papers from arXiv URLs via API at http:\u002F\u002Fweakaccept.top:8000\u002F.","https:\u002F\u002Fgithub.com\u002Fjavimosch\u002Fopen-claw-skills\u002Fblob\u002Fmain\u002Fskills\u002Fzxrys\u002Farxiv-paper-reviews\u002FSKILL.md",[],[]]