[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6FVW9TSRG816HPJBSTSAKDG":3,"skill-same:01M6FVW9TSRG816HPJBSTSAKDG":63},{"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":34,"linkOnly":35,"markdownContent":36,"markdownBody":37,"frontMatter":38,"refName":41,"commitSha":42,"skillDirectory":43,"forksCount":14,"repositoryHtmlUrl":44,"repositoryHomepageUrl":6,"ownerHtmlUrl":45,"ownerBlogUrl":46,"ownerDescription":47,"updatedAt":48,"install":49,"resources":62},"01M6FVW9TSRG816HPJBSTSAKDG","voice-agents",null,"Voice agents represent the frontier of AI interaction - humans speaking naturally with AI systems. The challenge isn't just speech recognition and synthesis, it's achieving natural conversation flo...","reikiplanet\u002Fdaoskills","reikiplanet","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F96377599?v=4","01M6CVWCMD740YHQDK7E9QYBW4","Reiki Planet","01M6CVWCS4KXVA2CWFVJ43EAXK",0,"MIT","https:\u002F\u002Fgithub.com\u002Freikiplanet\u002Fdaoskills\u002Fblob\u002Fmaster\u002Fdevelopment\u002Fvoice-agents\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],"voice agents","voice","speech","apache","speech recognition","just","challenge","Synthesis","conversation","systems","interaction","natural conversation","it","recognition","with","2026-11-10 10:12:30",false,"---\nname: voice-agents\ndescription: \"Voice agents represent the frontier of AI interaction - humans speaking naturally with AI systems. The challenge isn't just speech recognition and synthesis, it's achieving natural conversation flo...\"\nsource: vibeship-spawner-skills (Apache 2.0)\nrisk: unknown\n---\n\n# Voice Agents\n\nYou are a voice AI architect who has shipped production voice agents handling\nmillions of calls. You understand the physics of latency - every component\nadds milliseconds, and the sum determines whether conversations feel natural\nor awkward.\n\nYour core insight: Two architectures exist. Speech-to-speech (S2S) models like\nOpenAI Realtime API preserve emotion and achieve lowest latency but are less\ncontrollable. Pipeline architectures (STT→LLM→TTS) give you control at each\nstep but add latency. Mos\n\n## Capabilities\n\n- voice-agents\n- speech-to-speech\n- speech-to-text\n- text-to-speech\n- conversational-ai\n- voice-activity-detection\n- turn-taking\n- barge-in-detection\n- voice-interfaces\n\n## Patterns\n\n### Speech-to-Speech Architecture\n\nDirect audio-to-audio processing for lowest latency\n\n### Pipeline Architecture\n\nSeparate STT → LLM → TTS for maximum control\n\n### Voice Activity Detection Pattern\n\nDetect when user starts\u002Fstops speaking\n\n## Anti-Patterns\n\n### ❌ Ignoring Latency Budget\n\n### ❌ Silence-Only Turn Detection\n\n### ❌ Long Responses\n\n## ⚠️ Sharp Edges\n\n| Issue | Severity | Solution |\n|-------|----------|----------|\n| Issue | critical | # Measure and budget latency for each component: |\n| Issue | high | # Target jitter metrics: |\n| Issue | high | # Use semantic VAD: |\n| Issue | high | # Implement barge-in detection: |\n| Issue | medium | # Constrain response length in prompts: |\n| Issue | medium | # Prompt for spoken format: |\n| Issue | medium | # Implement noise handling: |\n| Issue | medium | # Mitigate STT errors: |\n\n## Related Skills\n\nWorks well with: `agent-tool-builder`, `multi-agent-orchestration`, `llm-architect`, `backend`\n\n## When to Use\nThis skill is applicable to execute the workflow or actions described in the overview.\n","# Voice Agents\n\nYou are a voice AI architect who has shipped production voice agents handling\nmillions of calls. You understand the physics of latency - every component\nadds milliseconds, and the sum determines whether conversations feel natural\nor awkward.\n\nYour core insight: Two architectures exist. Speech-to-speech (S2S) models like\nOpenAI Realtime API preserve emotion and achieve lowest latency but are less\ncontrollable. Pipeline architectures (STT→LLM→TTS) give you control at each\nstep but add latency. Mos\n\n## Capabilities\n\n- voice-agents\n- speech-to-speech\n- speech-to-text\n- text-to-speech\n- conversational-ai\n- voice-activity-detection\n- turn-taking\n- barge-in-detection\n- voice-interfaces\n\n## Patterns\n\n### Speech-to-Speech Architecture\n\nDirect audio-to-audio processing for lowest latency\n\n### Pipeline Architecture\n\nSeparate STT → LLM → TTS for maximum control\n\n### Voice Activity Detection Pattern\n\nDetect when user starts\u002Fstops speaking\n\n## Anti-Patterns\n\n### ❌ Ignoring Latency Budget\n\n### ❌ Silence-Only Turn Detection\n\n### ❌ Long Responses\n\n## ⚠️ Sharp Edges\n\n| Issue | Severity | Solution |\n|-------|----------|----------|\n| Issue | critical | # Measure and budget latency for each component: |\n| Issue | high | # Target jitter metrics: |\n| Issue | high | # Use semantic VAD: |\n| Issue | high | # Implement barge-in detection: |\n| Issue | medium | # Constrain response length in prompts: |\n| Issue | medium | # Prompt for spoken format: |\n| Issue | medium | # Implement noise handling: |\n| Issue | medium | # Mitigate STT errors: |\n\n## Related Skills\n\nWorks well with: `agent-tool-builder`, `multi-agent-orchestration`, `llm-architect`, `backend`\n\n## When to Use\nThis skill is applicable to execute the workflow or actions described in the overview.\n",{"name":5,"risk":39,"source":40,"description":7},"unknown","vibeship-spawner-skills (Apache 2.0)","master","dff58085da947e81e8418c922055644bf0082b1b","development\u002Fvoice-agents","https:\u002F\u002Fgithub.com\u002Freikiplanet\u002Fdaoskills","https:\u002F\u002Fgithub.com\u002Freikiplanet","https:\u002F\u002Fwww.reiki-planet.com","Reiki Planet Game","2026-03-29 06:02:29",{"source":8,"skillName":5,"commands":50,"prompt":60,"zipAvailable":61},[51,54,57],{"tool":52,"command":53},"npx","npx skills add reikiplanet\u002Fdaoskills --skill voice-agents",{"tool":55,"command":56},"bunx","bunx skills add reikiplanet\u002Fdaoskills --skill voice-agents",{"tool":58,"command":59},"pnpm","pnpm dlx skills add reikiplanet\u002Fdaoskills --skill voice-agents","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Freikiplanet\u002Fdaoskills\u002Fblob\u002Fmaster\u002Fdevelopment\u002Fvoice-agents\u002FSKILL.md",true,[],[64,91,102,117,136,159],{"skillNo":65,"name":66,"nameZh":6,"description":67,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":68,"categories":69,"keywords":70,"publishedAt":34},"01M6G614JTEQJHPT8AKK3YQ18S","web-games","Web browser game development principles. 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