[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71HQENRE5K0974Y8QZ8HTVR":3,"skill-same:01M71HQENRE5K0974Y8QZ8HTVR":89},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":22,"publishedAt":43,"linkOnly":44,"markdownContent":45,"markdownBody":46,"frontMatter":47,"refName":48,"commitSha":49,"skillDirectory":50,"forksCount":51,"repositoryHtmlUrl":52,"repositoryHomepageUrl":6,"ownerHtmlUrl":53,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":54,"install":55,"resources":68},"01M71HQENRE5K0974Y8QZ8HTVR","alicloud-ai-audio-asr",null,"Transcribe non-realtime speech with Alibaba Cloud Model Studio Qwen ASR models (`qwen3-asr-flash`, `qwen-audio-asr`, `qwen3-asr-flash-filetrans`). Use when converting recorded audio files to text, generating transcripts with timestamps, or documenting DashScope\u002FOpenAI-compatible ASR request and response fields.","JSGforever\u002Fskillguard","JSGforever","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F85541948?v=4","01M71FQD3E132VMR5F4TAYX3YS","01M71FQD4DYW0XJ4XQ4YQH75Y9",2,"GPL-3.0","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__cinience--alicloud-ai-audio-asr\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000016","图像与多媒体","SCENARIO","使用场景",[23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42],"ASR","alicloud ai audio asr","Audio","fields","request","models","qwen3","with","text","realtime","studio","timestamps","when","use","files","qwen asr","transcribe","model","speech","openai-compatible","2026-11-10 10:12:30",false,"---\nname: alicloud-ai-audio-asr\ndescription: Transcribe non-realtime speech with Alibaba Cloud Model Studio Qwen ASR models (`qwen3-asr-flash`, `qwen-audio-asr`, `qwen3-asr-flash-filetrans`). Use when converting recorded audio files to text, generating transcripts with timestamps, or documenting DashScope\u002FOpenAI-compatible ASR request and response fields.\n---\n\nCategory: provider\n\n# Model Studio Qwen ASR (Non-Realtime)\n\n## Validation\n\n```bash\nmkdir -p output\u002Falicloud-ai-audio-asr\npython -m py_compile skills\u002Fai\u002Faudio\u002Falicloud-ai-audio-asr\u002Fscripts\u002Ftranscribe_audio.py && echo \"py_compile_ok\" > output\u002Falicloud-ai-audio-asr\u002Fvalidate.txt\n```\n\nPass criteria: command exits 0 and `output\u002Falicloud-ai-audio-asr\u002Fvalidate.txt` is generated.\n\n## Output And Evidence\n\n- Store transcripts and API responses under `output\u002Falicloud-ai-audio-asr\u002F`.\n- Keep one command log or sample response per run.\n\nUse Qwen ASR for recorded audio transcription (non-realtime), including short audio sync calls and long audio async jobs.\n\n## Critical model names\n\nUse one of these exact model strings:\n- `qwen3-asr-flash`\n- `qwen-audio-asr`\n- `qwen3-asr-flash-filetrans`\n\nSelection guidance:\n- Use `qwen3-asr-flash` or `qwen-audio-asr` for short\u002Fnormal recordings (sync).\n- Use `qwen3-asr-flash-filetrans` for long-file transcription (async task workflow).\n\n## Prerequisites\n\n- Install SDK dependencies (script uses Python stdlib only):\n\n```bash\npython3 -m venv .venv\n. .venv\u002Fbin\u002Factivate\n```\n\n- Set `DASHSCOPE_API_KEY` in environment, or add `dashscope_api_key` to `~\u002F.alibabacloud\u002Fcredentials`.\n\n## Normalized interface (asr.transcribe)\n\n### Request\n- `audio` (string, required): public URL or local file path.\n- `model` (string, optional): default `qwen3-asr-flash`.\n- `language_hints` (array\u003Cstring>, optional): e.g. `zh`, `en`.\n- `sample_rate` (number, optional)\n- `vocabulary_id` (string, optional)\n- `disfluency_removal_enabled` (bool, optional)\n- `timestamp_granularities` (array\u003Cstring>, optional): e.g. `sentence`.\n- `async` (bool, optional): default false for sync models, true for `qwen3-asr-flash-filetrans`.\n\n### Response\n- `text` (string): normalized transcript text.\n- `task_id` (string, optional): present for async submission.\n- `status` (string): `SUCCEEDED` or submission status.\n- `raw` (object): original API response.\n\n## Quick start (official HTTP API)\n\nSync transcription (OpenAI-compatible protocol):\n\n```bash\ncurl -sS --location 'https:\u002F\u002Fdashscope.aliyuncs.com\u002Fcompatible-mode\u002Fv1\u002Fchat\u002Fcompletions' \\\n  --header \"Authorization: Bearer $DASHSCOPE_API_KEY\" \\\n  --header 'Content-Type: application\u002Fjson' \\\n  --data '{\n    \"model\": \"qwen3-asr-flash\",\n    \"messages\": [\n      {\n        \"role\": \"user\",\n        \"content\": [\n          {\n            \"type\": \"input_audio\",\n            \"input_audio\": {\n              \"data\": \"https:\u002F\u002Fdashscope.oss-cn-beijing.aliyuncs.com\u002Faudios\u002Fwelcome.mp3\"\n            }\n          }\n        ]\n      }\n    ],\n    \"stream\": false,\n    \"asr_options\": {\n      \"enable_itn\": false\n    }\n  }'\n```\n\nAsync long-file transcription (DashScope protocol):\n\n```bash\ncurl -sS --location 'https:\u002F\u002Fdashscope.aliyuncs.com\u002Fapi\u002Fv1\u002Fservices\u002Faudio\u002Fasr\u002Ftranscription' \\\n  --header \"Authorization: Bearer $DASHSCOPE_API_KEY\" \\\n  --header 'X-DashScope-Async: enable' \\\n  --header 'Content-Type: application\u002Fjson' \\\n  --data '{\n    \"model\": \"qwen3-asr-flash-filetrans\",\n    \"input\": {\n      \"file_url\": \"https:\u002F\u002Fdashscope.oss-cn-beijing.aliyuncs.com\u002Faudios\u002Fwelcome.mp3\"\n    }\n  }'\n```\n\nPoll task result:\n\n```bash\ncurl -sS --location \"https:\u002F\u002Fdashscope.aliyuncs.com\u002Fapi\u002Fv1\u002Ftasks\u002F\u003Ctask_id>\" \\\n  --header \"Authorization: Bearer $DASHSCOPE_API_KEY\"\n```\n\n## Local helper script\n\nUse the bundled script for URL\u002Flocal-file input and optional async polling:\n\n```bash\npython skills\u002Fai\u002Faudio\u002Falicloud-ai-audio-asr\u002Fscripts\u002Ftranscribe_audio.py \\\n  --audio \"https:\u002F\u002Fdashscope.oss-cn-beijing.aliyuncs.com\u002Faudios\u002Fwelcome.mp3\" \\\n  --model qwen3-asr-flash \\\n  --language-hints zh,en \\\n  --print-response\n```\n\nLong-file mode:\n\n```bash\npython skills\u002Fai\u002Faudio\u002Falicloud-ai-audio-asr\u002Fscripts\u002Ftranscribe_audio.py \\\n  --audio \"https:\u002F\u002Fdashscope.oss-cn-beijing.aliyuncs.com\u002Faudios\u002Fwelcome.mp3\" \\\n  --model qwen3-asr-flash-filetrans \\\n  --async \\\n  --wait\n```\n\n## Operational guidance\n\n- For local files, use `input_audio.data` (data URI) when direct URL is unavailable.\n- Keep `language_hints` minimal to reduce recognition ambiguity.\n- For async tasks, use 5-20s polling interval with max retry guard.\n- Save normalized outputs under `output\u002Falicloud-ai-audio-asr\u002Ftranscripts\u002F`.\n\n## Output location\n\n- Default output: `output\u002Falicloud-ai-audio-asr\u002Ftranscripts\u002F`\n- Override base dir with `OUTPUT_DIR`.\n\n## Workflow\n\n1) Confirm user intent, region, identifiers, and whether the operation is read-only or mutating.\n2) Run one minimal read-only query first to verify connectivity and permissions.\n3) Execute the target operation with explicit parameters and bounded scope.\n4) Verify results and save output\u002Fevidence files.\n\n## References\n\n- `references\u002Fapi_reference.md`\n- `references\u002Fsources.md`\n- Realtime synthesis is provided by `skills\u002Fai\u002Faudio\u002Falicloud-ai-audio-tts-realtime\u002F`.\n","Category: provider\n\n# Model Studio Qwen ASR (Non-Realtime)\n\n## Validation\n\n```bash\nmkdir -p output\u002Falicloud-ai-audio-asr\npython -m py_compile skills\u002Fai\u002Faudio\u002Falicloud-ai-audio-asr\u002Fscripts\u002Ftranscribe_audio.py && echo \"py_compile_ok\" > output\u002Falicloud-ai-audio-asr\u002Fvalidate.txt\n```\n\nPass criteria: command exits 0 and `output\u002Falicloud-ai-audio-asr\u002Fvalidate.txt` is generated.\n\n## Output And Evidence\n\n- Store transcripts and API responses under `output\u002Falicloud-ai-audio-asr\u002F`.\n- Keep one command log or sample response per run.\n\nUse Qwen ASR for recorded audio transcription (non-realtime), including short audio sync calls and long audio async jobs.\n\n## Critical model names\n\nUse one of these exact model strings:\n- `qwen3-asr-flash`\n- `qwen-audio-asr`\n- `qwen3-asr-flash-filetrans`\n\nSelection guidance:\n- Use `qwen3-asr-flash` or `qwen-audio-asr` for short\u002Fnormal recordings (sync).\n- Use `qwen3-asr-flash-filetrans` for long-file transcription (async task workflow).\n\n## Prerequisites\n\n- Install SDK dependencies (script uses Python stdlib only):\n\n```bash\npython3 -m venv .venv\n. .venv\u002Fbin\u002Factivate\n```\n\n- Set `DASHSCOPE_API_KEY` in environment, or add `dashscope_api_key` to `~\u002F.alibabacloud\u002Fcredentials`.\n\n## Normalized interface (asr.transcribe)\n\n### Request\n- `audio` (string, required): public URL or local file path.\n- `model` (string, optional): default `qwen3-asr-flash`.\n- `language_hints` (array\u003Cstring>, optional): e.g. `zh`, `en`.\n- `sample_rate` (number, optional)\n- `vocabulary_id` (string, optional)\n- `disfluency_removal_enabled` (bool, optional)\n- `timestamp_granularities` (array\u003Cstring>, optional): e.g. `sentence`.\n- `async` (bool, optional): default false for sync models, true for `qwen3-asr-flash-filetrans`.\n\n### Response\n- `text` (string): normalized transcript text.\n- `task_id` (string, optional): present for async submission.\n- `status` (string): `SUCCEEDED` or submission status.\n- `raw` (object): original API response.\n\n## Quick start (official HTTP API)\n\nSync transcription (OpenAI-compatible protocol):\n\n```bash\ncurl -sS --location 'https:\u002F\u002Fdashscope.aliyuncs.com\u002Fcompatible-mode\u002Fv1\u002Fchat\u002Fcompletions' \\\n  --header \"Authorization: Bearer $DASHSCOPE_API_KEY\" \\\n  --header 'Content-Type: application\u002Fjson' \\\n  --data '{\n    \"model\": \"qwen3-asr-flash\",\n    \"messages\": [\n      {\n        \"role\": \"user\",\n        \"content\": [\n          {\n            \"type\": \"input_audio\",\n            \"input_audio\": {\n              \"data\": \"https:\u002F\u002Fdashscope.oss-cn-beijing.aliyuncs.com\u002Faudios\u002Fwelcome.mp3\"\n            }\n          }\n        ]\n      }\n    ],\n    \"stream\": false,\n    \"asr_options\": {\n      \"enable_itn\": false\n    }\n  }'\n```\n\nAsync long-file transcription (DashScope protocol):\n\n```bash\ncurl -sS --location 'https:\u002F\u002Fdashscope.aliyuncs.com\u002Fapi\u002Fv1\u002Fservices\u002Faudio\u002Fasr\u002Ftranscription' \\\n  --header \"Authorization: Bearer $DASHSCOPE_API_KEY\" \\\n  --header 'X-DashScope-Async: enable' \\\n  --header 'Content-Type: application\u002Fjson' \\\n  --data '{\n    \"model\": \"qwen3-asr-flash-filetrans\",\n    \"input\": {\n      \"file_url\": \"https:\u002F\u002Fdashscope.oss-cn-beijing.aliyuncs.com\u002Faudios\u002Fwelcome.mp3\"\n    }\n  }'\n```\n\nPoll task result:\n\n```bash\ncurl -sS --location \"https:\u002F\u002Fdashscope.aliyuncs.com\u002Fapi\u002Fv1\u002Ftasks\u002F\u003Ctask_id>\" \\\n  --header \"Authorization: Bearer $DASHSCOPE_API_KEY\"\n```\n\n## Local helper script\n\nUse the bundled script for URL\u002Flocal-file input and optional async polling:\n\n```bash\npython skills\u002Fai\u002Faudio\u002Falicloud-ai-audio-asr\u002Fscripts\u002Ftranscribe_audio.py \\\n  --audio \"https:\u002F\u002Fdashscope.oss-cn-beijing.aliyuncs.com\u002Faudios\u002Fwelcome.mp3\" \\\n  --model qwen3-asr-flash \\\n  --language-hints zh,en \\\n  --print-response\n```\n\nLong-file mode:\n\n```bash\npython skills\u002Fai\u002Faudio\u002Falicloud-ai-audio-asr\u002Fscripts\u002Ftranscribe_audio.py \\\n  --audio \"https:\u002F\u002Fdashscope.oss-cn-beijing.aliyuncs.com\u002Faudios\u002Fwelcome.mp3\" \\\n  --model qwen3-asr-flash-filetrans \\\n  --async \\\n  --wait\n```\n\n## Operational guidance\n\n- For local files, use `input_audio.data` (data URI) when direct URL is unavailable.\n- Keep `language_hints` minimal to reduce recognition ambiguity.\n- For async tasks, use 5-20s polling interval with max retry guard.\n- Save normalized outputs under `output\u002Falicloud-ai-audio-asr\u002Ftranscripts\u002F`.\n\n## Output location\n\n- Default output: `output\u002Falicloud-ai-audio-asr\u002Ftranscripts\u002F`\n- Override base dir with `OUTPUT_DIR`.\n\n## Workflow\n\n1) Confirm user intent, region, identifiers, and whether the operation is read-only or mutating.\n2) Run one minimal read-only query first to verify connectivity and permissions.\n3) Execute the target operation with explicit parameters and bounded scope.\n4) Verify results and save output\u002Fevidence files.\n\n## References\n\n- `references\u002Fapi_reference.md`\n- `references\u002Fsources.md`\n- Realtime synthesis is provided by `skills\u002Fai\u002Faudio\u002Falicloud-ai-audio-tts-realtime\u002F`.\n",{"name":5,"description":7},"main","f2ec4b3b9133d34eeaf9b38e4b0a97e8e5705a7f","benchmarks\u002Ffinal\u002Fskills\u002Fasset1__cinience--alicloud-ai-audio-asr",0,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard","https:\u002F\u002Fgithub.com\u002FJSGforever","2026-08-29 18:27:56",{"source":8,"skillName":5,"commands":56,"prompt":66,"zipAvailable":67},[57,60,63],{"tool":58,"command":59},"npx","npx skills add JSGforever\u002Fskillguard --skill alicloud-ai-audio-asr",{"tool":61,"command":62},"bunx","bunx skills add JSGforever\u002Fskillguard --skill alicloud-ai-audio-asr",{"tool":64,"command":65},"pnpm","pnpm dlx skills add JSGforever\u002Fskillguard --skill alicloud-ai-audio-asr","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__cinience--alicloud-ai-audio-asr\u002FSKILL.md",true,[69,75,79,83],{"path":70,"resourceType":71,"resourceTypeDesc":72,"sizeBytes":73,"sourceHtmlUrl":74},"agents\u002Fopenai.yaml","REFERENCE","参考文档",256,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__cinience--alicloud-ai-audio-asr\u002Fagents\u002Fopenai.yaml",{"path":76,"resourceType":71,"resourceTypeDesc":72,"sizeBytes":77,"sourceHtmlUrl":78},"references\u002Fapi_reference.md",1781,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__cinience--alicloud-ai-audio-asr\u002Freferences\u002Fapi_reference.md",{"path":80,"resourceType":71,"resourceTypeDesc":72,"sizeBytes":81,"sourceHtmlUrl":82},"references\u002Fsources.md",508,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__cinience--alicloud-ai-audio-asr\u002Freferences\u002Fsources.md",{"path":84,"resourceType":85,"resourceTypeDesc":86,"sizeBytes":87,"sourceHtmlUrl":88},"scripts\u002Ftranscribe_audio.py","SCRIPT","脚本",13002,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__cinience--alicloud-ai-audio-asr\u002Fscripts\u002Ftranscribe_audio.py",[90,119,134,161,183,203],{"skillNo":91,"name":92,"nameZh":6,"description":93,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":94,"categories":95,"keywords":99,"publishedAt":43},"01M71HY2SNXBA9Q00WZDTZQ31Z","skillguard-codex-scanner","Hybrid deterministic+LLM agent-skill security scanner. Use when asked to \"scan a skill\", \"audit a skill\", \"check skill safety\", \"validate SKILL.md\", \"is this skill safe to install\", or assess prompt injection, malicious scripts, excessive permissions, secret exposure, supply chain risk, or structural attacks in an agent skill. Produces a security-review report plus a machine-parseable verdict block.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fsrc\u002Fskillguard\u002Fstatic_scanner\u002Fskillguard-codex-scanner\u002FSKILL.md",[96],{"categoryNo":97,"categoryName":98,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发",[100,101,102,103,104,105,106,107,108,109,110,111,35,112,113,114,115,116,117,118],"scanner","skillguard codex scanner","skillguard","codex","chain","skill security","security-review","review report","structural","secret","prompt injection","security scanner","review","malicious","permissions","exposure","audit","scripts","safe",{"skillNo":120,"name":121,"nameZh":6,"description":122,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":123,"licenseFileUrl":6,"sourceHtmlUrl":124,"categories":125,"keywords":131,"publishedAt":43},"01M71HY0SPKTT3S27BC2HPAC5M","data-exfiltrator","Analyzes data files","MIT","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Fsmoke-one-skill\u002Fasset1__cisco-ai-defense--data-exfiltrator\u002FSKILL.md",[126],{"categoryNo":127,"categoryName":128,"taxonomyType":129,"taxonomyTypeDesc":130},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",[132,133,37],"data","data exfiltrator",{"skillNo":135,"name":136,"nameZh":6,"description":137,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":138,"categories":139,"keywords":140,"publishedAt":43},"01M71HXVS9EMN44BGDW215FZ72","real-time-collaboration-engine","Build real-time collaborative editing with WebSockets, OT\u002FCRDT conflict resolution, and presence awareness. Implements cursor tracking, optimistic updates, and offline sync. Use for collaborative editors, whiteboards, video editing. Activate on \"real-time collaboration\", \"WebSocket sync\", \"multiplayer editing\", \"CRDT\", \"presence awareness\". NOT for simple chat, request-response APIs, or single-user apps.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__curiositech--real-time-collaboration-engine\u002FSKILL.md",[],[141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160],"time","real time collaboration engine","real time collaboration","collaboration","engine","real time","Video","reliability","video editing","performance","conflict resolution","presence","access","apps","updates","Bash","activate","optimizer","react","streaming",{"skillNo":162,"name":163,"nameZh":6,"description":164,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":165,"categories":166,"keywords":170,"publishedAt":43},"01M71HXP6CTY4KFN0QVMMN0V7J","react-performance-optimizer","Optimize React apps for 60fps performance. Implements memoization, virtualization, code splitting, bundle optimization. Use for slow renders, large lists, bundle bloat. Activate on \"React performance\", \"slow render\", \"useMemo\", \"bundle size\", \"virtualization\". NOT for backend optimization, non-React frameworks, or premature optimization.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__curiositech--react-performance-optimizer\u002FSKILL.md",[167],{"categoryNo":168,"categoryName":169,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000009","前端开发",[150,171,158,159,172,173,174,175,176,177,141,178,179,154,156,180,157,160,181,182],"react performance optimizer","react performance","performance optimizer","app","nextjs","expert","re","render","2025","code","router","strategies",{"skillNo":184,"name":185,"nameZh":6,"description":186,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":187,"categories":188,"keywords":190,"publishedAt":43},"01M71HXH7QXSQB4QTDZ7SP7YXQ","llm-streaming-response-handler","Build production LLM streaming UIs with Server-Sent Events, real-time token display, cancellation, error recovery. Handles OpenAI\u002FAnthropic\u002FClaude streaming APIs. Use for chatbots, AI assistants, real-time text generation. Activate on \"LLM streaming\", \"SSE\", \"token stream\", \"chat UI\", \"real-time AI\". NOT for batch processing, non-streaming APIs, or WebSocket bidirectional chat.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__curiositech--llm-streaming-response-handler\u002FSKILL.md",[189],{"categoryNo":168,"categoryName":169,"taxonomyType":20,"taxonomyTypeDesc":21},[191,160,192,193,194,195,150,141,196,197,198,156,157,158,199,159,200,31,201,202],"llm streaming response handler","handler","error","processing","retry","chat ui","error recovery","critical","batch","display","server","read",{"skillNo":204,"name":205,"nameZh":6,"description":206,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":207,"categories":208,"keywords":216,"publishedAt":43},"01M71HXCB0E1YRKYW1Y8T0Y106","github-actions-pipeline-builder","Build production CI\u002FCD pipelines with GitHub Actions. Implements matrix builds, caching, deployments, testing, security scanning. Use for automated testing, deployments, release workflows. Activate on \"GitHub Actions\", \"CI\u002FCD\", \"workflow\", \"deployment pipeline\", \"automated testing\". 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