[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6DF0Y4BMP22646A2DAYEAE4":3,"skill-same:01M6DF0Y4BMP22646A2DAYEAE4":92},{"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":23,"publishedAt":35,"linkOnly":36,"markdownContent":37,"markdownBody":38,"frontMatter":39,"refName":40,"commitSha":41,"skillDirectory":42,"forksCount":14,"repositoryHtmlUrl":43,"repositoryHomepageUrl":6,"ownerHtmlUrl":44,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":45,"install":46,"resources":59},"01M6DF0Y4BMP22646A2DAYEAE4","transcribe",null,"Use when asked to transcribe speech to text from audio\u002Fvideo, with diarization to label speakers in recordings, interviews or meetings. Do NOT use for WORD-LEVEL caption or karaoke timing -- use reframe-transcribe.","Prekzursil\u002Fagent-skills-toolchain","Prekzursil","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F54636077?v=4","01M6DACZ1PCQHD99SCR1YXG28B","Andrei Mihai Visalon","01M6DACZ670WZF535V3WYYSS4Z",0,"MIT","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Fskills\u002Ftranscribe\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000016","图像与多媒体","SCENARIO","使用场景",[5,24,25,26,27,28,29,30,31,32,33,34],"speech","Video","Audio","Word","text","speech to text","meetings","use","recordings","do","reframe","2026-11-10 10:12:30",false,"---\nname: \"transcribe\"\ndescription: \"Use when asked to transcribe speech to text from audio\u002Fvideo, with diarization to label speakers in recordings, interviews or meetings. Do NOT use for WORD-LEVEL caption or karaoke timing -- use reframe-transcribe.\"\n---\n\n\n# Audio Transcribe\n\nTranscribe audio using OpenAI, with optional speaker diarization when requested. Prefer the bundled CLI for deterministic, repeatable runs.\n\n## Workflow\n1. Collect inputs: audio file path(s), desired response format (text\u002Fjson\u002Fdiarized_json), optional language hint, and any known speaker references.\n2. Verify `OPENAI_API_KEY` is set. If missing, ask the user to set it locally (do not ask them to paste the key).\n3. Run the bundled `transcribe_diarize.py` CLI with sensible defaults (fast text transcription).\n4. Validate the output: transcription quality, speaker labels, and segment boundaries; iterate with a single targeted change if needed.\n5. Save outputs under `output\u002Ftranscribe\u002F` when working in this repo.\n\n## Decision rules\n- Default to `gpt-4o-mini-transcribe` with `--response-format text` for fast transcription.\n- If the user wants speaker labels or diarization, use `--model gpt-4o-transcribe-diarize --response-format diarized_json`.\n- If audio is longer than ~30 seconds, keep `--chunking-strategy auto`.\n- Prompting is not supported for `gpt-4o-transcribe-diarize`.\n\n## Output conventions\n- Use `output\u002Ftranscribe\u002F\u003Cjob-id>\u002F` for evaluation runs.\n- Use `--out-dir` for multiple files to avoid overwriting.\n\n## Dependencies (install if missing)\nPrefer `uv` for dependency management.\n\n```\nuv pip install openai\n```\nIf `uv` is unavailable:\n```\npython3 -m pip install openai\n```\n\n## Environment\n- `OPENAI_API_KEY` must be set for live API calls.\n- If the key is missing, instruct the user to create one in the OpenAI platform UI and export it in their shell.\n- Never ask the user to paste the full key in chat.\n\n## Skill path (set once)\n\n```bash\nexport CODEX_HOME=\"${CODEX_HOME:-$HOME\u002F.codex}\"\nexport TRANSCRIBE_CLI=\"$CODEX_HOME\u002Fskills\u002Ftranscribe\u002Fscripts\u002Ftranscribe_diarize.py\"\n```\n\nUser-scoped skills install under `$CODEX_HOME\u002Fskills` (default: `~\u002F.codex\u002Fskills`).\n\n## CLI quick start\nSingle file (fast text default):\n```\npython3 \"$TRANSCRIBE_CLI\" \\\n  path\u002Fto\u002Faudio.wav \\\n  --out transcript.txt\n```\n\nDiarization with known speakers (up to 4):\n```\npython3 \"$TRANSCRIBE_CLI\" \\\n  meeting.m4a \\\n  --model gpt-4o-transcribe-diarize \\\n  --known-speaker \"Alice=refs\u002Falice.wav\" \\\n  --known-speaker \"Bob=refs\u002Fbob.wav\" \\\n  --response-format diarized_json \\\n  --out-dir output\u002Ftranscribe\u002Fmeeting\n```\n\nPlain text output (explicit):\n```\npython3 \"$TRANSCRIBE_CLI\" \\\n  interview.mp3 \\\n  --response-format text \\\n  --out interview.txt\n```\n\n## Reference map\n- `references\u002Fapi.md`: supported formats, limits, response formats, and known-speaker notes.\n","# Audio Transcribe\n\nTranscribe audio using OpenAI, with optional speaker diarization when requested. Prefer the bundled CLI for deterministic, repeatable runs.\n\n## Workflow\n1. Collect inputs: audio file path(s), desired response format (text\u002Fjson\u002Fdiarized_json), optional language hint, and any known speaker references.\n2. Verify `OPENAI_API_KEY` is set. If missing, ask the user to set it locally (do not ask them to paste the key).\n3. Run the bundled `transcribe_diarize.py` CLI with sensible defaults (fast text transcription).\n4. Validate the output: transcription quality, speaker labels, and segment boundaries; iterate with a single targeted change if needed.\n5. Save outputs under `output\u002Ftranscribe\u002F` when working in this repo.\n\n## Decision rules\n- Default to `gpt-4o-mini-transcribe` with `--response-format text` for fast transcription.\n- If the user wants speaker labels or diarization, use `--model gpt-4o-transcribe-diarize --response-format diarized_json`.\n- If audio is longer than ~30 seconds, keep `--chunking-strategy auto`.\n- Prompting is not supported for `gpt-4o-transcribe-diarize`.\n\n## Output conventions\n- Use `output\u002Ftranscribe\u002F\u003Cjob-id>\u002F` for evaluation runs.\n- Use `--out-dir` for multiple files to avoid overwriting.\n\n## Dependencies (install if missing)\nPrefer `uv` for dependency management.\n\n```\nuv pip install openai\n```\nIf `uv` is unavailable:\n```\npython3 -m pip install openai\n```\n\n## Environment\n- `OPENAI_API_KEY` must be set for live API calls.\n- If the key is missing, instruct the user to create one in the OpenAI platform UI and export it in their shell.\n- Never ask the user to paste the full key in chat.\n\n## Skill path (set once)\n\n```bash\nexport CODEX_HOME=\"${CODEX_HOME:-$HOME\u002F.codex}\"\nexport TRANSCRIBE_CLI=\"$CODEX_HOME\u002Fskills\u002Ftranscribe\u002Fscripts\u002Ftranscribe_diarize.py\"\n```\n\nUser-scoped skills install under `$CODEX_HOME\u002Fskills` (default: `~\u002F.codex\u002Fskills`).\n\n## CLI quick start\nSingle file (fast text default):\n```\npython3 \"$TRANSCRIBE_CLI\" \\\n  path\u002Fto\u002Faudio.wav \\\n  --out transcript.txt\n```\n\nDiarization with known speakers (up to 4):\n```\npython3 \"$TRANSCRIBE_CLI\" \\\n  meeting.m4a \\\n  --model gpt-4o-transcribe-diarize \\\n  --known-speaker \"Alice=refs\u002Falice.wav\" \\\n  --known-speaker \"Bob=refs\u002Fbob.wav\" \\\n  --response-format diarized_json \\\n  --out-dir output\u002Ftranscribe\u002Fmeeting\n```\n\nPlain text output (explicit):\n```\npython3 \"$TRANSCRIBE_CLI\" \\\n  interview.mp3 \\\n  --response-format text \\\n  --out interview.txt\n```\n\n## Reference map\n- `references\u002Fapi.md`: supported formats, limits, response formats, and known-speaker notes.\n",{"name":5,"description":7},"main","a298c929b6cbd662e1fce54302ce520d5ceea1a5","skills\u002Ftranscribe","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain","https:\u002F\u002Fgithub.com\u002FPrekzursil","2026-11-02 14:30:57",{"source":8,"skillName":5,"commands":47,"prompt":57,"zipAvailable":58},[48,51,54],{"tool":49,"command":50},"npx","npx skills add Prekzursil\u002Fagent-skills-toolchain --skill transcribe",{"tool":52,"command":53},"bunx","bunx skills add Prekzursil\u002Fagent-skills-toolchain --skill transcribe",{"tool":55,"command":56},"pnpm","pnpm dlx skills add Prekzursil\u002Fagent-skills-toolchain --skill transcribe","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Fskills\u002Ftranscribe\u002FSKILL.md",true,[60,66,72,76,82,86],{"path":61,"resourceType":62,"resourceTypeDesc":63,"sizeBytes":64,"sourceHtmlUrl":65},"agents\u002Fopenai.yaml","REFERENCE","参考文档",414,"https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Fskills\u002Ftranscribe\u002Fagents\u002Fopenai.yaml",{"path":67,"resourceType":68,"resourceTypeDesc":69,"sizeBytes":70,"sourceHtmlUrl":71},"assets\u002Ftranscribe-small.svg","ASSET","资产文件",750,"https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Fskills\u002Ftranscribe\u002Fassets\u002Ftranscribe-small.svg",{"path":73,"resourceType":68,"resourceTypeDesc":69,"sizeBytes":74,"sourceHtmlUrl":75},"assets\u002Ftranscribe.png",1288,"https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Fskills\u002Ftranscribe\u002Fassets\u002Ftranscribe.png",{"path":77,"resourceType":78,"resourceTypeDesc":79,"sizeBytes":80,"sourceHtmlUrl":81},"LICENSE.txt","LICENSE","许可证",10776,"https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Fskills\u002Ftranscribe\u002FLICENSE.txt",{"path":83,"resourceType":62,"resourceTypeDesc":63,"sizeBytes":84,"sourceHtmlUrl":85},"references\u002Fapi.md",457,"https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Fskills\u002Ftranscribe\u002Freferences\u002Fapi.md",{"path":87,"resourceType":88,"resourceTypeDesc":89,"sizeBytes":90,"sourceHtmlUrl":91},"scripts\u002Ftranscribe_diarize.py","SCRIPT","脚本",8730,"https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Fskills\u002Ftranscribe\u002Fscripts\u002Ftranscribe_diarize.py",[93,114,142,169,183,199],{"skillNo":94,"name":95,"nameZh":6,"description":96,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":97,"categories":98,"keywords":99,"publishedAt":35},"01M6DF7D7478R55P46REYH4QAC","clarify-requirements","Resolve genuine pre-execution ambiguity by scanning repo context, generating 1-6 grounded options, and asking 1-3 focused questions via AskUserQuestion. NOT for mid-task use (injection risk); NOT when the goal is already unambiguous; use to disambiguate vague prompts before any file edits.","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Ftools\u002Fworkspace-hooks\u002Fskills\u002Fclarify-requirements\u002FSKILL.md",[],[100,101,102,103,104,105,106,107,108,31,109,110,111,112,113],"clarify requirements","clarify","requirements","risk","options","task","prompts","goal","scanning","context","repo","injection","execution","file",{"skillNo":115,"name":116,"nameZh":6,"description":117,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":118,"categories":119,"keywords":123,"publishedAt":35},"01M6DF79CA4BHJS66J8EZDBPWJ","openmm-md","Run FREE, open-source, Windows-native GPU molecular dynamics via the openmm-md MCP (OpenMM + CUDA on the local NVIDIA GPU). Use for protein \u002F protein-ligand MD when you want a free stack or are on Windows without a Schrodinger license. Covers the full workflow (prepare, solvate, minimize, equilibrate, production, analyze, mmgbsa) AND an honest decision guide vs Schrodinger Desmond, including how to run Desmond legitimately on Linux or a cloud GPU with a real license. This is a deliberately LESSER free alternative and does NOT replace the schrodinger MCP tools. Do NOT use it to pick a free tool when a validated FEP+, WaterMap, IFD-MD, or Prime MM-GBSA result is actually required.","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Ftools\u002Fmcp\u002Fopenmm-md-mcp\u002Fskill\u002Fopenmm-md\u002FSKILL.md",[120],{"categoryNo":121,"categoryName":122,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",[124,125,126,127,128,129,130,131,132,133,134,135,136,137,31,138,139,140,33,141],"openmm md","how","decision","pick","linux","analyze","tool","stack","open","NVIDIA","gpu","license","workflow","windows","free","molecular dynamics","local","MCP",{"skillNo":143,"name":144,"nameZh":6,"description":145,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":146,"categories":147,"keywords":154,"publishedAt":35},"01M6DF76C1MG85VEWP8VZCBNMN","visual-review","Take screenshots of web pages and UI using Playwright for visual review and iteration","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Ftools\u002Feditor\u002Fmetaswarm\u002Fskills\u002Fvisual-review\u002FSKILL.md",[148,151],{"categoryNo":149,"categoryName":150,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000003","演示文稿",{"categoryNo":152,"categoryName":153,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量",[155,156,157,158,159,160,161,162,163,164,125,165,166,167,168],"review","visual","visual review","pages","web","false","iteration","take","check","slides","ui","screenshot","playwright","screenshots",{"skillNo":170,"name":171,"nameZh":6,"description":172,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":173,"categories":174,"keywords":175,"publishedAt":35},"01M6DF73AQVCBZKEN0YXEX9FXP","status","Diagnostic status report — shows metaswarm installation state, project setup, and potential issues","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Ftools\u002Feditor\u002Fmetaswarm\u002Fskills\u002Fstatus\u002FSKILL.md",[],[171,176,177,178,179,180,181,182],"setup","report","project","installation","project setup","issues","state",{"skillNo":184,"name":185,"nameZh":6,"description":186,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":187,"categories":188,"keywords":190,"publishedAt":35},"01M6DF6X6C2XB0P6GX76P7TTYV","start","Use when starting work on any task, when the user mentions metaswarm, or when the user wants to begin tracked development work","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Ftools\u002Feditor\u002Fmetaswarm\u002Fskills\u002Fstart\u002FSKILL.md",[189],{"categoryNo":121,"categoryName":122,"taxonomyType":21,"taxonomyTypeDesc":22},[185,191,105,192,193,194,31,195,196,197,198],"start issue","issue","ready","work on issue","user","work","work on","development",{"skillNo":200,"name":176,"nameZh":6,"description":201,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":202,"categories":203,"keywords":204,"publishedAt":35},"01M6DF6QMJ9AJKFKHHKRT005PQ","Interactive project setup — detects your project, configures metaswarm, writes project-local files","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002Ftools\u002Feditor\u002Fmetaswarm\u002Fskills\u002Fsetup\u002FSKILL.md",[],[176,178,140,205,180,206],"files","interactive"]