[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6CPSFQV0WGNESS0P6XZ0D7P":3,"skill-same:01M6CPSFQV0WGNESS0P6XZ0D7P":72},{"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":39,"linkOnly":40,"markdownContent":41,"markdownBody":42,"frontMatter":43,"refName":35,"commitSha":50,"skillDirectory":51,"forksCount":52,"repositoryHtmlUrl":53,"repositoryHomepageUrl":6,"ownerHtmlUrl":54,"ownerBlogUrl":55,"ownerDescription":56,"updatedAt":57,"install":58,"resources":71},"01M6CPSFQV0WGNESS0P6XZ0D7P","openai-jupyter-notebook",null,"Use when the user asks to create, scaffold, or edit Jupyter notebooks (`.ipynb`) for experiments, explorations, or tutorials; prefer the bundled templates and run the helper script `new_notebook.py` to generate a clean starting notebook. (Imported from openai upstream skills)","khalidsaidi\u002Fskillrunner","khalidsaidi","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F4368721?v=4","01M6CPK1G2TKAWA8BSNSANBNWJ","Khalid Saidi","01M6CPK1M7RGKV85142PWBEJ54",1,"MIT","https:\u002F\u002Fgithub.com\u002Fkhalidsaidi\u002Fskillrunner\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fopenai-jupyter-notebook\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"jupyter notebook","openai jupyter notebook","notebook","jupyter","openai","run","generate","jupyter notebooks","https","templates","knowledge","edit","create","use","clean","experiments","main","upstream","imported","github","2026-11-10 10:12:30",false,"---\nname: openai-jupyter-notebook\ndescription: \"Use when the user asks to create, scaffold, or edit Jupyter notebooks (`.ipynb`) for experiments, explorations, or tutorials; prefer the bundled templates and run the helper script `new_notebook.py` to generate a clean starting notebook. (Imported from openai upstream skills)\"\nversion: \"1.0.0\"\ntags: [\"openai\", \"upstream\", \"imported\"]\nkind: knowledge\nrisk: low\navailability: advanced\ndocs:\n  source: \"https:\u002F\u002Fgithub.com\u002Fopenai\u002Fskills\u002Ftree\u002Fmain\u002Fskills\u002F.curated\u002Fjupyter-notebook\"\n---\n\n# openai-jupyter-notebook\n\nImported upstream skill.\n\n- Provider source: https:\u002F\u002Fgithub.com\u002Fopenai\u002Fskills\u002Ftree\u002Fmain\u002Fskills\u002F.curated\u002Fjupyter-notebook\n- Original skill name: jupyter-notebook\n\n## Upstream Content\n\n# Jupyter Notebook Skill\n\nCreate clean, reproducible Jupyter notebooks for two primary modes:\n\n- Experiments and exploratory analysis\n- Tutorials and teaching-oriented walkthroughs\n\nPrefer the bundled templates and the helper script for consistent structure and fewer JSON mistakes.\n\n## When to use\n- Create a new `.ipynb` notebook from scratch.\n- Convert rough notes or scripts into a structured notebook.\n- Refactor an existing notebook to be more reproducible and skimmable.\n- Build experiments or tutorials that will be read or re-run by other people.\n\n## Decision tree\n- If the request is exploratory, analytical, or hypothesis-driven, choose `experiment`.\n- If the request is instructional, step-by-step, or audience-specific, choose `tutorial`.\n- If editing an existing notebook, treat it as a refactor: preserve intent and improve structure.\n\n## Skill path (set once)\n\n```bash\nexport CODEX_HOME=\"${CODEX_HOME:-$HOME\u002F.codex}\"\nexport JUPYTER_NOTEBOOK_CLI=\"$CODEX_HOME\u002Fskills\u002Fjupyter-notebook\u002Fscripts\u002Fnew_notebook.py\"\n```\n\nUser-scoped skills install under `$CODEX_HOME\u002Fskills` (default: `~\u002F.codex\u002Fskills`).\n\n## Workflow\n1. Lock the intent.\nIdentify the notebook kind: `experiment` or `tutorial`.\nCapture the objective, audience, and what \"done\" looks like.\n\n2. Scaffold from the template.\nUse the helper script to avoid hand-authoring raw notebook JSON.\n\n```bash\nuv run --python 3.12 python \"$JUPYTER_NOTEBOOK_CLI\" \\\n  --kind experiment \\\n  --title \"Compare prompt variants\" \\\n  --out output\u002Fjupyter-notebook\u002Fcompare-prompt-variants.ipynb\n```\n\n```bash\nuv run --python 3.12 python \"$JUPYTER_NOTEBOOK_CLI\" \\\n  --kind tutorial \\\n  --title \"Intro to embeddings\" \\\n  --out output\u002Fjupyter-notebook\u002Fintro-to-embeddings.ipynb\n```\n\n3. Fill the notebook with small, runnable steps.\nKeep each code cell focused on one step.\nAdd short markdown cells that explain the purpose and expected result.\nAvoid large, noisy outputs when a short summary works.\n\n4. Apply the right pattern.\nFor experiments, follow `references\u002Fexperiment-patterns.md`.\nFor tutorials, follow `references\u002Ftutorial-patterns.md`.\n\n5. Edit safely when working with existing notebooks.\nPreserve the notebook structure; avoid reordering cells unless it improves the top-to-bottom story.\nPrefer targeted edits over full rewrites.\nIf you must edit raw JSON, review `references\u002Fnotebook-structure.md` first.\n\n6. Validate the result.\nRun the notebook top-to-bottom when the environment allows.\nIf execution is not possible, say so explicitly and call out how to validate locally.\nUse the final pass checklist in `references\u002Fquality-checklist.md`.\n\n## Templates and helper script\n- Templates live in `assets\u002Fexperiment-template.ipynb` and `assets\u002Ftutorial-template.ipynb`.\n- The helper script loads a template, updates the title cell, and writes a notebook.\n\nScript path:\n- `$JUPYTER_NOTEBOOK_CLI` (installed default: `$CODEX_HOME\u002Fskills\u002Fjupyter-notebook\u002Fscripts\u002Fnew_notebook.py`)\n\n## Temp and output conventions\n- Use `tmp\u002Fjupyter-notebook\u002F` for intermediate files; delete when done.\n- Write final artifacts under `output\u002Fjupyter-notebook\u002F` when working in this repo.\n- Use stable, descriptive filenames (for example, `ablation-temperature.ipynb`).\n\n## Dependencies (install only when needed)\nPrefer `uv` for dependency management.\n\nOptional Python packages for local notebook execution:\n\n```bash\nuv pip install jupyterlab ipykernel\n```\n\nThe bundled scaffold script uses only the Python standard library and does not require extra dependencies.\n\n## Environment\nNo required environment variables.\n\n## Reference map\n- `references\u002Fexperiment-patterns.md`: experiment structure and heuristics.\n- `references\u002Ftutorial-patterns.md`: tutorial structure and teaching flow.\n- `references\u002Fnotebook-structure.md`: notebook JSON shape and safe editing rules.\n- `references\u002Fquality-checklist.md`: final validation checklist.\n","# openai-jupyter-notebook\n\nImported upstream skill.\n\n- Provider source: https:\u002F\u002Fgithub.com\u002Fopenai\u002Fskills\u002Ftree\u002Fmain\u002Fskills\u002F.curated\u002Fjupyter-notebook\n- Original skill name: jupyter-notebook\n\n## Upstream Content\n\n# Jupyter Notebook Skill\n\nCreate clean, reproducible Jupyter notebooks for two primary modes:\n\n- Experiments and exploratory analysis\n- Tutorials and teaching-oriented walkthroughs\n\nPrefer the bundled templates and the helper script for consistent structure and fewer JSON mistakes.\n\n## When to use\n- Create a new `.ipynb` notebook from scratch.\n- Convert rough notes or scripts into a structured notebook.\n- Refactor an existing notebook to be more reproducible and skimmable.\n- Build experiments or tutorials that will be read or re-run by other people.\n\n## Decision tree\n- If the request is exploratory, analytical, or hypothesis-driven, choose `experiment`.\n- If the request is instructional, step-by-step, or audience-specific, choose `tutorial`.\n- If editing an existing notebook, treat it as a refactor: preserve intent and improve structure.\n\n## Skill path (set once)\n\n```bash\nexport CODEX_HOME=\"${CODEX_HOME:-$HOME\u002F.codex}\"\nexport JUPYTER_NOTEBOOK_CLI=\"$CODEX_HOME\u002Fskills\u002Fjupyter-notebook\u002Fscripts\u002Fnew_notebook.py\"\n```\n\nUser-scoped skills install under `$CODEX_HOME\u002Fskills` (default: `~\u002F.codex\u002Fskills`).\n\n## Workflow\n1. Lock the intent.\nIdentify the notebook kind: `experiment` or `tutorial`.\nCapture the objective, audience, and what \"done\" looks like.\n\n2. Scaffold from the template.\nUse the helper script to avoid hand-authoring raw notebook JSON.\n\n```bash\nuv run --python 3.12 python \"$JUPYTER_NOTEBOOK_CLI\" \\\n  --kind experiment \\\n  --title \"Compare prompt variants\" \\\n  --out output\u002Fjupyter-notebook\u002Fcompare-prompt-variants.ipynb\n```\n\n```bash\nuv run --python 3.12 python \"$JUPYTER_NOTEBOOK_CLI\" \\\n  --kind tutorial \\\n  --title \"Intro to embeddings\" \\\n  --out output\u002Fjupyter-notebook\u002Fintro-to-embeddings.ipynb\n```\n\n3. Fill the notebook with small, runnable steps.\nKeep each code cell focused on one step.\nAdd short markdown cells that explain the purpose and expected result.\nAvoid large, noisy outputs when a short summary works.\n\n4. Apply the right pattern.\nFor experiments, follow `references\u002Fexperiment-patterns.md`.\nFor tutorials, follow `references\u002Ftutorial-patterns.md`.\n\n5. Edit safely when working with existing notebooks.\nPreserve the notebook structure; avoid reordering cells unless it improves the top-to-bottom story.\nPrefer targeted edits over full rewrites.\nIf you must edit raw JSON, review `references\u002Fnotebook-structure.md` first.\n\n6. Validate the result.\nRun the notebook top-to-bottom when the environment allows.\nIf execution is not possible, say so explicitly and call out how to validate locally.\nUse the final pass checklist in `references\u002Fquality-checklist.md`.\n\n## Templates and helper script\n- Templates live in `assets\u002Fexperiment-template.ipynb` and `assets\u002Ftutorial-template.ipynb`.\n- The helper script loads a template, updates the title cell, and writes a notebook.\n\nScript path:\n- `$JUPYTER_NOTEBOOK_CLI` (installed default: `$CODEX_HOME\u002Fskills\u002Fjupyter-notebook\u002Fscripts\u002Fnew_notebook.py`)\n\n## Temp and output conventions\n- Use `tmp\u002Fjupyter-notebook\u002F` for intermediate files; delete when done.\n- Write final artifacts under `output\u002Fjupyter-notebook\u002F` when working in this repo.\n- Use stable, descriptive filenames (for example, `ablation-temperature.ipynb`).\n\n## Dependencies (install only when needed)\nPrefer `uv` for dependency management.\n\nOptional Python packages for local notebook execution:\n\n```bash\nuv pip install jupyterlab ipykernel\n```\n\nThe bundled scaffold script uses only the Python standard library and does not require extra dependencies.\n\n## Environment\nNo required environment variables.\n\n## Reference map\n- `references\u002Fexperiment-patterns.md`: experiment structure and heuristics.\n- `references\u002Ftutorial-patterns.md`: tutorial structure and teaching flow.\n- `references\u002Fnotebook-structure.md`: notebook JSON shape and safe editing rules.\n- `references\u002Fquality-checklist.md`: final validation checklist.\n",{"docs":44,"kind":29,"name":5,"risk":46,"tags":47,"version":48,"description":7,"availability":49},{"source":45},"https:\u002F\u002Fgithub.com\u002Fopenai\u002Fskills\u002Ftree\u002Fmain\u002Fskills\u002F.curated\u002Fjupyter-notebook","low",[23,36,37],"1.0.0","advanced","c4da92076cba308457cd72bd1ab06c087e2cdf96","registry\u002Fskills\u002Fopenai-jupyter-notebook",0,"https:\u002F\u002Fgithub.com\u002Fkhalidsaidi\u002Fskillrunner","https:\u002F\u002Fgithub.com\u002Fkhalidsaidi","https:\u002F\u002Fkhalidsaidi.com","Software engineer. Maintainer of SourceMint (SRCMNT), an open-source fixed-supply ERC-20 and Foundry tooling on Base.","2026-11-07 02:40:24",{"source":8,"skillName":5,"commands":59,"prompt":69,"zipAvailable":70},[60,63,66],{"tool":61,"command":62},"npx","npx skills add khalidsaidi\u002Fskillrunner --skill openai-jupyter-notebook",{"tool":64,"command":65},"bunx","bunx skills add khalidsaidi\u002Fskillrunner --skill openai-jupyter-notebook",{"tool":67,"command":68},"pnpm","pnpm dlx skills add khalidsaidi\u002Fskillrunner --skill openai-jupyter-notebook","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fkhalidsaidi\u002Fskillrunner\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fopenai-jupyter-notebook\u002FSKILL.md",true,[],[73,90,98,118,127,145],{"skillNo":74,"name":75,"nameZh":6,"description":76,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":77,"categories":78,"keywords":79,"publishedAt":39},"01M6CPY1N6W58XKWMN4356E8GF","yeet","Use only when the user explicitly asks to stage, commit, push, and open a GitHub pull request in one flow using the GitHub CLI (`gh`).","https:\u002F\u002Fgithub.com\u002Fkhalidsaidi\u002Fskillrunner\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fopenai-yeet\u002Fupstream\u002FSKILL.md",[],[75,80,81,32,82,83,84,85,86,87,88,89,38],"only","cli","user","gh","open","flow","push","pull","pull request","commit",{"skillNo":91,"name":92,"nameZh":6,"description":93,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":94,"categories":95,"keywords":96,"publishedAt":39},"01M6CPXZ5RN2ZB5A4Y65RE5Y5J","openai-yeet","Use only when the user explicitly asks to stage, commit, push, and open a GitHub pull request in one flow using the GitHub CLI (`gh`). (Imported from openai upstream skills)","https:\u002F\u002Fgithub.com\u002Fkhalidsaidi\u002Fskillrunner\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fopenai-yeet\u002FSKILL.md",[],[75,23,97,86,87,88,89,38,81,27,37,36,35,80,32,82,83,29,84,85],"openai yeet",{"skillNo":99,"name":100,"nameZh":6,"description":101,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":102,"categories":103,"keywords":109,"publishedAt":39},"01M6CPXWGRW59XN1V109G172CV","vercel-deploy","Deploy applications and websites to Vercel. Use when the user requests deployment actions like \"deploy my app\", \"deploy and give me the link\", \"push this live\", or \"create a preview deployment\".","https:\u002F\u002Fgithub.com\u002Fkhalidsaidi\u002Fskillrunner\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fopenai-vercel-deploy\u002Fupstream\u002FSKILL.md",[104],{"categoryNo":105,"categoryName":106,"taxonomyType":107,"taxonomyTypeDesc":108},"01JBSEEDCAT000000000000011","运维与部署","SCENARIO","使用场景",[110,111,112,86,32,113,114,115,116,82,117,31],"vercel","vercel deploy","deploy","actions","applications","me","preview deployment","deployment",{"skillNo":119,"name":120,"nameZh":6,"description":121,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":122,"categories":123,"keywords":125,"publishedAt":39},"01M6CPXSZSZRPQ5TY73K5QWN1B","openai-vercel-deploy","Deploy applications and websites to Vercel. Use when the user requests deployment actions like \"deploy my app\", \"deploy and give me the link\", \"push this live\", or \"create a preview deployment\". (Imported from openai upstream skills)","https:\u002F\u002Fgithub.com\u002Fkhalidsaidi\u002Fskillrunner\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fopenai-vercel-deploy\u002FSKILL.md",[124],{"categoryNo":105,"categoryName":106,"taxonomyType":107,"taxonomyTypeDesc":108},[112,23,111,110,126,113,37,36,115,35,116,32,82,29,114,27,86,31,117,38],"openai vercel deploy",{"skillNo":128,"name":129,"nameZh":6,"description":130,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":131,"categories":132,"keywords":136,"publishedAt":39},"01M6CPXQ4SRTZZZ0VTD7WZP0RN","transcribe","Transcribe audio files to text with optional diarization and known-speaker hints. Use when a user asks to transcribe speech from audio\u002Fvideo, extract text from recordings, or label speakers in interviews or meetings.","https:\u002F\u002Fgithub.com\u002Fkhalidsaidi\u002Fskillrunner\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fopenai-transcribe\u002Fupstream\u002FSKILL.md",[133],{"categoryNo":134,"categoryName":135,"taxonomyType":107,"taxonomyTypeDesc":108},"01JBSEEDCAT000000000000016","图像与多媒体",[129,82,137,138,139,140,141,142,143,32,144],"text","Audio","Video","speech","extract","files","recordings","meetings",{"skillNo":146,"name":147,"nameZh":6,"description":148,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":149,"categories":150,"keywords":152,"publishedAt":39},"01M6CPXMG2SCTAA04EB3PDRRXN","openai-transcribe","Transcribe audio files to text with optional diarization and known-speaker hints. Use when a user asks to transcribe speech from audio\u002Fvideo, extract text from recordings, or label speakers in interviews or meetings. (Imported from openai upstream skills)","https:\u002F\u002Fgithub.com\u002Fkhalidsaidi\u002Fskillrunner\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fopenai-transcribe\u002FSKILL.md",[151],{"categoryNo":134,"categoryName":135,"taxonomyType":107,"taxonomyTypeDesc":108},[23,153,129,38,32,37,36,35,142,143,144,141,82,137,29,138,139,27,140],"openai transcribe"]