[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6FDX5X9TAAT05HS3XM8J5D9":3,"skill-same:01M6FDX5X9TAAT05HS3XM8J5D9":53},{"skillNo":4,"name":5,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":7,"ownerLogin":8,"ownerAvatarUrl":9,"ownerAccountNo":10,"ownerDisplayName":11,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":22,"publishedAt":26,"linkOnly":27,"markdownContent":28,"markdownBody":28,"frontMatter":29,"refName":30,"commitSha":31,"skillDirectory":32,"forksCount":33,"repositoryHtmlUrl":34,"repositoryHomepageUrl":35,"ownerHtmlUrl":36,"ownerBlogUrl":6,"ownerDescription":37,"updatedAt":38,"install":39,"resources":52},"01M6FDX5X9TAAT05HS3XM8J5D9","jupyter-notebook",null,"ComeOnOliver\u002Fskillshub","ComeOnOliver","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F43215937?v=4","01M6E5JNFECJAAVFE0W7SMWWD2","Haoran Shu","01M6E5JNNDQS7AJZDYFQ8TPZCK",67,"MIT","https:\u002F\u002Fgithub.com\u002FComeOnOliver\u002Fskillshub\u002Fblob\u002Fmain\u002Fskills\u002Fopenai\u002Fskills\u002Fjupyter-notebook\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[23,24,25],"jupyter notebook","jupyter","notebook","2026-11-10 10:12:30",false,"# 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",{},"main","def8531e65114c0fca8fb8551c1871ee0eed705c","skills\u002Fopenai\u002Fskills\u002Fjupyter-notebook",24,"https:\u002F\u002Fgithub.com\u002FComeOnOliver\u002Fskillshub","https:\u002F\u002Fskillshub.wtf","https:\u002F\u002Fgithub.com\u002FComeOnOliver","AI & Blockchain Engineer\r\n","2026-06-24 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