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在用户请求为实验、探索或教程创建、搭建或编辑 Jupyter 笔记本（`.ipynb`）时使用；优先使用捆绑的模板并运行辅助脚本 `new_notebook.py` 来生成一个干净的起始笔记本。
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Baseado na classificação ocupacional SOC
Tumia wakati unapoombwa kuthibitisha, kujaribu, kufanya mtihani wa haraka, au kuendesha daftari la kozi na mifano ya msimbo dhidi ya usanidi hai wa Microsoft Foundry / Azure OpenAI. Inajumuisha usanidi wa mazingira (.env, az login, vifurushi), mchezaji wa scripts/validate-notebooks.ps1, kutafsiri matokeo ya PASS/FAIL, na ni masomo yapi yanayohitaji rasilimali za ziada (Azure AI Search, GitHub MCP, Foundry Local, Playwright).
Použite, keď sa vyžaduje overenie, testovanie, rýchle testovanie alebo spustenie poznámkového bloku kurzu a ukážok kódu proti živej konfigurácii Microsoft Foundry / Azure OpenAI. Pokrýva nastavenie prostredia (.env, az login, balíky), skript runner scripts/validate-notebooks.ps1, interpretáciu výsledkov PASS/FAIL a ktoré lekcie potrebujú ďalšie zdroje (Azure AI Search, GitHub MCP, Foundry Local, Playwright).
Brukes når du blir bedt om å validere, teste, røykteste eller kjøre kursets notatbok og kodeeksempler mot en aktiv Microsoft Foundry / Azure OpenAI-konfigurasjon. Dekker miljøoppsett (.env, az login, pakker), skriptet/validate-notebooks.ps1-kjøreren, tolkning av PASS/FAIL-resultater, og hvilke leksjoner som trenger ekstra ressurser (Azure AI Search, GitHub MCP, Foundry Local, Playwright).
Gamitin kapag hiniling na i-validate, subukan, smoke-test, o patakbuhin ang notebook ng kurso at mga halimbawa ng code laban sa isang live na Microsoft Foundry / Azure OpenAI na configuration. Saklaw nito ang pag-setup ng kapaligiran (.env, az login, mga package), ang scripts/validate-notebooks.ps1 runner, ang pagpapakahulugan ng mga resulta na PASS/FAIL, at kung aling mga aralin ang nangangailangan ng karagdagang mga mapagkukunan (Azure AI Search, GitHub MCP, Foundry Local, Playwright).
Use wen dem ask you to validate, test, smoke-test, or run di course notebook and code samples against live Microsoft Foundry / Azure OpenAI configuration. E cover environment setup (.env, az login, packages), di scripts/validate-notebooks.ps1 runner, how to understand PASS/FAIL results, and which lessons need extra resources (Azure AI Search, GitHub MCP, Foundry Local, Playwright).
Use when asked to validate, test, smoke-test, or run the course's notebook and code samples against a live Microsoft Foundry / Azure OpenAI configuration. Covers environment setup (.env, az login, packages), the scripts/validate-notebooks.ps1 runner, interpreting PASS/FAIL results, and which lessons need extra resources (Azure AI Search, GitHub MCP, Foundry Local, Playwright).
| name | jupyter-notebook |
| description | 在用户请求为实验、探索或教程创建、搭建或编辑 Jupyter 笔记本（`.ipynb`）时使用；优先使用捆绑的模板并运行辅助脚本 `new_notebook.py` 来生成一个干净的起始笔记本。 |
为两种主要模式创建简洁、可重现的 Jupyter 笔记本：
优先使用捆绑的模板和辅助脚本，以获得一致的结构并减少 JSON 错误。
.ipynb 笔记本。experiment。tutorial。export CODEX_HOME="${CODEX_HOME:-$HOME/.codex}"
export JUPYTER_NOTEBOOK_CLI="$CODEX_HOME/skills/jupyter-notebook/scripts/new_notebook.py"
User-scoped skills install under $CODEX_HOME/skills (default: ~/.codex/skills).
确定意图。
Identify the notebook kind: experiment or tutorial.
Capture the objective, audience, and what "done" looks like.
从模板搭建脚手架。 Use the helper script to avoid hand-authoring raw notebook JSON.
uv run --python 3.12 python "$JUPYTER_NOTEBOOK_CLI" \
--kind experiment \
--title "Compare prompt variants" \
--out output/jupyter-notebook/compare-prompt-variants.ipynb
uv run --python 3.12 python "$JUPYTER_NOTEBOOK_CLI" \
--kind tutorial \
--title "Intro to embeddings" \
--out output/jupyter-notebook/intro-to-embeddings.ipynb
用小的、可运行的步骤填充笔记本。 Keep each code cell focused on one step. Add short markdown cells that explain the purpose and expected result. Avoid large, noisy outputs when a short summary works.
应用合适的模式。
For experiments, follow references/experiment-patterns.md.
For tutorials, follow references/tutorial-patterns.md.
在处理现有笔记本时安全编辑。
Preserve the notebook structure; avoid reordering cells unless it improves the top-to-bottom story.
Prefer targeted edits over full rewrites.
If you must edit raw JSON, review references/notebook-structure.md first.
验证结果。
Run the notebook top-to-bottom when the environment allows.
If execution is not possible, say so explicitly and call out how to validate locally.
Use the final pass checklist in references/quality-checklist.md.
assets/experiment-template.ipynb 和 assets/tutorial-template.ipynb。脚本路径：
$JUPYTER_NOTEBOOK_CLI (安装默认: $CODEX_HOME/skills/jupyter-notebook/scripts/new_notebook.py)tmp/jupyter-notebook/；完成后删除。output/jupyter-notebook/。ablation-temperature.ipynb）。Prefer uv for dependency management.
Optional Python packages for local notebook execution:
uv pip install jupyterlab ipykernel
The bundled scaffold script uses only the Python standard library and does not require extra dependencies.
No required environment variables.
references/experiment-patterns.md: 实验结构与启发式准则。references/tutorial-patterns.md: 教程结构与教学流程。references/notebook-structure.md: 笔记本 JSON 结构与安全编辑规则。references/quality-checklist.md: 最终验证检查清单。免责声明： 本文件已使用 AI 翻译服务 Co-op Translator 进行翻译。虽然我们努力保证准确性，但自动翻译可能存在错误或不准确之处。应以原文（原始语言版本）为准。对于重要信息，建议采用专业人工翻译。由于使用本翻译而导致的任何误解或误释，我们概不负责。