feat(agents): добавлены skills для PDF, docs, slides, jupyter и spreadsheet

- Зачем: - расширены возможности AI-ассистентов для работы с документами и презентациями - Что: - добавлен skill pdf для работы с PDF файлами - добавлен skill doc для работы с Word документами - добавлен skill slides для создания презентаций PowerPoint - добавлен skill jupyter-notebook для работы с Jupyter ноутбуками - добавлен skill spreadsheet для работы с таблицами (Excel/CSV) - изменена модель Claude с sonnet на opus - Проверка: - проверка доступности skills в AI-ассистентах
2026-03-13 23:35:45 +03:00
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+---
+name: "jupyter-notebook"
+description: "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."
+---
+
+
+# Jupyter Notebook Skill
+
+Create clean, reproducible Jupyter notebooks for two primary modes:
+
+- Experiments and exploratory analysis
+- Tutorials and teaching-oriented walkthroughs
+
+Prefer the bundled templates and the helper script for consistent structure and fewer JSON mistakes.
+
+## When to use
+- Create a new `.ipynb` notebook from scratch.
+- Convert rough notes or scripts into a structured notebook.
+- Refactor an existing notebook to be more reproducible and skimmable.
+- Build experiments or tutorials that will be read or re-run by other people.
+
+## Decision tree
+- If the request is exploratory, analytical, or hypothesis-driven, choose `experiment`.
+- If the request is instructional, step-by-step, or audience-specific, choose `tutorial`.
+- If editing an existing notebook, treat it as a refactor: preserve intent and improve structure.
+
+## Skill path (set once)
+
+```bash
+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`).
+
+## Workflow
+1. Lock the intent.
+Identify the notebook kind: `experiment` or `tutorial`.
+Capture the objective, audience, and what "done" looks like.
+
+2. Scaffold from the template.
+Use the helper script to avoid hand-authoring raw notebook JSON.
+
+```bash
+uv run --python 3.12 python "$JUPYTER_NOTEBOOK_CLI" \
+  --kind experiment \
+  --title "Compare prompt variants" \
+  --out output/jupyter-notebook/compare-prompt-variants.ipynb
+```
+
+```bash
+uv run --python 3.12 python "$JUPYTER_NOTEBOOK_CLI" \
+  --kind tutorial \
+  --title "Intro to embeddings" \
+  --out output/jupyter-notebook/intro-to-embeddings.ipynb
+```
+
+3. Fill the notebook with small, runnable steps.
+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.
+
+4. Apply the right pattern.
+For experiments, follow `references/experiment-patterns.md`.
+For tutorials, follow `references/tutorial-patterns.md`.
+
+5. Edit safely when working with existing notebooks.
+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.
+
+6. Validate the result.
+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`.
+
+## Templates and helper script
+- Templates live in `assets/experiment-template.ipynb` and `assets/tutorial-template.ipynb`.
+- The helper script loads a template, updates the title cell, and writes a notebook.
+
+Script path:
+- `$JUPYTER_NOTEBOOK_CLI` (installed default: `$CODEX_HOME/skills/jupyter-notebook/scripts/new_notebook.py`)
+
+## Temp and output conventions
+- Use `tmp/jupyter-notebook/` for intermediate files; delete when done.
+- Write final artifacts under `output/jupyter-notebook/` when working in this repo.
+- Use stable, descriptive filenames (for example, `ablation-temperature.ipynb`).
+
+## Dependencies (install only when needed)
+Prefer `uv` for dependency management.
+
+Optional Python packages for local notebook execution:
+
+```bash
+uv pip install jupyterlab ipykernel
+```
+
+The bundled scaffold script uses only the Python standard library and does not require extra dependencies.
+
+## Environment
+No required environment variables.
+
+## Reference map
+- `references/experiment-patterns.md`: experiment structure and heuristics.
+- `references/tutorial-patterns.md`: tutorial structure and teaching flow.
+- `references/notebook-structure.md`: notebook JSON shape and safe editing rules.
+- `references/quality-checklist.md`: final validation checklist.
@@ -0,0 +1,6 @@
+interface:
+  display_name: "Jupyter Notebooks"
+  short_description: "Create Jupyter notebooks for experiments and tutorials"
+  icon_small: "./assets/jupyter-small.svg"
+  icon_large: "./assets/jupyter.png"
+  default_prompt: "Create a Jupyter notebook for this task with clear sections, runnable cells, and concise takeaways."
@@ -0,0 +1,110 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# Experiment: TITLE\n",
+        "\n",
+        "Objective:\n",
+        "- State the question you want to answer.\n",
+        "- Define the success criteria.\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Setup: imports and reproducibility\n",
+        "from __future__ import annotations\n",
+        "\n",
+        "import random\n",
+        "import statistics\n",
+        "\n",
+        "SEED = 7\n",
+        "random.seed(SEED)\n",
+        "SEED\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Plan\n",
+        "\n",
+        "- Hypothesis:\n",
+        "- Variables to sweep:\n",
+        "- Metrics to record:\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Define parameters and lightweight helpers\n",
+        "sample_size = 20\n",
+        "values = [random.random() for _ in range(sample_size)]\n",
+        "summary = {\n",
+        "    \"count\": len(values),\n",
+        "    \"mean\": statistics.fmean(values),\n",
+        "    \"min\": min(values),\n",
+        "    \"max\": max(values),\n",
+        "}\n",
+        "summary\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Results\n",
+        "\n",
+        "- Key observations:\n",
+        "- Surprises or failure modes:\n",
+        "- Decision: continue, pivot, or stop:\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Record findings in a minimal, copy-pasteable structure\n",
+        "result = {\n",
+        "    \"seed\": SEED,\n",
+        "    \"mean\": summary[\"mean\"],\n",
+        "    \"range\": summary[\"max\"] - summary[\"min\"],\n",
+        "}\n",
+        "result\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Next steps\n",
+        "\n",
+        "- What to try next:\n",
+        "- What to document elsewhere (PRD, notes, issue):\n"
+      ]
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python",
+      "version": "3.12"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 5
+}
@@ -0,0 +1,3 @@
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@@ -0,0 +1,107 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# Tutorial: TITLE\n",
+        "\n",
+        "Audience:\n",
+        "- Describe who this is for.\n",
+        "\n",
+        "Prerequisites:\n",
+        "- List required concepts or setup.\n",
+        "\n",
+        "Learning goals:\n",
+        "- By the end, the reader can...\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Outline\n",
+        "\n",
+        "1. Setup\n",
+        "2. A minimal working example\n",
+        "3. Variations and pitfalls\n",
+        "4. Exercises\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Setup cell: keep it short and deterministic\n",
+        "from __future__ import annotations\n",
+        "\n",
+        "import math\n",
+        "import random\n",
+        "\n",
+        "SEED = 21\n",
+        "random.seed(SEED)\n",
+        "SEED\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Step 1 - Start with a tiny example\n",
+        "\n",
+        "Explain what the next cell does in plain language.\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Minimal working example\n",
+        "angles = [0, math.pi / 4, math.pi / 2]\n",
+        "sines = [math.sin(a) for a in angles]\n",
+        "list(zip(angles, sines))\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Exercises\n",
+        "\n",
+        "- Try a different input.\n",
+        "- Predict the output before running the code.\n",
+        "- Note one common mistake and how to fix it.\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Exercise answer scaffold\n",
+        "def describe(values: list[float]) -> dict[str, float]:\n",
+        "    return {\"min\": min(values), \"max\": max(values)}\n",
+        "\n",
+        "describe(sines)\n"
+      ]
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python",
+      "version": "3.12"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 5
+}
@@ -0,0 +1,10 @@
+# Experiment Patterns
+
+Use this structure for exploratory and experimental work:
+
+- Title and objective: state the question and the success criteria.
+- Setup and reproducibility: import only what you need, set a seed early, and keep configuration in one short cell.
+- Plan: list hypotheses, sweeps, and metrics before running code.
+- Minimal baseline: start with the smallest runnable example and confirm it runs end-to-end before adding complexity.
+- Results and notes: summarize findings in markdown near the relevant code and record key metrics in a small dictionary or table-like structure.
+- Next steps: decide whether to continue, pivot, or stop, and capture follow-up ideas as short bullets.
@@ -0,0 +1,17 @@
+# Notebook Structure
+
+Jupyter notebooks are JSON documents with this high-level shape:
+
+- `nbformat` and `nbformat_minor`
+- `metadata`
+- `cells` (a list of markdown and code cells)
+
+When editing `.ipynb` files programmatically:
+
+- Preserve `nbformat` and `nbformat_minor` from the template.
+- Keep `cells` as an ordered list; do not reorder unless intentional.
+- For code cells, set `execution_count` to `null` when unknown.
+- For code cells, set `outputs` to an empty list when scaffolding.
+- For markdown cells, keep `cell_type="markdown"` and `metadata={}`.
+
+Prefer scaffolding from the bundled templates or `new_notebook.py` (for example, `$CODEX_HOME/skills/jupyter-notebook/scripts/new_notebook.py`) instead of hand-authoring raw notebook JSON.
@@ -0,0 +1,11 @@
+# Quality Checklist
+
+Before delivering a notebook:
+
+- Run it top-to-bottom at least once (or as much as the environment allows).
+- Ensure early cells set all required state; avoid hidden state from prior runs.
+- Keep outputs tidy. Avoid giant outputs when a short summary works.
+- Prefer small tables, key metrics, or short printouts.
+- Keep the narrative skimmable. Use headings and short bullets, and avoid long paragraphs.
+- Leave helpful TODOs only when necessary, and label them clearly.
+- If execution is not possible, call out the risk and how to validate locally.
@@ -0,0 +1,9 @@
+# Tutorial Patterns
+
+Use this structure for teaching and walkthroughs:
+
+- Audience, prerequisites, and learning goals: say who it is for, list what they should already know, and state what they will be able to do by the end.
+- Outline: provide a short numbered outline so readers can skim.
+- Step-by-step flow: pair a short markdown explanation with a small code cell that runs on its own and a brief interpretation of the result.
+- Exercises: include at least one exercise that reinforces the key concept and provide an answer scaffold in the next cell.
+- Pitfalls and extensions: call out one common mistake and how to fix it, and suggest one optional extension for curious readers.
@@ -0,0 +1,130 @@
+from __future__ import annotations
+
+import argparse
+import json
+import re
+from pathlib import Path
+from typing import Any
+
+
+def slugify(text: str) -> str:
+    lowered = text.strip().lower()
+    cleaned = re.sub(r"[^a-z0-9]+", "-", lowered)
+    collapsed = re.sub(r"-+", "-", cleaned).strip("-")
+    return collapsed or "notebook"
+
+
+def find_repo_root(start: Path) -> Path:
+    for candidate in (start, *start.parents):
+        if (candidate / ".git").exists():
+            return candidate
+    return start
+
+
+def load_template(skill_dir: Path, kind: str) -> dict[str, Any]:
+    asset_name = "experiment-template.ipynb" if kind == "experiment" else "tutorial-template.ipynb"
+    template_path = skill_dir / "assets" / asset_name
+    if not template_path.exists():
+        raise SystemExit(f"Missing template: {template_path}")
+    with template_path.open("r", encoding="utf-8") as f:
+        data = json.load(f)
+    if not isinstance(data, dict):
+        raise SystemExit(f"Unexpected template shape: {template_path}")
+    return data
+
+
+def update_title(notebook: dict[str, Any], kind: str, title: str) -> None:
+    prefix = "Experiment" if kind == "experiment" else "Tutorial"
+    expected = f"# {prefix}: {title}\n"
+
+    cells = notebook.get("cells")
+    if not isinstance(cells, list) or not cells:
+        raise SystemExit("Template notebook has no cells")
+
+    first_cell = cells[0]
+    if not isinstance(first_cell, dict) or first_cell.get("cell_type") != "markdown":
+        raise SystemExit("Template notebook must start with a markdown title cell")
+
+    source = first_cell.get("source", [])
+    if isinstance(source, str):
+        source_lines = [source]
+    elif isinstance(source, list):
+        source_lines = [str(line) for line in source]
+    else:
+        source_lines = []
+
+    if source_lines:
+        source_lines[0] = expected
+    else:
+        source_lines = [expected]
+
+    first_cell["source"] = source_lines
+
+    metadata = notebook.setdefault("metadata", {})
+    if not isinstance(metadata, dict):
+        raise SystemExit("Notebook metadata must be a mapping")
+
+    language_info = metadata.setdefault("language_info", {})
+    if isinstance(language_info, dict):
+        language_info.setdefault("name", "python")
+        language_info.setdefault("version", "3.12")
+
+
+def default_output(repo_root: Path, title: str) -> Path:
+    filename = f"{slugify(title)}.ipynb"
+    return repo_root / "output" / "jupyter-notebook" / filename
+
+
+def parse_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser(description="Scaffold a Jupyter notebook for experiments or tutorials.")
+    parser.add_argument(
+        "--kind",
+        choices=["experiment", "tutorial"],
+        default="experiment",
+        help="Notebook style to scaffold (default: experiment).",
+    )
+    parser.add_argument(
+        "--title",
+        required=True,
+        help="Human-readable notebook title used in the first markdown cell.",
+    )
+    parser.add_argument(
+        "--out",
+        type=Path,
+        default=None,
+        help="Output path for the notebook. Defaults to output/jupyter-notebook/<slug>.ipynb.",
+    )
+    parser.add_argument(
+        "--force",
+        action="store_true",
+        help="Overwrite the output file if it already exists.",
+    )
+    return parser.parse_args()
+
+
+def main() -> None:
+    args = parse_args()
+
+    script_path = Path(__file__).resolve()
+    skill_dir = script_path.parents[1]
+    repo_root = find_repo_root(skill_dir)
+
+    notebook = load_template(skill_dir, args.kind)
+    update_title(notebook, args.kind, args.title)
+
+    out_path = args.out or default_output(repo_root, args.title)
+    out_path = out_path.resolve()
+
+    if out_path.exists() and not args.force:
+        raise SystemExit(f"Refusing to overwrite existing file without --force: {out_path}")
+
+    out_path.parent.mkdir(parents=True, exist_ok=True)
+    with out_path.open("w", encoding="utf-8") as f:
+        json.dump(notebook, f, indent=2)
+        f.write("\n")
+
+    print(f"Wrote {out_path} using kind={args.kind}.")
+
+
+if __name__ == "__main__":
+    main()