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
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ddadmin committed 2026-03-13 23:35:45 +03:00
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{
"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
}
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{
"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
}