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Skills Cookbook - Claude Code Guide

This is a comprehensive Jupyter notebook cookbook demonstrating Claude's Skills feature for document generation (Excel, PowerPoint, PDF). It's designed for developers learning to integrate Skills into their applications.

Claude Code Knowledge Pack7/10/2026

Overview

Skills Cookbook - Claude Code Guide

Project Overview

This is a comprehensive Jupyter notebook cookbook demonstrating Claude's Skills feature for document generation (Excel, PowerPoint, PDF). It's designed for developers learning to integrate Skills into their applications.

Quick Start Commands

Environment Setup

# Create and activate virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\\Scripts\\activate

# Install dependencies (MUST use local whl for Skills support)
pip install -r requirements.txt

# Configure API key
cp .env.example .env
# Edit .env and add your ANTHROPIC_API_KEY

Running Notebooks

# Launch Jupyter
jupyter notebook

# Or use VSCode with Jupyter extension
# Make sure to select the venv kernel in VSCode: Cmd+Shift+P → "Python: Select Interpreter"

Testing & Verification

# Verify environment and SDK version
python -c "import anthropic; print(f'SDK Version: {anthropic.__version__}')"

# Check outputs directory for generated files
ls -lh outputs/

Architecture Overview

Directory Structure

skills/
├── notebooks/              # 3 progressive Jupyter notebooks
│   ├── 01_skills_introduction.ipynb
│   ├── 02_skills_financial_applications.ipynb  # WIP
│   └── 03_skills_custom_development.ipynb      # WIP
├── sample_data/           # Financial datasets for examples
├── custom_skills/         # Custom skill development area
├── outputs/               # Generated files (xlsx, pptx, pdf)
├── file_utils.py          # Files API helper functions
└── docs/                  # Implementation tracking

Key Technical Details

Beta API Requirements:

  • All Skills functionality uses client.beta.* namespace
  • Required beta headers: code-execution-2025-08-25, files-api-2025-04-14, skills-2025-10-02
  • Must use client.beta.messages.create() with container parameter
  • Code execution tool (code_execution_20250825) is REQUIRED
  • Use pre-built Agent skills by referencing their skill_id or create and upload your own via the Skills API

Files API Integration:

  • Skills generate files and return file_id attributes
  • Must use client.beta.files.download() to download files
  • Must use client.beta.files.retrieve_metadata() to get file info
  • Helper functions in file_utils.py handle extraction and download

Built-in Skills:

  • xlsx - Excel workbooks with formulas and charts
  • pptx - PowerPoint presentations
  • pdf - PDF documents
  • docx - Word documents

Development Gotchas

1. SDK Version

Important: Ensure you have the Anthropic SDK version 0.71.0 or later with Skills support

pip install anthropic>=0.71.0
# Restart Jupyter kernel after installation if upgrading!

2. Beta Namespace Required

Problem: container parameter not recognized, files API fails Solution: Use client.beta.messages.create() and client.beta.files.*

# ❌ Wrong
response = client.messages.create(container={...})
content = client.files.content(file_id)

# ✅ Correct
response = client.beta.messages.create(container={...})
content = client.beta.files.content(file_id)

3. Beta Headers Placement

Problem: Setting Skills beta in default_headers requires code_execution on ALL requests Solution: Use betas parameter per-request instead

# ❌ Wrong (affects all requests)
client = Anthropic(default_headers={"anthropic-beta": "skills-2025-10-02"})

# ✅ Correct (per-request)
response = client.beta.messages.create(
    betas=["code-execution-2025-08-25", "files-api-2025-04-14", "skills-2025-10-02"],
    ...
)

4. File ID Extraction

Problem: Response structure differs from standard Messages API Solution: File IDs in bash_code_execution_tool_result.content.content[0].file_id

# Use file_utils.extract_file_ids() - handles beta response structure
from file_utils import extract_file_ids, download_all_files
file_ids = extract_file_ids(response)

5. Files API Response Objects

Problem: 'BinaryAPIResponse' object has no attribute 'content', 'FileMetadata' object has no attribute 'size' Solution: Use .read() for file content and .size_bytes for file size

# ❌ Wrong
file_content = client.beta.files.download(file_id)
with open(path, 'wb') as f:
    f.write(file_content.content)  # No .content attribute!

# ✅ Correct
file_content = client.beta.files.download(file_id)
with open(path, 'wb') as f:
    f.write(file_content.read())  # Use .read()

# FileMetadata fields: id, filename, size_bytes (not size), mime_type, created_at, type, downloadable
metadata = client.beta.files.retrieve_metadata(file_id)
print(f"Size: {metadata.size_bytes} bytes")  # Use size_bytes, not size

6. Jupyter Kernel Selection

Problem: Wrong Python interpreter = wrong dependencies Solution: Always select venv kernel in VSCode/Jupyter

  • VSCode: Cmd+Shift+P → "Python: Select Interpreter" → select venv
  • Jupyter: Kernel → Change Kernel → select venv

7. Module Reload Required

Problem: Changes to file_utils.py not reflected in running notebooks Solution: Restart kernel or reload module


importlib.reload(file_utils)

8. Document Generation Times

Problem: File creation takes longer than typical API calls, users may think cell is frozen Actual Observed Times:

  • Excel: ~2 minutes
  • PowerPoint: ~1-2 minutes (simple 2-3 slide presentations)
  • PDF: ~1-2 minutes

Solution: Add clear timing expectations before file creation cells

**⏱️ Note**: Excel generation typically takes 1-2 minutes.
Be patient - the cell will show [*] while running!

Important: Keep examples simple and focused. Generation times are consistent at 1-2 minutes for well-scoped examples.

Common Tasks

Adding a New Notebook Section

  1. Follow existing structure in 01_skills_introduction.ipynb
  2. Include setup cell with imports and beta headers
  3. Show API call, response handling, file download
  4. Add error handling examples
  5. Update docs/skills_cookbook_plan.md checklist

Creating Sample Data

  1. Add realistic financial data to sample_data/
  2. Use CSV for tabular, JSON for structured
  3. Include headers and proper formatting
  4. Reference in notebook with pandas
  5. Keep file sizes reasonable (<100KB)

Testing File Download

  1. Run notebook cell to generate file
  2. Check response for file_id
  3. Use download_all_files() helper
  4. Verify file in outputs/ directory
  5. Open file in native app to validate

Note: Files are overwritten by default. You'll see [overwritten] in the download summary when a file already existed. Set overwrite=False to prevent this.

Debugging API Errors

  1. Check SDK version: anthropic.__version__ should be 0.69.0
  2. Verify beta headers are passed per-request
  3. Ensure code_execution tool is included
  4. Check response structure with print(response)
  5. Look for error details in response.stop_reason

Testing Checklist

Before committing notebook changes:

  • Restart kernel and run all cells
  • Verify all file downloads work
  • Check outputs/ for generated files
  • Validate files open correctly in native apps
  • Update skills_cookbook_plan.md checklist
  • Test in fresh virtual environment

Resources

Project-Specific Notes

  • Focus Domain: Finance & Analytics with practical business applications
  • Target Audience: Intermediate developers and business analysts
  • Notebook 1: Complete and tested (file downloads working)
  • Notebook 2: Financial Applications - next priority
  • Notebook 3: Custom Skills Development - after Notebook 2

Environment Variables

Required in .env:

ANTHROPIC_API_KEY=your-api-key-here

Optional (for advanced examples):

ANTHROPIC_BASE_URL=https://api.anthropic.com  # If using proxy