611 Multi LLM Support Ea2cf3f6

Multi-LLM Platform Support Guide

Skill Seekers supports multiple LLM platforms through a clean adaptor system. The core scraping and content organization remains universal, while packaging and upload are platform-specific.

Supported Platforms

Quick Start

Claude AI (Default)

No changes needed! All existing workflows continue to work:

# Scrape documentation
skill-seekers scrape --config configs/react.json

# Package for Claude (default)
skill-seekers package output/react/

# Upload to Claude
skill-seekers upload react.zip

Google Gemini

# Install Gemini support
pip install skill-seekers[gemini]

# Set API key
export GOOGLE_API_KEY=AIzaSy...

# Scrape documentation (same as always)
skill-seekers scrape --config configs/react.json

# Package for Gemini
skill-seekers package output/react/ --target gemini

# Upload to Gemini
skill-seekers upload react-gemini.tar.gz --target gemini

# Optional: Enhance with Gemini
skill-seekers enhance output/react/ --target gemini

Output: react-gemini.tar.gz ready for Google AI Studio

OpenAI ChatGPT

# Install OpenAI support
pip install skill-seekers[openai]

# Set API key
export OPENAI_API_KEY=sk-proj-...

# Scrape documentation (same as always)
skill-seekers scrape --config configs/react.json

# Package for OpenAI
skill-seekers package output/react/ --target openai

# Upload to OpenAI (creates Assistant + Vector Store)
skill-seekers upload react-openai.zip --target openai

# Optional: Enhance with GPT-4o
skill-seekers enhance output/react/ --target openai

Output: OpenAI Assistant created with file search enabled

Generic Markdown (Universal Export)

# Package as generic markdown (no dependencies)
skill-seekers package output/react/ --target markdown

# Output: react-markdown.zip with:
#   - README.md
#   - references/*.md
#   - DOCUMENTATION.md (combined)

Use case: Export for any LLM, documentation hosting, or manual distribution

Installation Options

Install Core Package Only

# Default installation (Claude support only)
pip install skill-seekers

Install with Specific Platform Support

# Google Gemini support
pip install skill-seekers[gemini]

# OpenAI ChatGPT support
pip install skill-seekers[openai]

# All LLM platforms
pip install skill-seekers[all-llms]

# Development dependencies (includes testing)
pip install skill-seekers[dev]

Install from Source

git clone https://github.com/yusufkaraaslan/Skill_Seekers.git
cd Skill_Seekers

# Editable install with all platforms
pip install -e .[all-llms]

Platform Comparison

Format Differences

Claude AI:

• Format: ZIP archive
• SKILL.md: YAML frontmatter + markdown
• Structure: SKILL.md, references/, scripts/, assets/
• API: Anthropic Skills API
• Enhancement: Claude Sonnet 4

Google Gemini:

• Format: tar.gz archive
• SKILL.md → system_instructions.md (plain markdown, no frontmatter)
• Structure: system_instructions.md, references/, gemini_metadata.json
• API: Google Files API + grounding
• Enhancement: Gemini 2.0 Flash

OpenAI ChatGPT:

• Format: ZIP archive
• SKILL.md → assistant_instructions.txt (plain text)
• Structure: assistant_instructions.txt, vector_store_files/, openai_metadata.json
• API: Assistants API + Vector Store
• Enhancement: GPT-4o

Generic Markdown:

• Format: ZIP archive
• Structure: README.md, references/, DOCUMENTATION.md (combined)
• No API integration
• No enhancement support
• Universal compatibility

API Key Configuration

Claude AI:

export ANTHROPIC_API_KEY=sk-ant-...

Google Gemini:

export GOOGLE_API_KEY=AIzaSy...

OpenAI ChatGPT:

export OPENAI_API_KEY=sk-proj-...

Complete Workflow Examples

Workflow 1: Claude AI (Default)

# 1. Scrape
skill-seekers scrape --config configs/react.json

# 2. Enhance (optional but recommended)
skill-seekers enhance output/react/

# 3. Package
skill-seekers package output/react/

# 4. Upload
skill-seekers upload react.zip

# Access at: https://claude.ai/skills

Workflow 2: Google Gemini

# Setup (one-time)
pip install skill-seekers[gemini]
export GOOGLE_API_KEY=AIzaSy...

# 1. Scrape (universal)
skill-seekers scrape --config configs/react.json

# 2. Enhance for Gemini
skill-seekers enhance output/react/ --target gemini

# 3. Package for Gemini
skill-seekers package output/react/ --target gemini

# 4. Upload to Gemini
skill-seekers upload react-gemini.tar.gz --target gemini

# Access at: https://aistudio.google.com/files/

Workflow 3: OpenAI ChatGPT

# Setup (one-time)
pip install skill-seekers[openai]
export OPENAI_API_KEY=sk-proj-...

# 1. Scrape (universal)
skill-seekers scrape --config configs/react.json

# 2. Enhance with GPT-4o
skill-seekers enhance output/react/ --target openai

# 3. Package for OpenAI
skill-seekers package output/react/ --target openai

# 4. Upload (creates Assistant + Vector Store)
skill-seekers upload react-openai.zip --target openai

# Access at: https://platform.openai.com/assistants/

Workflow 4: Export to All Platforms

# Install all platforms
pip install skill-seekers[all-llms]

# Scrape once
skill-seekers scrape --config configs/react.json

# Package for all platforms
skill-seekers package output/react/ --target claude
skill-seekers package output/react/ --target gemini
skill-seekers package output/react/ --target openai
skill-seekers package output/react/ --target markdown

# Result:
# - react.zip (Claude)
# - react-gemini.tar.gz (Gemini)
# - react-openai.zip (OpenAI)
# - react-markdown.zip (Universal)

Advanced Usage

Custom Enhancement Models

Each platform uses its default enhancement model, but you can customize:

# Use specific model for enhancement (if supported)
skill-seekers enhance output/react/ --target gemini --model gemini-2.0-flash-exp
skill-seekers enhance output/react/ --target openai --model gpt-4o

Programmatic Usage

from skill_seekers.cli.adaptors import get_adaptor

# Get platform-specific adaptor
gemini = get_adaptor('gemini')
openai = get_adaptor('openai')
claude = get_adaptor('claude')

# Package for specific platform
gemini_package = gemini.package(skill_dir, output_path)
openai_package = openai.package(skill_dir, output_path)

# Upload with API key
result = gemini.upload(gemini_package, api_key)
print(f"Uploaded to: {result['url']}")

Platform Detection

Check which platforms are available:

from skill_seekers.cli.adaptors import list_platforms, is_platform_available

# List all registered platforms
platforms = list_platforms()
print(platforms)  # ['claude', 'gemini', 'openai', 'markdown']

# Check if platform is available
if is_platform_available('gemini'):
    print("Gemini adaptor is available")

Backward Compatibility

100% backward compatible with existing workflows:

• All existing Claude commands work unchanged
• Default behavior remains Claude-focused
• Optional --target flag adds multi-platform support
• No breaking changes to existing configs or workflows

Platform-Specific Guides

For detailed platform-specific instructions, see:

• Claude AI Integration (default)
• Google Gemini Integration
• OpenAI ChatGPT Integration

Troubleshooting

Missing Dependencies

Error: ModuleNotFoundError: No module named 'google.generativeai'

Solution:

pip install skill-seekers[gemini]

Error: ModuleNotFoundError: No module named 'openai'

Solution:

pip install skill-seekers[openai]

API Key Issues

Error: Invalid API key format

Solution: Check your API key format:

• Claude: sk-ant-...
• Gemini: AIza...
• OpenAI: sk-proj-... or sk-...

Package Format Errors

Error: Not a tar.gz file: react.zip

Solution: Use correct --target flag:

# Gemini requires tar.gz
skill-seekers package output/react/ --target gemini

# OpenAI and Claude use ZIP
skill-seekers package output/react/ --target openai

FAQ

Q: Can I use the same scraped data for all platforms?

A: Yes! The scraping phase is universal. Only packaging and upload are platform-specific.

Q: Do I need separate API keys for each platform?

A: Yes, each platform requires its own API key. Set them as environment variables.

Q: Can I enhance with different models?

A: Yes, each platform uses its own enhancement model:

• Claude: Claude Sonnet 4
• Gemini: Gemini 2.0 Flash
• OpenAI: GPT-4o

Q: What if I don't want to upload automatically?

A: Use the package command without upload. You'll get the packaged file to upload manually.

Q: Is the markdown export compatible with all LLMs?

A: Yes! The generic markdown export creates universal documentation that works with any LLM or documentation system.

Q: Can I contribute a new platform adaptor?

A: Absolutely! See the Contributing Guide for how to add new platform adaptors.

Next Steps

1. Choose your target platform
2. Install optional dependencies if needed
3. Set up API keys
4. Follow the platform-specific workflow
5. Upload and test your skill

For more help, see:

• Quick Start Guide
• Troubleshooting Guide
• Platform-Specific Guides