Multi-Platform Upload Guide

Multi-Platform Upload Guide

Skill Seekers supports uploading to 4 LLM platforms: Claude AI, Google Gemini, OpenAI ChatGPT, and Generic Markdown export.

Quick Platform Selection

Claude AI (Default)

Prerequisites

# Option 1: Set API key for automatic upload
export ANTHROPIC_API_KEY=sk-ant-...

# Option 2: No API key (manual upload)
# No setup needed - just package and upload manually

Package for Claude

# Claude uses ZIP format (default)
skill-seekers package output/react/

Output: output/react.zip

Upload to Claude

Option 1: Automatic (with API key)

skill-seekers upload output/react.zip

Option 2: Manual (no API key)

1. Go to https://claude.ai/skills
2. Click "Upload Skill" or "Add Skill"
3. Select output/react.zip
4. Done!

Option 3: MCP (easiest)

In Claude Code, just say:
"Package and upload the React skill"

What's inside the ZIP:

react.zip
├── SKILL.md            ← Main skill file (YAML frontmatter + markdown)
└── references/         ← Reference documentation
    ├── index.md
    ├── api.md
    └── ...

Google Gemini

Prerequisites

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

# Set API key
export GOOGLE_API_KEY=AIzaSy...

Package for Gemini

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

Output: output/react-gemini.tar.gz

Upload to Gemini

skill-seekers upload output/react-gemini.tar.gz --target gemini

What happens:

• Uploads to Google Files API
• Creates grounding resource
• Available in Google AI Studio

Access your skill:

• Go to https://aistudio.google.com/
• Your skill is available as grounding data

What's inside the tar.gz:

react-gemini.tar.gz
├── system_instructions.md  ← Main skill file (plain markdown, no frontmatter)
├── references/             ← Reference documentation
│   ├── index.md
│   ├── api.md
│   └── ...
└── gemini_metadata.json    ← Gemini-specific metadata

Format differences:

• No YAML frontmatter (Gemini uses plain markdown)
• SKILL.md → system_instructions.md
• Includes gemini_metadata.json for platform integration

OpenAI ChatGPT

Prerequisites

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

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

Package for OpenAI

# OpenAI uses ZIP format with vector store
skill-seekers package output/react/ --target openai

Output: output/react-openai.zip

Upload to OpenAI

skill-seekers upload output/react-openai.zip --target openai

What happens:

• Creates OpenAI Assistant via Assistants API
• Creates Vector Store for semantic search
• Uploads reference files to vector store
• Enables file_search tool automatically

Access your assistant:

• Go to https://platform.openai.com/assistants/
• Your assistant is listed with name based on skill
• Includes file search enabled

What's inside the ZIP:

react-openai.zip
├── assistant_instructions.txt  ← Main skill file (plain text, no YAML)
├── vector_store_files/         ← Files for vector store
│   ├── index.md
│   ├── api.md
│   └── ...
└── openai_metadata.json        ← OpenAI-specific metadata

Format differences:

• No YAML frontmatter (OpenAI uses plain text)
• SKILL.md → assistant_instructions.txt
• Reference files packaged separately for Vector Store
• Includes openai_metadata.json for assistant configuration

Unique features:

• ✅ Semantic search across documentation
• ✅ Vector Store for efficient retrieval
• ✅ File search tool enabled by default

Generic Markdown (Universal Export)

Package for Markdown

# Generic markdown for manual distribution
skill-seekers package output/react/ --target markdown

Output: output/react-markdown.zip

Distribution

No upload API available - Use for manual distribution:

• Share ZIP file directly
• Upload to documentation hosting
• Include in git repositories
• Use with any LLM that accepts markdown

What's inside the ZIP:

react-markdown.zip
├── README.md               ← Getting started guide
├── DOCUMENTATION.md        ← Combined documentation
├── references/             ← Separate reference files
│   ├── index.md
│   ├── api.md
│   └── ...
└── manifest.json           ← Skill metadata

Format differences:

• No platform-specific formatting
• Pure markdown - works anywhere
• Combined DOCUMENTATION.md for easy reading
• Separate references/ for modular access

Use cases:

• Works with any LLM (local models, other platforms)
• Documentation website hosting
• Offline documentation
• Share via git/email
• Include in project repositories

Complete Workflow

Single Platform (Claude)

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

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

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

# 4. Upload to Claude
skill-seekers upload output/react.zip

Multi-Platform (Same Skill)

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

# 2. Enhance once (or per-platform if desired)
skill-seekers enhance output/react/

# 3. 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

# 4. Upload to platforms
export ANTHROPIC_API_KEY=sk-ant-...
export GOOGLE_API_KEY=AIzaSy...
export OPENAI_API_KEY=sk-proj-...

skill-seekers upload output/react.zip --target claude
skill-seekers upload output/react-gemini.tar.gz --target gemini
skill-seekers upload output/react-openai.zip --target openai

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

File Size Limits

Platform Limits

Check package size:

ls -lh output/react.zip

Most skills are small:

• Small skill: 5-20 KB
• Medium skill: 20-100 KB
• Large skill: 100-500 KB

Troubleshooting

"SKILL.md not found"

Make sure you scraped and built first:

skill-seekers scrape --config configs/react.json
skill-seekers package output/react/

"Invalid target platform"

Use valid platform names:

# Valid
--target claude
--target gemini
--target openai
--target markdown

# Invalid
--target anthropic  ❌
--target google     ❌

"API key not set"

Claude:

export ANTHROPIC_API_KEY=sk-ant-...

Gemini:

export GOOGLE_API_KEY=AIzaSy...
pip install skill-seekers[gemini]

OpenAI:

export OPENAI_API_KEY=sk-proj-...
pip install skill-seekers[openai]

Upload fails

If API upload fails, you can always use manual upload:

• Claude: https://claude.ai/skills
• Gemini: https://aistudio.google.com/
• OpenAI: https://platform.openai.com/assistants/

Wrong file format

Each platform requires specific format:

• Claude/OpenAI/Markdown: .zip file
• Gemini: .tar.gz file

Make sure to use --target parameter when packaging.

Platform Comparison

Format Comparison

Upload Comparison

Enhancement Comparison

API Key Setup

Get API Keys

Claude (Anthropic):

1. Go to https://console.anthropic.com/
2. Create API key
3. Copy key (starts with sk-ant-)
4. export ANTHROPIC_API_KEY=sk-ant-...

Gemini (Google):

1. Go to https://aistudio.google.com/
2. Get API key
3. Copy key (starts with AIza)
4. export GOOGLE_API_KEY=AIzaSy...

OpenAI:

1. Go to https://platform.openai.com/
2. Create API key
3. Copy key (starts with sk-proj-)
4. export OPENAI_API_KEY=sk-proj-...

Persist API Keys

Add to shell profile to keep them set:

# macOS/Linux (bash)
echo 'export ANTHROPIC_API_KEY=sk-ant-...' >> ~/.bashrc
echo 'export GOOGLE_API_KEY=AIzaSy...' >> ~/.bashrc
echo 'export OPENAI_API_KEY=sk-proj-...' >> ~/.bashrc

# macOS (zsh)
echo 'export ANTHROPIC_API_KEY=sk-ant-...' >> ~/.zshrc
echo 'export GOOGLE_API_KEY=AIzaSy...' >> ~/.zshrc
echo 'export OPENAI_API_KEY=sk-proj-...' >> ~/.zshrc

Then restart your terminal or run:

source ~/.bashrc  # or ~/.zshrc

See Also

• FEATURE_MATRIX.md - Complete feature comparison
• MULTI_LLM_SUPPORT.md - Multi-platform guide
• ENHANCEMENT.md - AI enhancement guide
• README.md - Main documentation