Skill Seekers Feature Matrix

Skill Seekers Feature Matrix

Complete feature support across all platforms and skill modes.

Platform Support

Skill Mode Support

CLI Command Support

MCP Tool Support

Feature Comparison by Platform

Claude AI (Default)

• Format: YAML frontmatter + markdown
• Package: ZIP with SKILL.md, references/, scripts/, assets/
• Upload: POST to https://api.anthropic.com/v1/skills
• Enhancement: Claude Sonnet 4 (local or API)
• Unique Features: MCP integration, Skills API
• Limitations: No vector store, no file search

Google Gemini

• Format: Plain markdown (no frontmatter)
• Package: tar.gz with system_instructions.md, references/, metadata
• Upload: Google Files API
• Enhancement: Gemini 2.0 Flash
• Unique Features: Grounding support, long context (1M tokens)
• Limitations: tar.gz format only

OpenAI ChatGPT

• Format: Assistant instructions (plain text)
• Package: ZIP with assistant_instructions.txt, vector_store_files/, metadata
• Upload: Assistants API + Vector Store creation
• Enhancement: GPT-4o
• Unique Features: Vector store, file_search tool, semantic search
• Limitations: Requires Assistants API structure

Generic Markdown

• Format: Pure markdown (universal)
• Package: ZIP with README.md, DOCUMENTATION.md, references/
• Upload: None (manual distribution)
• Enhancement: None
• Unique Features: Works with any LLM, no API dependencies
• Limitations: No upload, no enhancement

Workflow Coverage

Single-Source Workflow

Config → Scrape → Build → [Enhance] → Package --target X → [Upload --target X]

Platforms: All 4 Modes: Docs, GitHub, PDF

Unified Multi-Source Workflow

Config → Scrape All → Detect Conflicts → Merge → Build → [Enhance] → Package --target X → [Upload --target X]

Platforms: All 4 Modes: Unified only

Complete Installation Workflow

install --target X → Fetch → Scrape → Enhance → Package → Upload

Platforms: All 4 Modes: All (via config type detection)

API Key Requirements

Note: Local enhancement (Claude Code Max) requires no API key for any platform.

Installation Options

# Core package (Claude only)
pip install skill-seekers

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

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

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

Examples

Package for Multiple Platforms (Same Skill)

# Scrape once (platform-agnostic)
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)

Upload to Multiple Platforms

export ANTHROPIC_API_KEY=sk-ant-...
export GOOGLE_API_KEY=AIzaSy...
export OPENAI_API_KEY=sk-proj-...

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

Use MCP Tools for Any Platform

# In Claude Code or any MCP client

# Package for Gemini
package_skill(skill_dir="output/react", target="gemini")

# Upload to OpenAI
upload_skill(skill_zip="output/react-openai.zip", target="openai")

# Enhance with Gemini
enhance_skill(skill_dir="output/react", target="gemini", mode="api")

Complete Workflow with Different Platforms

# Install React skill for Claude (default)
skill-seekers install --config react

# Install Django skill for Gemini
skill-seekers install --config django --target gemini

# Install FastAPI skill for OpenAI
skill-seekers install --config fastapi --target openai

# Install Vue skill as generic markdown
skill-seekers install --config vue --target markdown

Split Unified Config by Source

# Split multi-source config into separate configs
skill-seekers split --config configs/react_unified.json --strategy source

# Creates:
# - react-documentation.json (docs only)
# - react-github.json (GitHub only)

# Then scrape each separately
skill-seekers unified --config react-documentation.json
skill-seekers unified --config react-github.json

# Or scrape in parallel for speed
skill-seekers unified --config react-documentation.json &
skill-seekers unified --config react-github.json &
wait

Verification Checklist

Before release, verify all combinations:

CLI Commands × Platforms

• scrape → package claude → upload claude
• scrape → package gemini → upload gemini
• scrape → package openai → upload openai
• scrape → package markdown
• github → package (all platforms)
• pdf → package (all platforms)
• unified → package (all platforms)
• enhance claude
• enhance gemini
• enhance openai

MCP Tools × Platforms

• package_skill target=claude
• package_skill target=gemini
• package_skill target=openai
• package_skill target=markdown
• upload_skill target=claude
• upload_skill target=gemini
• upload_skill target=openai
• enhance_skill target=claude
• enhance_skill target=gemini
• enhance_skill target=openai
• install_skill target=claude
• install_skill target=gemini
• install_skill target=openai

Skill Modes × Platforms

• Docs → Claude
• Docs → Gemini
• Docs → OpenAI
• Docs → Markdown
• GitHub → All platforms
• PDF → All platforms
• Unified → All platforms
• Local Repo → All platforms

Platform-Specific Notes

Claude AI

• Best for: General-purpose skills, MCP integration
• When to use: Default choice, best MCP support
• File size limit: 25 MB per skill package

Google Gemini

• Best for: Large context skills, grounding support
• When to use: Need long context (1M tokens), grounding features
• File size limit: 100 MB per upload

OpenAI ChatGPT

• Best for: Vector search, semantic retrieval
• When to use: Need semantic search across documentation
• File size limit: 512 MB per vector store

Generic Markdown

• Best for: Universal compatibility, no API dependencies
• When to use: Using non-Claude/Gemini/OpenAI LLMs, offline use
• Distribution: Manual - share ZIP file directly

Frequently Asked Questions

Q: Can I package once and upload to multiple platforms? A: No. Each platform requires a platform-specific package format. You must:

1. Scrape once (universal)
2. Package separately for each platform (--target flag)
3. Upload each platform-specific package

Q: Do I need to scrape separately for each platform? A: No! Scraping is platform-agnostic. Scrape once, then package for multiple platforms.

Q: Which platform should I choose? A:

• Claude: Best default choice, excellent MCP integration
• Gemini: Choose if you need long context (1M tokens) or grounding
• OpenAI: Choose if you need vector search and semantic retrieval
• Markdown: Choose for universal compatibility or offline use

Q: Can I enhance a skill for different platforms? A: Yes! Enhancement adds platform-specific formatting:

• Claude: YAML frontmatter + markdown
• Gemini: Plain markdown with system instructions
• OpenAI: Plain text assistant instructions

Q: Do all skill modes work with all platforms? A: Yes! All 5 skill modes (Docs, GitHub, PDF, Unified, Local Repo) work with all 4 platforms.

See Also

• README.md - Complete user documentation
• UNIFIED_SCRAPING.md - Multi-source scraping guide
• ENHANCEMENT.md - AI enhancement guide
• UPLOAD_GUIDE.md - Upload instructions
• MCP_SETUP.md - MCP server setup