frankenstein

Synthesize the strongest parts of multiple AI skills into a single attribution-rich skill.

1|Updated Apr 20, 2026
One-click install
npx skills add https://github.com/IndianBoy42/dot-opencode --skill frankenstein
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: frankenstein
Source: https://github.com/IndianBoy42/dot-opencode/tree/main/skills/frankenstein
Command: npx skills add https://github.com/IndianBoy42/dot-opencode --skill frankenstein

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Combines the strongest parts of multiple AI skills into a single, best-of-breed Frankenstein skill, enabling faster, safer, and more capable AI tooling by reusing existing capabilities with clear attribution.

Core Features & Use Cases

  • Sourcing and evaluation across public skill repositories (ClawHub, GitHub, skills.sh, skillsmp.com and others)
  • Security-first analysis using skill-auditor and sandwrap for safe orchestration
  • Unified, attribution-rich skill construction that preserves provenance and licensing
  • End-to-end synthesis for complex workflows by merging methodologies and components

Quick Start

Frankenstein me an SEO audit skill.

Frequently Asked Questions about frankenstein

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I merge multiple AI skills into a single workflow?

You merge multiple AI skills by sourcing candidates from public repositories, analyzing them safely for security, and synthesizing the strongest parts into a single attribution-rich skill.

What is the best way to combine features from different AI skill repositories?

The best way to combine features from different AI skill repositories is to evaluate candidates across platforms like ClawHub and GitHub, apply security scanning, and construct a unified skill preserving provenance and licensing.

Can I aggregate source code from GitHub and ClawHub without losing attribution?

Yes, you can aggregate source code from GitHub and ClawHub while preserving attribution by synthesizing the combined skill with provenance tracking and clear licensing metadata.

How does security scanning work when merging external AI skills?

Security scanning during skill merging works by applying safe analysis and orchestration tools to evaluate each candidate skill, ensuring only vetted components are combined into the final workflow.

Does combining multiple AI skills require manual component comparison?

No, combining multiple AI skills does not require manual component comparison because the workflow automatically analyzes each candidate safely, compares features, and builds a combined skill with the best of each.

When should I not use a skill merging approach for AI workflows?

You should not use a skill merging approach when your workflow requires minimal dependencies, as the synthesis process aggregates multiple external components and creates a complex, attribution-rich combined skill.