✓ Verified 💻 Development ✓ Enhanced Data

Frankenstein

Combine the best parts of multiple skills into one.

Rating
4.2 (169 reviews)
Downloads
2,620 downloads
Version
1.0.0

Overview

Combine the best parts of multiple skills into one.

Key Features

1

Search All Sources

2

Security Scan

3

Safe Analysis

4

Compare

5

Synthesize

6

Build Initial Draft

7

Vetting Loop (CRITICAL)

8

Human Review

Complete Documentation

View Source →

Frankenstein

Model Requirements

Default: Opus (or best available thinking model)

Frankenstein requires deep reasoning to:

  • Compare multiple skill approaches
  • Identify subtle methodology differences
  • Synthesize the best parts creatively
  • Catch security/quality issues others miss
Only use a smaller model if user explicitly requests it for cost reasons. The synthesis quality depends heavily on reasoning depth.

Create monster skills by combining the best parts of existing ones.

Quick Start

text
Frankenstein me an SEO audit skill

How It Works

Step 1: Search All Sources

Search EVERY AI skills repository for matching skills:

1. ClawHub (primary)

bash
clawhub search "[topic]" --registry "https://clawhub.ai"

2. GitHub

text
Search: "[topic] AI skill" OR "[topic] claude skill" OR "[topic] agent skill"
Look for: SKILL.md, CLAUDE.md, or similar agent instruction files

3. skills.sh

text
https://skills.sh/search?q=[topic]

4. skillsmp.com (Skills Marketplace)

text
https://skillsmp.com/search/[topic]

5. Other sources to check:

  • Anthropic's skill examples
  • OpenAI GPT configurations (convert to skill format)
  • LangChain agent templates
  • AutoGPT/AgentGPT skill repos
Gather all candidates before filtering. More sources = better Frankenstein.

Step 2: Security Scan

Run each skill through skill-auditor. Skip any with HIGH risk scores.

For each skill found:

  • Install to temp directory
  • Run skill-auditor scan
  • Score >= 7 = SAFE (proceed)
  • Score < 7 = RISKY (skip with warning)

Step 3: Safe Analysis

Analyze safe skills in sandwrap read-only mode.

For each safe skill, extract:

  • Core features (what it does)
  • Methodology (how it approaches the problem)
  • Scripts/tools (reusable code)
  • Unique strengths (what makes it special)
  • Weaknesses (what's missing)

Step 4: Compare

Build comparison matrix:

Featureskill-Askill-Bskill-CWINNER
Feature 1YesNoYesA, C
Feature 2BasicAdvancedNoneB
Feature 3NoNoYesC

Step 5: Synthesize

Take the winning approach for each feature:
  • Feature 1 methodology from skill-A
  • Feature 2 implementation from skill-B
  • Feature 3 approach from skill-C

Step 6: Build Initial Draft

Use skill-creator to assemble the Frankenstein skill:
  • Combine winning features
  • Resolve conflicts (if two approaches clash)
  • Write unified SKILL.md
  • Include scripts from winners
  • Document sources

Step 7: Vetting Loop (CRITICAL)

Run plan → test → improve loop until 3 stable passes:

text
Pass 1:
  1. Read draft
  2. Try to break it (find holes, contradictions, gaps)
  3. Document issues
  4. Fix them
  
Pass 2:
  1. Read improved version
  2. Actively try to find MORE issues
  3. Fix any found
  
Pass 3+:
  Continue until you genuinely try to improve
  but can't find significant issues

What to look for each pass:

  • Missing features that sources had
  • Contradictions between combined approaches
  • Vague instructions that aren't actionable
  • Token waste (verbose where concise works)
  • Security gaps
  • Broken references to files/scripts
Document in VETTING-LOG.md:
  • Each pass number
  • Issues found
  • Fixes applied
  • Why considered stable
Only proceed when:
  • 3 consecutive passes with no major issues
  • Minor issues documented as known limitations

Step 8: Human Review

Present the vetted skill for approval:
  • Show what came from where
  • Highlight conflicts resolved
  • Show vetting summary
  • Ask for final OK before saving

Output

Creates a new skill with:

  • Best features from all analyzed skills
  • Clear attribution (credits source skills)
  • Security-scanned components only
  • Unified documentation

Example Session

User: "Frankenstein me an SEO audit skill"

Frankenstein:

text
Searching ClawHub for "SEO audit"...
Found 5 skills:
  1. seo-audit (coreyhaines31)
  2. audit-website (squirrelscan)
  3. seo-optimizer (local)
  4. technical-seo (unknown)
  5. seo-checker (unknown)

Security scanning...
  ✓ seo-audit: SAFE (8/10)
  ✓ audit-website: SAFE (7/10)
  ✓ seo-optimizer: SAFE (9/10)
  ✗ technical-seo: RISKY (4/10) - skipping
  ✗ seo-checker: RISKY (3/10) - skipping

Analyzing 3 safe skills...

Comparison:
| Feature              | seo-audit | audit-website | seo-optimizer |
|----------------------|-----------|---------------|---------------|
| Methodology depth    | ★★★★★     | ★★★           | ★★★★          |
| Automated rules      | None      | 230+          | 50+           |
| Auto-fix capability  | No        | No            | Yes           |
| CLI tool             | No        | squirrel      | No            |
| E-E-A-T coverage     | Yes       | Yes           | Partial       |

Recommended combination:
- Methodology: seo-audit (best framework)
- Rules engine: audit-website (230+ rules via squirrel CLI)
- Auto-fix: seo-optimizer (automated fixes)
- E-E-A-T: seo-audit (comprehensive)

Build this Frankenstein? [Yes/No]

Dependencies

This skill uses:

  • clawhub CLI (search/install)
  • skill-auditor (security scanning)
  • sandwrap (safe analysis)
  • skill-creator (building)

Spawning Sub-Agents

When spawning analysis sub-agents, always use Opus (or best thinking model) unless user explicitly requests otherwise:

text
sessions_spawn(
  task: "FRANKENSTEIN ANALYSIS: [topic]...",
  model: "opus"
)

Cheaper models miss nuances between skills and produce shallow combinations.

Limitations

  • Only combines publicly available skills
  • Skips skills that fail security scan
  • Cannot resolve deep architectural conflicts
  • Human judgment needed for final synthesis
  • Quality depends on available skills

Credits

When a Frankenstein skill is built, it includes attribution:

text
## Sources
Built from best parts of:
- seo-audit by coreyhaines31 (methodology)
- audit-website by squirrelscan (rules engine)
- seo-optimizer (auto-fix)

Installation

Terminal bash

openclaw install frankenstein
    
Copied!

💻Code Examples

Frankenstein me an SEO audit skill

frankenstein-me-an-seo-audit-skill.txt
## How It Works

### Step 1: Search All Sources

Search EVERY AI skills repository for matching skills:

**1. ClawHub (primary)**

https://skillsmp.com/search/[topic]

httpsskillsmpcomsearchtopic.txt
**5. Other sources to check:**
- Anthropic's skill examples
- OpenAI GPT configurations (convert to skill format)
- LangChain agent templates
- AutoGPT/AgentGPT skill repos

**Gather all candidates before filtering.** More sources = better Frankenstein.

### Step 2: Security Scan
Run each skill through skill-auditor. Skip any with HIGH risk scores.

For each skill found:
- Install to temp directory
- Run skill-auditor scan
- Score >= 7 = SAFE (proceed)
- Score < 7 = RISKY (skip with warning)

### Step 3: Safe Analysis
Analyze safe skills in sandwrap read-only mode.

For each safe skill, extract:
- Core features (what it does)
- Methodology (how it approaches the problem)
- Scripts/tools (reusable code)
- Unique strengths (what makes it special)
- Weaknesses (what's missing)

### Step 4: Compare
Build comparison matrix:

| Feature | skill-A | skill-B | skill-C | WINNER |
|---------|---------|---------|---------|--------|
| Feature 1 | Yes | No | Yes | A, C |
| Feature 2 | Basic | Advanced | None | B |
| Feature 3 | No | No | Yes | C |

### Step 5: Synthesize
Take the winning approach for each feature:
- Feature 1 methodology from skill-A
- Feature 2 implementation from skill-B
- Feature 3 approach from skill-C

### Step 6: Build Initial Draft
Use skill-creator to assemble the Frankenstein skill:
- Combine winning features
- Resolve conflicts (if two approaches clash)
- Write unified SKILL.md
- Include scripts from winners
- Document sources

### Step 7: Vetting Loop (CRITICAL)

**Run plan → test → improve loop until 3 stable passes:**

but can't find significant issues

-but-cant-find-significant-issues.txt
**What to look for each pass:**
- Missing features that sources had
- Contradictions between combined approaches
- Vague instructions that aren't actionable
- Token waste (verbose where concise works)
- Security gaps
- Broken references to files/scripts

**Document in VETTING-LOG.md:**
- Each pass number
- Issues found
- Fixes applied
- Why considered stable

**Only proceed when:**
- 3 consecutive passes with no major issues
- Minor issues documented as known limitations

### Step 8: Human Review
Present the vetted skill for approval:
- Show what came from where
- Highlight conflicts resolved
- Show vetting summary
- Ask for final OK before saving

## Output

Creates a new skill with:
- Best features from all analyzed skills
- Clear attribution (credits source skills)
- Security-scanned components only
- Unified documentation

## Example Session

User: "Frankenstein me an SEO audit skill"

Frankenstein:

Build this Frankenstein? [Yes/No]

build-this-frankenstein-yesno.txt
## Dependencies

This skill uses:
- clawhub CLI (search/install)
- skill-auditor (security scanning)
- sandwrap (safe analysis)
- skill-creator (building)

## Spawning Sub-Agents

When spawning analysis sub-agents, always use Opus (or best thinking model) unless user explicitly requests otherwise:

)

.txt
Cheaper models miss nuances between skills and produce shallow combinations.

## Limitations

- Only combines publicly available skills
- Skips skills that fail security scan
- Cannot resolve deep architectural conflicts
- Human judgment needed for final synthesis
- Quality depends on available skills

## Credits

When a Frankenstein skill is built, it includes attribution:
example.txt
Pass 1:
  1. Read draft
  2. Try to break it (find holes, contradictions, gaps)
  3. Document issues
  4. Fix them
  
Pass 2:
  1. Read improved version
  2. Actively try to find MORE issues
  3. Fix any found
  
Pass 3+:
  Continue until you genuinely try to improve
  but can't find significant issues
example.txt
Searching ClawHub for "SEO audit"...
Found 5 skills:
  1. seo-audit (coreyhaines31)
  2. audit-website (squirrelscan)
  3. seo-optimizer (local)
  4. technical-seo (unknown)
  5. seo-checker (unknown)

Security scanning...
  ✓ seo-audit: SAFE (8/10)
  ✓ audit-website: SAFE (7/10)
  ✓ seo-optimizer: SAFE (9/10)
  ✗ technical-seo: RISKY (4/10) - skipping
  ✗ seo-checker: RISKY (3/10) - skipping

Analyzing 3 safe skills...

Comparison:
| Feature              | seo-audit | audit-website | seo-optimizer |
|----------------------|-----------|---------------|---------------|
| Methodology depth    | ★★★★★     | ★★★           | ★★★★          |
| Automated rules      | None      | 230+          | 50+           |
| Auto-fix capability  | No        | No            | Yes           |
| CLI tool             | No        | squirrel      | No            |
| E-E-A-T coverage     | Yes       | Yes           | Partial       |

Recommended combination:
- Methodology: seo-audit (best framework)
- Rules engine: audit-website (230+ rules via squirrel CLI)
- Auto-fix: seo-optimizer (automated fixes)
- E-E-A-T: seo-audit (comprehensive)

Build this Frankenstein? [Yes/No]
example.txt
sessions_spawn(
  task: "FRANKENSTEIN ANALYSIS: [topic]...",
  model: "opus"
)
example.txt
## Sources
Built from best parts of:
- seo-audit by coreyhaines31 (methodology)
- audit-website by squirrelscan (rules engine)
- seo-optimizer (auto-fix)

Tags

#coding_agents-and-ides

Quick Info

Category Development
Model Claude 3.5
Complexity One-Click
Author rubenaquispe
Last Updated 3/10/2026
🚀
Optimized for
Claude 3.5
🧠

Ready to Install?

Get started with this skill in seconds

openclaw install frankenstein