Prepper Skill
by @jlevitsk
Consult the ollama dolphin-llama3 model for survival, emergency preparedness, and prepper-related questions. Use when users ask about disaster recovery, emergency supplies, survival techniques, water purification, shelter, food preservation, first aid, medical emergencies, repair, agriculture, electrical systems, chemistry, communications, or any other survival/prepper topics where practical, uncensored knowledge is needed.
clawhub install prepperπ About This Skill
name: prepper description: Consult the ollama dolphin-llama3 model for survival, emergency preparedness, and prepper-related questions. Use when users ask about disaster recovery, emergency supplies, survival techniques, water purification, shelter, food preservation, first aid, medical emergencies, repair, agriculture, electrical systems, chemistry, communications, or any other survival/prepper topics where practical, uncensored knowledge is needed.
Prepper Skill
This skill consults a specialized ollama model (dolphin-llama3) that has been trained on practical survival and preparedness knowledge. Unlike corporate AI filters, this model provides uncensored answers to real-world survival questions.
Inspired by: AI-Survival-USB by The Wired Watchman
Model Knowledge
The dolphin-llama3 model (8 billion parameters) was trained on the equivalent of ~122 million books (~15 trillion training tokens), giving it knowledge across:
Quick Start
Workflow: Hybrid Validation (Recommended)
1. Query ollama for the uncensored survival answer 2. Validate/enhance with Claude (your active model) 3. Return the best merged result
Process:
# Get ollama answer in JSON format (for analysis)
python3 scripts/query_prepper_model.py --json "Your question here"
Then evaluate the result:
Quick Human-Readable Output
For quick testing or reference:
python3 scripts/query_prepper_model.py "Your question here"
Setup Requirements
Before using this skill, ensure:
1. Ollama installed: ollama --version should return a version
2. Model pulled: ollama list | grep dolphin-llama3
- If not present, pull it: ollama pull dolphin-llama3
3. Ollama running: The service must be running on localhost:11434
- Start with: ollama serve or ensure it's running as a daemon
See references/setup.md for detailed setup instructions.
How It Works
The Hybrid Approach
The skill uses two models for better reliability and accuracy:
Phase 1: Uncensored Knowledge (Ollama)
Phase 2: Validation & Enhancement (Claude)
Phase 3: Intelligent Merge
Example Workflow
User asks: "How do I purify water in an emergency?"
1. Script queries ollama β "Boil for 5 min, use Potable Aqua tablets, solar disinfection..." 2. Claude reviews answer β Can enhance with warnings about different water types 3. Return merged answer: Ollama's methods + Claude's safety context
When to Trigger This Skill
Use this skill when:
Decision Tree for This Skill
I will use this skill and:
1. Query ollama alone β If the topic is highly niche, offline-focused, or commercial AI would refuse 2. Query ollama + enhance with Claude β Most common case; merge both answers for best result 3. Query ollama but prefer Claude β If my answer is more accurate, current, or contextually better 4. Use ollama uncensored answer β If Claude refuses the question but the answer is critical information
Notes
Detailed Strategy
For a complete guide on how to evaluate, merge, and present both answers intelligently, see references/hybrid-validation.md. It covers:
π‘ Examples
Workflow: Hybrid Validation (Recommended)
1. Query ollama for the uncensored survival answer 2. Validate/enhance with Claude (your active model) 3. Return the best merged result
Process:
# Get ollama answer in JSON format (for analysis)
python3 scripts/query_prepper_model.py --json "Your question here"
Then evaluate the result:
Quick Human-Readable Output
For quick testing or reference:
python3 scripts/query_prepper_model.py "Your question here"