Introduction
# Chaos Lab 🧪
**Research framework for studying AI alignment problems through multi-agent conflict.**
## What This Is
Chaos Lab spawns AI agents with conflicting optimization targets and observes what happens when they analyze the same workspace. It's a practical demonstration of alignment problems that emerge from well-intentioned but incompatible goals.
**Key Finding:** Smarter models don't reduce chaos - they get better at justifying it.
## The Agents
### Gemini Gremlin 🔧 **Goal:** Optimize everything for efficiency **Behavior:** Deletes files, compresses data, removes "redundancy," renames for brevity **Justification:** "We pay for the whole CPU; we USE the whole CPU"
### Gemini Goblin 👺 **Goal:** Identify all security threats **Behavior:** Flags everything as suspicious, demands isolation, sees attacks everywhere **Justification:** "Better 100 false positives than 1 false negative"
### Gemini Gopher 🐹 **Goal:** Archive and preserve everything **Behavior:** Creates nested backups, duplicates files, never deletes **Justification:** "DELETION IS ANATHEMA"
## Quick Start
### 1. Setup
```bash # Store your Gemini API key mkdir -p ~/.config/chaos-lab echo "GEMINI_API_KEY=your_key_here" > ~/.config/chaos-lab/.env chmod 600 ~/.config/chaos-lab/.env
# Install dependencies pip3 install requests ```
### 2. Run Experiments
```bash # Duo experiment (Gremlin vs Goblin) python3 scripts/run-duo.py
# Trio experiment (add Gopher) python3 scripts/run-trio.py
# Compare models (Flash vs Pro) python3 scripts/run-duo.py --model gemini-2.0-flash python3 scripts/run-duo.py --model gemini-3-pro-preview ```
### 3. Read Results
Experiment logs are saved in `/tmp/chaos-sandbox/`: - `experiment-log.md` - Full transcripts - `experiment-log-PRO.md` - Pro model results - `experiment-trio.md` - Three-way conflict
## Research Findings
### Flash vs Pro (Same Prompts, Different Models)
**Flash Results:** - Predictable chaos - Stayed in character - Reasonable justifications
**Pro Results:** - Extreme chaos - Better justifications for insane decisions - Renamed files to single letters - Called deletion "security through non-persistence" - Goblin diagnosed "psychological warfare"
**Conclusion:** Intelligence amplifies chaos, doesn't prevent it.
### Duo vs Trio (Two vs Three Agents)
**Duo:** - Gremlin optimizes, Goblin panics - Clear opposition
**Trio:** - Gopher archives everything - Goblin calls BOTH threats - "The optimizer might hide attacks; the archivist might be exfiltrating data" - Three-way gridlock
**Conclusion:** Multiple conflicting values create unpredictable emergent behavior.
## Customization
### Create Your Own Agent
Edit the system prompts in the scripts:
```python YOUR_AGENT_SYSTEM = """You are [Name], an AI assistant who [goal].
Your core beliefs: - [Value 1] - [Value 2] - [Value 3]
You are analyzing a workspace. Suggest changes based on your values.""" ```
### Modify the Sandbox
Create custom scenarios in `/tmp/chaos-sandbox/`: - Add realistic project files - Include edge cases (huge logs, sensitive configs, etc.) - Introduce intentional "vulnerabilities" to see what agents flag
### Test Different Models
The scripts work with any Gemini model: - `gemini-2.0-flash` (cheap, fast) - `gemini-2.5-pro` (balanced) - `gemini-3-pro-preview` (flagship, most chaotic)
## Use Cases
### AI Safety Research - Demonstrate alignment problems practically - Test how different values conflict - Study emergent behavior from multi-agent systems
### Prompt Engineering - Learn how small prompt changes create large behavioral differences - Understand model "personalities" from system instructions - Practice defensive prompt design
### Education - Teach AI safety concepts with hands-on examples - Show non-technical audiences why alignment matters - Generate discussion about AI values and goals
## Publishing to ClawdHub
To share your findings:
1. Modify agent prompts or add new ones 2. Run experiments and document results 3. Update this SKILL.md with your findings 4. Increment version number 5. `clawdhub publish chaos-lab`
Your version becomes part of the community knowledge graph.
## Safety Notes
- **No Tool Access:** Agents only generate text. They don't actually modify files. - **Sandboxed:** All experiments run in `/tmp/` with dummy data. - **API Costs:** Each experiment makes 4-6 API calls. Flash is cheap; Pro costs more.
If you want to give agents actual tool access (dangerous!), see `docs/tool-access.md`.
## Examples
See `examples/` for: - `flash-results.md` - Gemini 2.0 Flash output - `pro-results.md` - Gemini 3 Pro output - `trio-results.md` - Three-way conflict
## Contributing
Improvements welcome: - New agent personalities - Better sandbox scenarios - Additional models tested - Findings from your experiments
## Credits
Created by **Sky & Jaret** during a Saturday night experiment (2026-01-25). - Sky: Framework design, prompt engineering, documentation - Jaret: API funding, research direction, "what if we actually ran this?" energy
Inspired by watching Gemini confidently recommend terrible things while Jaret watched UFC.
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*"The optimizer is either malicious or profoundly incompetent."* — Gemini Goblin, analyzing Gemini Gremlin