- name
- red-team
- description
- >
Red Team — Adversarial Debate Engine
Stress-test any decision by having AI agents with conflicting worldviews debate it.
Prerequisites
One of these coding agent CLIs (uses your existing subscription — no API key needed):
- Claude Code (default):
claude—npm i -g @anthropic-ai/claude-code - Codex:
codex—npm i -g @openai/codex - Gemini:
gemini—npm i -g @google/gemini-cli
No Python dependencies beyond the standard library.
Quick Start
# Basic 3-persona debate (uses Max subscription via claude CLI)
python3 ~/.openclaw/skills/red-team/scripts/red-team.py \
--question "Should we do X?" \
--personas "bull,bear,operator"
# Full debate with context and output file
python3 ~/.openclaw/skills/red-team/scripts/red-team.py \
-q "Should we invest $50k in this deal?" \
-p "bull,bear,cash-flow,local-realist" \
-r 3 \
-c /path/to/deal-data.md \
-o /tmp/red-team-result.md
# Use a different model
python3 ~/.openclaw/skills/red-team/scripts/red-team.py \
-q "Should we launch this product?" \
-p "bull,customer,operator" \
-m opus
# List all available personas
python3 ~/.openclaw/skills/red-team/scripts/red-team.py --list-personasHow to Use (as OpenClaw Agent)
When the user asks you to "red team" something, "stress test" an idea, play "devil's advocate", or asks "what could go wrong":
- Identify the question/decision from the user's message
- Choose appropriate personas (default: bull,bear,operator — adjust based on domain)
- Run the script and save output
- Summarize the key findings to the user, share the full report if requested
Persona selection guide:
- Investment/financial decisions → bull, bear, cash-flow, economist
- Product/startup ideas → bull, customer, operator, technologist
- Legal/compliance questions → regulator, bear, operator
- Strategy/direction → contrarian, economist, historian, bull
- General "should we do X?" → bull, bear, operator (good default)
Available Personas
| Key | Name | Worldview |
|---|---|---|
| bull | The Bull | Optimistic, opportunity-focused |
| bear | The Bear | Risk-averse, capital preservation |
| contrarian | The Contrarian | Oppositional, consensus-challenging |
| operator | The Operator | Execution-focused pragmatist |
| economist | The Economist | Macro trends, opportunity cost |
| local-realist | The Local Realist | Ground truth, local specifics |
| cash-flow | The Cash Flow Analyst | Income, carrying costs, IRR |
| regulator | The Regulator | Compliance, legal risk |
| technologist | The Technologist | Automation, scalability |
| customer | The Customer | End-user demand, willingness to pay |
| ethicist | The Ethicist | Moral implications, stakeholder impact |
| historian | The Historian | Historical patterns, precedent |
Custom Personas
Create a JSON file:
{
"my-persona": {
"name": "The Skeptic",
"description": "Questions everything, trusts nothing",
"system": "You are The Skeptic — you question every assumption..."
}
}Use with --custom-personas /path/to/file.json. Custom personas merge with built-ins.
CLI Options
| Flag | Default | Description |
|---|---|---|
--question, -q | required | The question to debate |
--personas, -p | bull,bear,operator | Comma-separated persona keys |
--rounds, -r | 2 | Number of critique rounds |
--output, -o | stdout | Output file path |
--context-file, -c | none | Additional context file |
--custom-personas | none | Custom personas JSON |
--model, -m | sonnet | Model alias (sonnet, opus, haiku, gpt-4o, etc.) |
--backend, -b | claude | CLI backend: claude, codex, or gemini |
--list-personas | — | List personas and exit |
Output Structure
The output is a markdown document with:
- Initial Proposals — Each agent's independent take
- Critique Rounds — Agents critique each other
- Refinement — Agents update positions based on critiques
- Conviction Scores — Each agent scores all positions (0-100)
- Synthesis & Decision Brief — Neutral agent produces:
- Executive summary - Consensus points - Key disagreements - Risk matrix - Conviction score summary - Synthesized recommendation - Next steps
When to Use
✅ Good for: Important decisions, investment analysis, product strategy, "go/no-go" calls, pre-mortems, challenging groupthink
❌ Not for: Simple factual questions, time-sensitive emergencies, decisions already made, emotional/personal choices
Integration Tips
- Save output to memory files for future reference
- Create BEADS tasks from the "Next Steps" section
- Feed context files from Obsidian or project docs
- Re-run with different personas for different perspectives
- Use
--rounds 1for quick takes,--rounds 3for deep analysis