Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· Developer Tools
Red Team
Adversarial multi-agent debate engine for stress-testing decisions, ideas, and strategies. Orchestrates multiple AI agents with conflicting worldviews (bull,...
skill openclawclawhub Free
Adversarial multi-agent debate engine for stress-testing decisions, ideas, and strategies. Orchestrates multiple AI agents with conflicting worldviews (bull,...
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- README.md, SKILL.md, references/personas.md, scripts/red-team.py
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- retrodigio
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Red Team β 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 β no API key needed): Claude Code (default): claude β npm i -g @anthropic-ai/claude-code Codex: codex β npm i -g @openai/codex Gemini: gemini β 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-personas
How 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 β 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 β bull, bear, cash-flow, economist Product/startup ideas β bull, customer, operator, technologist Legal/compliance questions β regulator, bear, operator Strategy/direction β contrarian, economist, historian, bull General "should we do X?" β bull, bear, operator (good default)
Available Personas
KeyNameWorldviewbullThe BullOptimistic, opportunity-focusedbearThe BearRisk-averse, capital preservationcontrarianThe ContrarianOppositional, consensus-challengingoperatorThe OperatorExecution-focused pragmatisteconomistThe EconomistMacro trends, opportunity costlocal-realistThe Local RealistGround truth, local specificscash-flowThe Cash Flow AnalystIncome, carrying costs, IRRregulatorThe RegulatorCompliance, legal risktechnologistThe TechnologistAutomation, scalabilitycustomerThe CustomerEnd-user demand, willingness to payethicistThe EthicistMoral implications, stakeholder impacthistorianThe HistorianHistorical patterns, precedent
Custom Personas
Create a JSON file: { "my-persona": { "name": "The Skeptic", "description": "Questions everything, trusts nothing", "system": "You are The Skeptic β you question every assumption..." } } Use with --custom-personas /path/to/file.json. Custom personas merge with built-ins.
CLI Options
FlagDefaultDescription--question, -qrequiredThe question to debate--personas, -pbull,bear,operatorComma-separated persona keys--rounds, -r2Number of critique rounds--output, -ostdoutOutput file path--context-file, -cnoneAdditional context file--custom-personasnoneCustom personas JSON--model, -msonnetModel alias (sonnet, opus, haiku, gpt-4o, etc.)--backend, -bclaudeCLI backend: claude, codex, or gemini--list-personasβList personas and exit
Output Structure
The output is a markdown document with: Initial Proposals β Each agent's independent take Critique Rounds β Agents critique each other Refinement β Agents update positions based on critiques Conviction Scores β Each agent scores all positions (0-100) Synthesis & Decision Brief β Neutral agent produces: Executive summary Consensus points Key disagreements Risk matrix Conviction score summary Synthesized recommendation Next steps
When to Use
β Good for: Important decisions, investment analysis, product strategy, "go/no-go" calls, pre-mortems, challenging groupthink β 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 1 for quick takes, --rounds 3 for deep analysis
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
3 Docs1 Scripts
- SKILL.md
- README.md
- references/personas.md
- scripts/red-team.py