miknas-council-of-wisdom（米克纳斯智慧委员会）

Council of Wisdom - AI Debate System

Description: A sophisticated multi-agent debate framework where two expert agents debate opposing viewpoints, managed by a referee, with 9 specialized council members voting on the most compelling argument. Includes automatic cleanup, multi-LLM provider support, and enterprise-grade monitoring, testing, and scalability.

When to Use This Skill

Use Council of Wisdom when you need:

• Comprehensive analysis from multiple expert perspectives
• Balanced debate on complex topics with opposing viewpoints
• Decision-making with structured voting and reasoning
• Multi-provider AI evaluation (different LLMs per agent)
• Automatic agent lifecycle management (spawn → debate → vote → cleanup)
• Enterprise-grade monitoring, testing, feedback loops

Common use cases:

• Strategic decision analysis
• Technical architecture debates
• Product feature prioritization
• Risk assessment and mitigation planning
• Investment or business opportunity evaluation
• Policy or process design decisions

Architecture Overview

┌─────────────────────────────────────────────────────────────┐
│                     QUERY / ADVISE / TROUBLE                 │
└───────────────────────────┬─────────────────────────────────┘
                            │
                            ▼
┌─────────────────────────────────────────────────────────────┐
│                    REFEREE AGENT                            │
│  • Receives query                                           │
│  • Orchestrates debate                                      │
│  • Manages council voting                                   │
│  • Delivers structured outcome                              │
└─────────────┬───────────────────────┬───────────────────────┘
              │                       │
              ▼                       ▼
┌─────────────────────────┐  ┌─────────────────────────┐
│    MASTER DEBATER A     │  │    MASTER DEBATER B     │
│  • Domain expert #1     │  │  • Domain expert #2     │
│  • Persuasive arguments │  │  • Persuasive arguments │
│  • Opposing viewpoint   │  │  • Opposing viewpoint   │
└─────────────────────────┘  └─────────────────────────┘
              │                       │
              └───────────┬───────────┘
                          │
                          ▼
┌─────────────────────────────────────────────────────────────┐
│              COUNCIL OF 9 EXPERTS                            │
│  • Each is a non-human domain expert                        │
│  • Unique perspective & methodology                        │
│  • Vote on most convincing argument                         │
│  • Provide brief reasoning                                  │
└───────────────────────────┬─────────────────────────────────┘
                            │
                            ▼
┌─────────────────────────────────────────────────────────────┐
│                 REFEREE AGGREGATION                         │
│  • Collects votes (9 total)                                 │
│  • Tally and determine winner                               │
│  • Structure outcome report                                 │
│  • Delete council agents & context                          │
└───────────────────────────┬─────────────────────────────────┘
                            │
                            ▼
┌─────────────────────────────────────────────────────────────┐
│              STRUCTURED OUTCOME REPORT                       │
│  • Winner declaration                                        │
│  • Vote tally                                                │
│  • Key arguments from each side                              │
│  • Council consensus insights                                │
│  • Actionable recommendations                                │
└─────────────────────────────────────────────────────────────┘

Council of 9 - Expert Specializations

Each council member represents a distinct analytical framework:

1. Logician - Formal logic, fallacy detection, deductive reasoning
2. Empiricist - Evidence-based, data-driven, statistical analysis
3. Pragmatist - Real-world applicability, practical outcomes
4. Ethicist - Moral frameworks, stakeholder impact, fairness
5. Futurist - Long-term implications, trend analysis, scenarios
6. Historian - Precedent analysis, historical patterns, lessons
7. Systems Thinker - Holistic view, interconnected effects
8. Risk Analyst - Failure modes, mitigation, uncertainty
9. Synthesizer - Integration, common ground, hybrid solutions

Core Components

1. Workspace Setup

Each Council of Wisdom instance has its own workspace:

council-of-wisdom init <project-name>

Creates:

council-of-wisdom/<project-name>/
├── workspace/
│   ├── strategy.md           # Project-specific strategy
│   ├── monitoring/
│   │   ├── metrics.md        # Key metrics definitions
│   │   ├── cadence.md        # Review cadences (daily/weekly/etc)
│   │   └── dashboard.json    # Metrics dashboard config
│   ├── testing/
│   │   ├── test-cases.md     # Test scenarios
│   │   └── quality-checks.md # Quality criteria
│   ├── feedback/
│   │   ├── feedback-log.md   # User feedback capture
│   │   └── improvement-queue.md
│   ├── prompts/
│   │   ├── referee.md        # Referee agent prompt
│   │   ├── debater-a.md      # Debater A prompt template
│   │   ├── debater-b.md      # Debater B prompt template
│   │   └── council/          # 9 council member prompts
│   │       ├── logician.md
│   │       ├── empiricist.md
│   │       └── ... (all 9)
│   ├── agents/
│   │   ├── referee.json      # Referee agent config
│   │   ├── debater-a.json    # Debater A config
│   │   ├── debater-b.json    # Debater B config
│   │   └── council.json      # Council member configs
│   ├── logs/                 # Debate transcripts, votes
│   └── reports/              # Final outcome reports
├── .github/                  # GitHub repo integration
└── README.md                 # Project documentation

2. GitHub Repository Integration

Every Council of Wisdom project has its own private GitHub repo:

# Auto-created during init
git remote add origin git@github.com:<username>/council-<project-name>.git
git branch -M main
git push -u origin main

Features:

• Private repository (enforced)
• Automated issue tracking for debates
• Wiki for knowledge base
• Actions for automated testing
• Releases for versioned outcomes

3. Multi-LLM Provider Support

Council members can use different LLM providers randomly:

# Enable multi-provider mode
council-of-wisdom config set multi-provider true

# Define available providers
council-of-wisdom config add-provider openai gpt-4
council-of-wisdom config add-provider anthropic claude-3-opus
council-of-wisdom config add-provider google gemini-pro

Each council member randomly receives a different provider for each debate, ensuring diverse reasoning patterns.

4. Agent Lifecycle Management

Spawn → Debate → Vote → Cleanup

# Full debate cycle
council-of-wisdom debate <topic> \
  --domain <domain> \
  --perspective-a "<perspective A>" \
  --perspective-b "<perspective B>"

Automatic cleanup:

• Council agents terminated after voting
• Context cleared (memory wiped)
• Logs archived to workspace
• Ready for next query in seconds

5. Strategy Framework

Every Council of Wisdom project has a strategy.md with:

Required fields:

• Council Purpose: What decisions this council makes
• Domain Expertise: Areas of specialization
• Decision Criteria: How to evaluate arguments
• Stakeholders: Who uses the decisions
• Success Metrics: What good looks like

Template: templates/strategy-template.md

6. Monitoring & Metrics

5-Cadence Operating Rhythm:

Key Metrics Dashboard:

{
  "debate_metrics": {
    "total_debates": 0,
    "avg_debate_time": 0,
    "vote_distribution": {},
    "argument_quality_score": 0
  },
  "agent_metrics": {
    "council_diversity_index": 0,
    "provider_rotation_efficiency": 0,
    "context_cleanup_success_rate": 0
  },
  "outcome_metrics": {
    "decision_adoption_rate": 0,
    "outcome_validity": 0,
    "stakeholder_satisfaction": 0
  }
}

7. Testing Framework

Test Categories:

1. Unit Tests - Individual agent prompts

   council-of-wisdom test unit --agent logician

1. Integration Tests - Full debate flow

   council-of-wisdom test integration --scenario "complex-decision"

1. Quality Checks - Argument quality, logic depth

   council-of-wisdom test quality --topic <topic>

1. Performance Tests - Speed, resource usage

   council-of-wisdom test performance --load 10

Test Scenarios: See templates/test-scenarios.md

8. Feedback & Optimization Loop

Feedback Capture:

# Add user feedback
council-of-wisdom feedback add \
  --debate-id <id> \
  --rating 1-5 \
  --comment "<feedback>"

# View improvement queue
council-of-wisdom feedback queue

Automated Optimization:

# Run optimization cycle
council-of-wisdom optimize \
  --analyze last-7-days \
  --update-prompts \
  --tune-providers

Optimization Targets:

• Prompt engineering improvements
• Provider selection optimization
• Council composition tuning
• Argument depth maximization
• Decision accuracy enhancement

9. Scalability Features

Horizontal Scaling:

• Multiple concurrent debates (up to N instances)
• Distributed council member allocation
• Load balancing across providers

Vertical Scaling:

• Council expansion (9 → 12 → 15 members)
• Domain specialization layers
• Nested debates (sub-councils for sub-issues)

Enterprise Features:

• Rate limiting and quota management
• Priority queues for urgent decisions
• Audit trails and compliance logging
• Multi-tenant support

Usage

Initialize a New Council

council-of-wisdom init strategic-decisions

Conduct a Debate

council-of-wisdom debate \
  "Should we invest in AI automation or human expertise for customer support?" \
  --domain "customer-support" \
  --perspective-a "AI automation prioritizes efficiency and scalability" \
  --perspective-b "Human expertise prioritizes empathy and complex problem-solving"

View Outcome Report

council-of-wisdom report <debate-id>

Run Daily Health Check

council-of-wisdom health-check

Run Optimization Cycle

council-of-wisdom optimize --period weekly

Examples

Example 1: Technical Architecture Decision

council-of-wisdom debate \
  "Should we use microservices or monolithic architecture for our new product?" \
  --domain "software-architecture" \
  --perspective-a "Microservices offer scalability, independent deployment, and team autonomy" \
  --perspective-b "Monolithic architecture offers simplicity, lower operational overhead, and faster initial development"

Outcome Report Structure:

# Debate Outcome Report

## Winner: Monolithic Architecture (6/9 votes)

## Vote Tally
- **Monolithic Architecture:** 6 votes (Logician, Empiricist, Pragmatist, Systems Thinker, Risk Analyst, Synthesizer)
- **Microservices:** 3 votes (Futurist, Ethicist, Historian)

## Key Arguments - Monolithic
1. **Development Velocity:** 3-5x faster initial time-to-market
2. **Operational Complexity:** 80% lower infrastructure overhead
3. **Team Coordination:** Reduced communication overhead by 60%

## Key Arguments - Microservices
1. **Future Scalability:** Better suited for 10x+ growth scenarios
2. **Technology Diversity:** Enables polyglot persistence and best-tool selection
3. **Fault Isolation:** Service failures don't cascade across entire system

## Council Insights
- **Consensus:** For a new product with uncertain market fit, monolithic architecture is strategically superior
- **Caveat:** If product validates and scales beyond 1M users, consider gradual migration to microservices
- **Risk Mitigation:** Design monolithic with modular boundaries to ease future migration

## Recommendation
**Adopt Monolithic Architecture for V1 with Modular Design**

### Action Plan
1. Build monolithic with clear module boundaries
2. Implement feature flags for gradual rollout
3. Monitor performance and architecture fit metrics
4. Re-evaluate architecture decision after 6 months or 500K users

Example 2: Marketing Strategy Debate

council-of-wisdom debate \
  "Should we focus on SEO-driven content marketing or paid advertising for customer acquisition?" \
  --domain "marketing" \
  --perspective-a "SEO content builds sustainable, compounding organic traffic and authority" \
  --perspective-b "Paid ads provide immediate, scalable, and predictable customer acquisition"

Advanced Features

Custom Council Composition

Override default council with custom experts:

council-of-wisdom config set-council \
  --members "industry-expert,financial-analyst,legal-counsel,product-strategist,customer-advocate,technical-lead,operations-manager,brand-architect,growth-hacker"

Nested Debates

For complex decisions, run sub-debates:

council-of-wisdom debate --nested \
  --main-topic "Should we enter the enterprise market?" \
  --sub-topic-1 "Pricing strategy" \
  --sub-topic-2 "Feature requirements" \
  --sub-topic-3 "Support infrastructure"

Weighted Voting

Assign different weights to council members:

council-of-wisdom config set-weights \
  --councilmember logician:2 \
  --councilmember empiricist:2 \
  --councilmember others:1

Debate Replay & Analysis

# Reconstruct and analyze past debates
council-of-wisdom replay <debate-id> --analyze

# Extract patterns across debates
council-of-wisdom analyze-patterns --period last-30-days

Monitoring Dashboards

Real-Time Monitoring

council-of-wisdom monitor --live

Shows:

• Active debates
• Agent status
• Provider health
• Queue depth

Historical Analysis

council-of-wisdom analytics --period quarterly

Generates:

• Decision trend analysis
• Argument quality evolution
• Provider performance comparison
• Council member effectiveness

Integration Points

GitHub Integration

# Create issue for debate
council-of-wisdom debate --create-issue

# Push outcome report to repo
council-of-wisdom report <id> --push

# Sync with GitHub wiki
council-of-wisdom sync-wiki

API Access (for automation)

# Start a debate via API
curl -X POST https://api.council-of-wisdom.com/v1/debates \
  -H "Authorization: Bearer <token>" \
  -d '{"topic": "...", "domain": "..."}'

# Get outcome
curl https://api.council-of-wisdom.com/v1/debates/<id>/outcome

Webhooks

Configure webhooks for:

• Debate completion
• Vote finalization
• Outcome report generation
• Optimization alerts

Troubleshooting

Agent Stuck During Debate

Symptom: Debate not progressing beyond initial arguments

Solutions:

1. Check provider status: council-of-wisdom status providers
2. Review agent logs: council-of-wisdom logs <agent-id>
3. Restart debate: council-of-wisdom debate --restart <debate-id>

Council Vote Deadlock (4-4 tie with 1 abstain)

Symptom: No clear winner

Resolution:

1. Automatic tiebreaker: Referee casts deciding vote
2. Extended debate: Add 2 rounds of rebuttal
3. Both perspectives documented as "equally valid with tradeoffs"

Context Cleanup Failure

Symptom: Council agents not terminating

Solutions:

1. Force cleanup: council-of-wisdom cleanup --force
2. Check process status: council-of-wisdom status agents
3. Review logs: council-of-wisdom logs cleanup

Poor Argument Quality

Symptom: Arguments are shallow or generic

Optimization:

# Run quality analysis
council-of-wisdom analyze-quality <debate-id>

# Auto-optimize prompts
council-of-wisdom optimize --focus prompt-engineering

# Test new prompts
council-of-wisdom test prompts --scenario quality-test

Best Practices

1. Define strategy first: Always have a clear strategy.md before debating
2. Iterate on prompts: Regularly optimize based on feedback
3. Monitor metrics: Review metrics at each cadence
4. Capture feedback: Always collect user feedback on outcomes
5. Archive outcomes: Store all reports in GitHub for traceability
6. Rotate providers: Use multi-provider to avoid bias
7. Regular cleanup: Ensure context cleanup is working
8. Version control: Commit all prompt changes to git
9. Test before deploy: Run integration tests for new prompts
10. Scale gradually: Start with 9 council, expand only when needed

Template Files

Reference Materials

*Council of Wisdom: Structured debate, collective intelligence, actionable decisions.*