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Council Advice

council-advice

Multi-model AI council for actionable project advice. Leverages Gemini 3 Flash and GPT-5.2 skills in parallel, then synthesizes through an Opus Judge for stage-appropriate, non-overkill recommendations. Use when seeking architectural guidance, code review synthesis, or implementation planning.

SKILL.md

Full skill instructions

Council Advice

A multi-model advisory council that provides actionable, stage-appropriate recommendations by combining perspectives from multiple AI models and filtering through rigorous evaluation rubrics.

Architecture Overview

                    ┌─────────────────────────────────────────────────────────────┐
                    │                    COUNCIL ADVICE FLOW                       │
                    └─────────────────────────────────────────────────────────────┘

                                         User Request
                                              │
                                              ▼
                    ┌─────────────────────────────────────────────────────────────┐
                    │                 PHASE 1: COUNCIL CONSULTATION                │
                    │                      (Parallel Execution)                    │
                    └─────────────────────────────────────────────────────────────┘
                                              │
                         ┌────────────────────┼────────────────────┐
                         │                    │                    │
                         ▼                    ▼                    ▼
                ┌─────────────────┐  ┌─────────────────┐  ┌─────────────────┐
                │ GEMINI ADVISOR  │  │ GPT-5.2 ADVISOR │  │ CONTEXT LOADER  │
                │ (Gemini 3 Flash)│  │                 │  │                 │
                │ gemini_analyze  │  │ gpt52_analyze   │  │ Read project    │
                │ gemini_query    │  │ gpt52_query     │  │ files & stage   │
                └────────┬────────┘  └────────┬────────┘  └────────┬────────┘
                         │                    │                    │
                         └────────────────────┼────────────────────┘
                                              │
                                              ▼
                    ┌─────────────────────────────────────────────────────────────┐
                    │                 PHASE 2: OPUS JUDGE DELIBERATION             │
                    │                   (Claude Opus 4.5 via API)                  │
                    └─────────────────────────────────────────────────────────────┘
                                              │
                                              ▼
                         ┌─────────────────────────────────────────┐
                         │            EVALUATION RUBRICS           │
                         │                                         │
                         │  • Stage Relevancy (MVP/​PoC/​Prod)       │
                         │  • Overkill Detection                   │
                         │  • Over-complexity Assessment           │
                         │  • Over-engineering Detection           │
                         │  • Implementation Feasibility           │
                         │  • Project Purpose Alignment            │
                         └─────────────────────────────────────────┘
                                              │
                                              ▼
                    ┌─────────────────────────────────────────────────────────────┐
                    │                 PHASE 3: ACTIONABLE REPORT                   │
                    │                   (Implementation Plan)                      │
                    └─────────────────────────────────────────────────────────────┘

How to Use

When the user asks for council advice on any topic:

  1. Clarify the request context if not provided:

    • Project stage: MVP, PoC, Production, Maintenance
    • Purpose: What problem is being solved?
    • Constraints: Time, resources, technical limitations
  2. Execute Phase 1: Call council members in parallel

  3. Execute Phase 2: Run the Opus Judge script

  4. Present Phase 3: Deliver the actionable report

Phase 1: Council Consultation

Execute these advisor consultations in parallel for maximum efficiency:

Gemini 3 Flash Advisor

Use the querying-gemini skill scripts for intelligent analysis:

For code/​architecture analysis:

python .claude/​skills/​querying-gemini/​scripts/​gemini_analyze.py \
  --target "$TARGET_PATH" \
  --focus-areas "architecture,quality,security,performance" \
  --analysis-type comprehensive \
  --output-format json

For general guidance queries:

python .claude/​skills/​querying-gemini/​scripts/​gemini_query.py \
  --prompt "You are the Gemini Advisor on a multi-model council. Analyze the following request and provide your expert recommendations.

REQUEST: $USER_REQUEST

CONTEXT:
- Project Stage: $STAGE
- Project Purpose: $PURPOSE
- Technical Stack: $TECH_STACK

Provide:
1. Your assessment of the situation
2. Specific recommendations (prioritized)
3. Potential risks or concerns
4. Alternative approaches if applicable

Be thorough but practical. Focus on actionable insights." \
  --thinking-level high \
  --output-format json

Gemini 3 Flash Advantages:

  • 1M token context window (analyze very large codebases)
  • Pro-level intelligence at Flash speed
  • Configurable thinking levels (minimal/​low/​medium/​high)
  • Cost-effective: $0.50/​1M input, $3/​1M output

GPT-5.2 Advisor

Use the querying-gpt52 skill scripts for high-reasoning analysis:

For code analysis:

python .claude/​skills/​querying-gpt52/​scripts/​gpt52_analyze.py \
  --target "$TARGET_PATH" \
  --focus-areas "architecture,quality,security,performance" \
  --analysis-type comprehensive \
  --output-format json

For high-reasoning queries:

python .claude/​skills/​querying-gpt52/​scripts/​gpt52_query.py \
  --prompt "You are the GPT-5.2 Advisor on a multi-model council. Provide high-reasoning analysis for the following request.

REQUEST: $USER_REQUEST

CONTEXT:
- Project Stage: $STAGE
- Project Purpose: $PURPOSE
- Technical Stack: $TECH_STACK

Analyze with focus on:
1. Root-cause understanding of the problem
2. Architecture-level recommendations
3. Code quality implications
4. Security and performance considerations
5. Testing and maintainability impact

Provide depth and rigor in your analysis." \
  --reasoning-effort high \
  --output-format json

GPT-5.2 Advantages:

  • 400K token context window
  • 128K token max output (comprehensive responses)
  • Extended reasoning with xhigh level
  • Aug 2025 knowledge cutoff

Context Loader

Simultaneously read relevant project files to understand:

  • Current implementation state
  • Project structure
  • Existing patterns and conventions

Phase 2: Opus Judge Deliberation

After receiving council responses, execute the Opus Judge script:

python .claude/​skills/​council-advice/​scripts/​opus_judge.py \
  --gemini-response "$GEMINI_RESPONSE" \
  --codex-response "$GPT52_RESPONSE" \
  --project-stage "$PROJECT_STAGE" \
  --project-purpose "$PROJECT_PURPOSE" \
  --request "$ORIGINAL_REQUEST"

Note: Both advisor scripts must use --output-format json so the Opus Judge can properly parse the responses.

The Opus Judge:

  1. Receives multi-model reviews
  2. Weights recommendations against project context
  3. Applies evaluation rubrics (see RUBRICS.md)
  4. Decides what to embrace and what to disregard
  5. Produces a synthesized, actionable report

Opus Judge Evaluation Criteria

For each recommendation, the judge evaluates:

CriterionAccept IfReject If
Stage RelevancyMatches current stage needsPremature optimization for stage
Overkill DetectionProportional to problemSolution exceeds problem scope
ComplexityAppropriate for team/​projectUnnecessarily complex
EngineeringSolves actual needBuilds for hypothetical futures
FeasibilityAchievable with current resourcesRequires unrealistic effort
Purpose AlignmentAdvances project goalsTangential to core mission

Phase 3: Actionable Report

The final output follows this structure for seamless conversion to implementation:

# Council Advice Report

## Executive Summary
[2-3 sentences on the key recommendation]

## Project Context
- **Stage**: {stage}
- **Purpose**: {purpose}
- **Request**: {original_request}

## Recommendations

### Embraced (Implement These)

#### 1. [Recommendation Title]
- **Source**: Gemini/​GPT-5.2/​Both
- **Priority**: P0/​P1/​P2
- **Rationale**: Why this was embraced
- **Implementation Steps**:
  1. Step one
  2. Step two
  3. Step three
- **Estimated Effort**: [time estimate]

### Deferred (Not Now, Maybe Later)

#### 1. [Recommendation Title]
- **Source**: Gemini/​GPT-5.2/​Both
- **Reason for Deferral**: [Stage mismatch/​Overkill/​etc.]
- **Revisit When**: [Condition for reconsidering]

### Rejected (Do Not Implement)

#### 1. [Recommendation Title]
- **Source**: Gemini/​GPT-5.2/​Both
- **Rejection Reason**: [Over-engineered/​Out of scope/​etc.]

## Implementation Plan

### Immediate Actions (This Session)
- [ ] Action 1
- [ ] Action 2

### Short-term Actions (This Sprint)
- [ ] Action 1
- [ ] Action 2

### Future Considerations
- [ ] Consideration 1
- [ ] Consideration 2

## Council Notes
[Any areas of agreement/​disagreement between advisors]

Best Practices

Parallel Execution

Always execute both advisor scripts in parallel for maximum efficiency. Use Bash tool with run_in_background: true for both scripts, then collect results.

Example parallel execution:

# Run both advisors in background
python .claude/​skills/​querying-gemini/​scripts/​gemini_query.py --prompt "..." --output-format json &
python .claude/​skills/​querying-gpt52/​scripts/​gpt52_query.py --prompt "..." --output-format json &
wait

Stage-Appropriate Advice

StagePrioritizeAvoid
MVPSpeed, validation, core featuresOptimization, scalability, edge cases
PoCProving concept, minimal viableProduction concerns, polish
ProductionReliability, security, performanceTechnical debt shortcuts
MaintenanceStability, documentationMajor rewrites

When to Use This Skill

  • Seeking architectural guidance
  • Planning feature implementation
  • Code review synthesis
  • Evaluating technical approaches
  • Making technology decisions
  • Refactoring strategy

When NOT to Use This Skill

  • Simple, straightforward tasks
  • Emergency bug fixes (use direct tools)
  • Documentation-only requests
  • One-line code changes

Model Comparison

FeatureGemini 3 FlashGPT-5.2
Context Window1,000,000 tokens400,000 tokens
Max Output64,000 tokens128,000 tokens
SpeedFasterSlower
Thinking Levelsminimal/​low/​medium/​highnone/​low/​medium/​high/​xhigh
Best ForLarge codebases, speed-criticalDeep reasoning, comprehensive output
API KeyGEMINI_API_KEYOPENAI_API_KEY

Troubleshooting

Gemini Scripts Not Found

Ensure the querying-gemini skill is installed:

ls -la .claude/​skills/​querying-gemini/​scripts/

Expected files:

  • gemini_query.py
  • gemini_analyze.py
  • gemini_code.py
  • gemini_fix.py

GPT-5.2 Scripts Not Found

Ensure the querying-gpt52 skill is installed:

ls -la .claude/​skills/​querying-gpt52/​scripts/

Expected files:

  • gpt52_query.py
  • gpt52_analyze.py
  • gpt52_fix.py

Opus Judge Script Fails

Check:

  1. ANTHROPIC_API_KEY is set
  2. Required packages installed (anthropic>=0.50.0)
  3. Script has execute permissions

API Key Issues

Ensure the following environment variables are set:

# For Gemini 3 Flash
export GEMINI_API_KEY=your-gemini-api-key
# or
export GOOGLE_API_KEY=your-google-api-key

# For GPT-5.2
export OPENAI_API_KEY=your-openai-api-key

# For Opus Judge
export ANTHROPIC_API_KEY=your-anthropic-api-key

Slow Response

  • Council consultation runs in parallel (~30-60s for GPT-5.2, ~10-30s for Gemini 3 Flash)
  • Opus Judge adds ~30-60s
  • Total expected time: 1-2 minutes for comprehensive advice

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