War Room

Overview

The War Room convenes multiple AI experts to analyze problems from diverse perspectives, challenge assumptions through adversarial review, and synthesize optimal approaches under the guidance of a Supreme Commander.

Philosophy

"The trick is that there is no trick. The power of intelligence stems from our vast diversity, not from any single, perfect principle."

• Marvin Minsky, Society of Mind

Reversibility-Based Routing

Before deliberation, assess the Reversibility Score (RS) to determine appropriate resource allocation:

RS = (Reversal Cost + Time Lock-In + Blast Radius + Information Loss + Reputation Impact) / 25

Quick Heuristics:

• Can be A/B tested? → Type 2
• Requires data migration? → Type 1
• Public commitment required? → Type 1A+

See modules/reversibility-assessment.md for full scoring guide.

When To Use

• Architectural decisions with major trade-offs
• Multi-stakeholder problems requiring diverse perspectives
• High-stakes choices with significant consequences (RS > 0.60)
• Novel problems without clear precedent
• When brainstorming produces multiple strong competing approaches

When NOT To Use

• Simple questions with obvious answers
• Routine implementation tasks
• Well-documented patterns with clear solutions
• Time-critical decisions requiring immediate action
• Type 2 decisions (RS ≤ 0.40): use Express mode or skip War Room entirely

Expert Panel

Default (Lightweight Mode)

Full Council (Escalated)

Deliberation Protocol

Two-Round Default

Round 1: Generation
  - Phase 1: Intelligence Gathering (Scout, Intel Officer)
  - Phase 2: Situation Assessment (Chief Strategist)
  - Phase 3: COA Development (Multiple experts, parallel)
  - Commander Escalation Check

Round 2: Pressure Testing
  - Phase 4: Red Team Review (all COAs)
  - Phase 5: Voting + Narrowing (top 2-3)
  - Phase 6: Premortem Analysis (selected COA)
  - Phase 7: Supreme Commander Synthesis
  - Phase 8: Discussion Publishing

Delphi Extension (High-Stakes)

For high-stakes decisions, extend to iterative Delphi convergence:

• Multiple rounds until expert consensus
• Convergence threshold: 0.85

Integration

With Brainstorm

War Room is AUTOMATICALLY INVOKED from Skill(attune:project-brainstorming) after Phase 3 (Approach Generation).

The brainstorm skill passes all context to War Room:

• Problem statement and constraints
• Generated approaches with pros/cons
• Comparison matrix
• Reversibility assessment (automatically calculated)

Bypass conditions (only if ALL true):

• RS ≤ 0.40 (Type 2 decision - clearly reversible)
• Single obvious approach with no meaningful trade-offs
• Low complexity with well-documented pattern
• User explicitly declines after seeing RS assessment

# Automatic invocation from brainstorm (do not skip)
/attune:war-room --from-brainstorm

# Direct invocation (standalone)
/attune:war-room "Should we use microservices or monolith for this system?"

With Memory Palace

Sessions persist to the Strategeion (War Palace):

~/.claude/memory-palace/strategeion/
  - war-table/      # Active sessions
  - campaign-archive/  # Historical decisions
  - doctrine/       # Learned patterns
  - armory/         # Expert configurations

With Conjure

Experts are invoked via conjure delegation:

• conjure:gemini-delegation for Gemini models
• conjure:qwen-delegation for Qwen models
• Direct CLI for GLM-5.3 (ccgd or claude-glm, via get_glm_command())

Delegation being on by default changes nothing here, because a War Room delegates by construction: a panel is external models or it is not a panel.

What does change is the fallback. conjure:delegation-core now returns a fallback_reason instead of raising when no provider answers or when an operator has declined delegation, and Claude answering every seat is the wrong way to spend that result.

A panel that could not reach external models is not a panel. When delegation is off or the chain is exhausted:

1. Say so before deliberating, naming the reason and the providers tried.
2. Do not fill the empty seats with Claude and present the output as a multi-model panel. Seven roles played by one model produce agreement that looks like consensus and is not.
3. Offer the choice: run a single-model review labeled as one, or stop until a provider is available.

This is the one place in the repository where a silent local fallback would misrepresent the result rather than merely slow it down.

Usage

Basic Invocation

/attune:war-room "What architecture should we use for the new payment system?"

With Context

/attune:war-room "Best approach for API versioning" --files src/api/**/*.py

Reversibility Assessment Only

Quick assessment without full deliberation:

/attune:war-room "Database migration to MongoDB" --assess-only

Output:

Reversibility Assessment
========================
Decision: Database migration to MongoDB

Dimensions:
  Reversal Cost:      5/5 (months of rework)
  Time Lock-In:       4/5 (migration path hardens)
  Blast Radius:       5/5 (all services affected)
  Information Loss:   4/5 (query patterns, ACID)
  Reputation Impact:  2/5 (internal unless downtime)

Reversibility Score: 0.80
Decision Type: Type 1A (One-Way Door)
Recommended Mode: Full Council

Proceed with full deliberation? [Y/n]

Force Express Mode (Type 2)

Skip to rapid decision for clearly reversible choices:

/attune:war-room "Which logging library to use" --express

Force Full Council

Override RS assessment for critical decisions:

/attune:war-room "Migration strategy" --full-council

Delphi Mode

For highest-stakes irreversible decisions:

/attune:war-room "Long-term platform decision" --delphi

Resume Session

/attune:war-room --resume war-room-20260120-153022

Output

Decision Document

The War Room produces a Supreme Commander Decision document:

## SUPREME COMMANDER DECISION: {session_id}

### Reversibility Assessment
| Dimension | Score | Rationale |
|-----------|-------|-----------|
| Reversal Cost | X/5 | ... |
| Time Lock-In | X/5 | ... |
| Blast Radius | X/5 | ... |
| Information Loss | X/5 | ... |
| Reputation Impact | X/5 | ... |

**RS: 0.XX | Type: [1A+/1A/1B/2] | Mode: [delphi/full_council/lightweight/express]**

### Decision
**Selected Approach**: [Name]

### Rationale
[Why this approach was selected]

### Implementation Orders
1. [ ] Immediate actions
2. [ ] Short-term actions

### Watch Points
[From Premortem - what to monitor]

### Reversal Plan (for Type 1 decisions)
[If this decision proves wrong, here's the exit strategy]

### Dissenting Views
[For the record]

Session Artifacts

Saved to Strategeion:

• Intelligence reports
• Situation assessment
• All COAs (with full attribution after unsealing)
• Red Team challenges
• Premortem analysis
• Final decision

Record the Tradeoff (decision journal)

The Supreme Commander Decision is a tradeoff record by construction: a selected approach, the COAs weighed against it, and the dissenting views. Mirror it into docs/tradeoffs.md so the reasoning stays with the code, not only in Strategeion (draft and confirm):

• If leyline is installed, invoke Skill(leyline:decision-journal) and append a tradeoff entry. Map directly: Selected Approach to decision, the RS and rationale to a Y-statement, the rejected COAs to options, and Dissenting Views to consequences_negative. Set phase to the originating phase (for example plan). Record the RS in the entry links. Append on confirmation.
• Fallback (leyline absent): append to docs/tradeoffs.md using the in-file ENTRY TEMPLATE; assign the next TR-NNN id.

If the decision is architectural enough to warrant a numbered ADR in docs/adr/, write the ADR and reference its number from the tradeoff entry rather than duplicating it.

Anonymization

Expert contributions are anonymized during deliberation using Merkle-DAG:

• Responses labeled as "Response A, B, C..." during review
• Attribution revealed only after decision is made
• Hash verification ensures integrity

See modules/merkle-dag.md for details.

Escalation

Automatic (Reversibility-Based)

Deliberation mode is automatically selected based on Reversibility Score:

Manual Override

The Supreme Commander may override automatic classification when:

• High complexity detected (multiple architectural trade-offs)
• Significant disagreement between initial experts
• Novel problem domain requiring specialized analysis
• Precedent-setting decision (future decisions will follow pattern)
• Political/organizational sensitivity beyond technical scope

Escalation requires written justification with RS assessment.

De-escalation

Equally important: identify decisions being over-deliberated:

• If RS ≤ 0.40, recommend Express mode or immediate execution
• Challenge "false irreversibility" ("we can't change this later" without evidence)
• Track de-escalation rate as team health metric

Configuration

User Settings

{
  "war_room": {
    "default_mode": "lightweight",
    "auto_escalate": true,
    "delphi_threshold": 0.85,
    "max_delphi_rounds": 5
  }
}

Hook Auto-Trigger

War Room can be auto-suggested via hook when:

• Keywords detected ("strategic decision", "trade-off", etc.)
• Complexity score exceeds threshold (0.7)
• User has opted in via settings

Agent Teams Execution Mode