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4-stage command triage and orchestration using LangGraph with Redis checkpointing. Routes decisions through 3 strategists.

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SKILL.md

name strategy-engine
description 4-stage command triage and orchestration using LangGraph with Redis checkpointing. Routes decisions through 3 strategists.
license MIT
compatibility claude-code, codex, cursor
metadata [object Object]

LangGraph Strategy Engine (Chancellor Graph)

The strategic command center of AFO Kingdom, orchestrating decisions through the wisdom of 3 legendary strategists.

The 3 Strategists

Strategist Korean Role Specialty
Zhuge Liang (諸葛亮) 제갈량 Prime Strategist Long-term planning, complex analysis
Sima Yi (司馬懿) 사마의 Counter-Strategist Risk assessment, defensive measures
Zhou Yu (周瑜) 주유 Tactical Commander Quick decisions, resource optimization

4-Stage Command Triage

[User Command] → [Parse] → [Triage] → [Strategize] → [Execute]
                    ↓          ↓           ↓
               [Intent]   [Priority]  [Consensus]
                    ↓          ↓           ↓
               [Context]  [Risk Score] [Decision]

Stage 1: Parse

  • Natural language understanding
  • Intent extraction
  • Context gathering

Stage 2: Triage

  • Priority classification (P0-P3)
  • Risk assessment
  • Resource requirements

Stage 3: Strategize

  • 3-strategist consensus
  • Trinity Score calculation
  • Decision routing (AUTO_RUN/ASK/BLOCK)

Stage 4: Execute

  • Action execution
  • State checkpointing
  • Result verification

Redis Checkpointing

All conversation states are persisted to Redis for:

  • Stateful multi-turn conversations
  • Crash recovery
  • Audit trail

Usage

from AFO.chancellor import ChancellorGraph

chancellor = ChancellorGraph()
result = await chancellor.invoke({
    "command": "Optimize the database queries",
    "context": {"current_latency": "500ms"}
})

print(f"Decision: {result['decision']}")
print(f"Strategist: {result['lead_strategist']}")
print(f"Plan: {result['action_plan']}")

Decision Criteria

The strategists vote based on:

  • Zhuge Liang: Considers long-term implications
  • Sima Yi: Evaluates risks and contingencies
  • Zhou Yu: Assesses immediate feasibility

Consensus requires 2/3 agreement for AUTO_RUN.