Multi-Scenario Orchestration

Design patterns for showcasing one skill across 3 parallel scenarios with synchronized execution and progressive difficulty.

Core Pattern

┌─────────────────────────────────────────────────────────────────────┐
│                   MULTI-SCENARIO ORCHESTRATOR                        │
├─────────────────────────────────────────────────────────────────────┤
│                                                                     │
│  [Coordinator] ──┬─→ [Scenario 1: Simple]       (Easy)            │
│       ▲          │      └─→ [Skill Instance 1]                    │
│       │          ├─→ [Scenario 2: Medium]       (Intermediate)    │
│       │          │      └─→ [Skill Instance 2]                    │
│       │          └─→ [Scenario 3: Complex]      (Advanced)        │
│       │                 └─→ [Skill Instance 3]                    │
│       │                                                             │
│   [State Manager] ◄──── All instances report progress              │
│   [Aggregator] ─→ Cross-scenario synthesis                         │
│                                                                     │
└─────────────────────────────────────────────────────────────────────┘

When to Use

Scenario	Example
Skill demos	Show /implement on simple, medium, complex tasks
Progressive testing	Validate skill scales with complexity
Comparative analysis	How does approach differ by difficulty?
Training/tutorials	Show skill progression from easy to hard

Quick Start

from langgraph.graph import StateGraph

# 1. Define 3 scenarios with progressive difficulty
scenarios = [
    {"name": "simple", "complexity": 1.0, "input_size": 10},
    {"name": "medium", "complexity": 3.0, "input_size": 50},
    {"name": "complex", "complexity": 8.0, "input_size": 200},
]

# 2. Fan out to parallel execution
# 3. Aggregate results
# 4. Report comparative metrics

Scenario Difficulty Scaling

Level	Complexity	Input Size	Time Budget	Quality
Simple	1x	Small (10)	30s	Basic
Medium	3x	Medium (50)	90s	Good
Complex	8x	Large (200)	300s	Excellent

Synchronization Modes

Mode	Description	Use When
Free-running	All run independently	Demo videos
Milestone-sync	Wait at 30%, 70%, 100%	Comparative analysis
Lock-step	All proceed together	Training

Key Components

1. Coordinator - Spawns and monitors 3 instances
2. State Manager - Tracks progress per scenario
3. Aggregator - Merges results, extracts patterns

Key Decisions

Decision	Recommendation
Synchronization mode	Free-running with checkpoints
Scenario count	Always 3: simple, medium, complex
Input scaling	1x, 3x, 8x (exponential)
Time budgets	30s, 90s, 300s
Checkpoint frequency	Every milestone + completion

Common Mistakes

• Sequential instead of parallel: Defeats purpose. Always fan-out.
• No synchronization: Results appear disjointed.
• Unclear difficulty scaling: Differ in scale, not approach.
• Missing aggregation: Individual results lack comparative insights.

Related Skills

• langgraph-supervisor - Supervisor routing pattern
• langgraph-parallel - Fan-out/fan-in execution
• langgraph-state - State management
• langgraph-checkpoints - Persistence
• multi-agent-orchestration - Coordination patterns

References

• Architectural Patterns - Full architecture
• State Machine Design - LangGraph state
• LangGraph Implementation - Code examples
• Claude Code Instance Management - Multi-instance
• Skill-Agnostic Template - Reusable template