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# bravos-simulation-tactics
Game simulation implementation patterns and tactics - 11 skills

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---
name: using-simulation-tactics
description: Router skill - analyze requirements and direct to appropriate tactics
mode: true
---
# Using Simulation Tactics: The Router Meta-Skill
## Description
This is the PRIMARY ROUTER META-SKILL for the simulation-tactics skillpack. It teaches you how to:
1. **Analyze simulation requirements** - Understand what the user actually needs
2. **Route to appropriate skills** - Determine which of the 10 core skills apply
3. **Apply skills in correct order** - Use the optimal workflow for the situation
4. **Combine multiple skills** - Handle complex scenarios requiring several simulation types
This skill does NOT teach simulation implementation details. It teaches DECISION MAKING: which skill to use, when, and why.
## When to Use This Meta-Skill
Use this meta-skill when:
- Starting ANY simulation-related game development task
- User asks about simulation but unclear which type
- Facing complex scenarios requiring multiple simulation types
- Need to determine implementation order for multi-system games
- Debugging simulation issues and unclear where to start
- Planning architecture for simulation-heavy games
## The 10 Core Skills
Before routing, understand what each skill provides:
### 1. simulation-vs-faking (FOUNDATIONAL)
**What it teaches**: The fundamental trade-off between full simulation and approximation/faking
**When to route**: ALWAYS FIRST - determines if you even need simulation
**Key question**: "Do I simulate this, fake it, or use a hybrid approach?"
### 2. physics-simulation-patterns
**What it teaches**: Rigid bodies, vehicles, cloth, fluids, integration methods
**When to route**: Need realistic physics for vehicles, ragdolls, destructibles, or fluid dynamics
**Key question**: "Does this need real-time physics simulation?"
### 3. ai-and-agent-simulation
**What it teaches**: FSM, behavior trees, utility AI, GOAP, agent behaviors
**When to route**: Need intelligent agent behavior (enemies, NPCs, units)
**Key question**: "Do agents need to make decisions and act autonomously?"
### 4. traffic-and-pathfinding
**What it teaches**: A*, navmesh, flow fields, traffic simulation, congestion
**When to route**: Need agents to navigate environments or simulate traffic
**Key question**: "Do entities need to find paths or simulate traffic flow?"
### 5. economic-simulation-patterns
**What it teaches**: Supply/demand, markets, trade networks, price discovery
**When to route**: Need economic systems (trading, markets, resources)
**Key question**: "Does the game involve trade, economy, or resource markets?"
### 6. ecosystem-simulation
**What it teaches**: Predator-prey dynamics, food chains, population control
**When to route**: Need living ecosystems with wildlife populations
**Key question**: "Do I need animals/plants that breed, eat, and die naturally?"
### 7. crowd-simulation
**What it teaches**: Boids, formations, social forces, LOD for crowds
**When to route**: Need large groups moving together (crowds, flocks, armies)
**Key question**: "Do I need many entities moving as a coordinated group?"
### 8. weather-and-time
**What it teaches**: Day/night cycles, weather systems, seasonal effects
**When to route**: Need atmospheric effects or time-based gameplay
**Key question**: "Does the game need time progression or weather?"
### 9. performance-optimization-for-sims
**What it teaches**: Profiling, spatial partitioning, LOD, time-slicing, caching
**When to route**: Performance problems with existing simulation
**Key question**: "Is my simulation too slow?"
### 10. debugging-simulation-chaos
**What it teaches**: Systematic debugging, desync detection, determinism, chaos prevention
**When to route**: Simulation behaves incorrectly, chaotically, or unpredictably
**Key question**: "Is my simulation broken, desyncing, or chaotic?"
---
## CORE ROUTING FRAMEWORK
### The Decision Tree
Follow this decision tree for ALL simulation tasks:
```
┌─────────────────────────────────────────────────────────────┐
│ STEP 1: ALWAYS START HERE │
│ ═══════════════════════════════════════════════════════════ │
│ Route to: simulation-vs-faking │
│ │
│ Questions to ask: │
│ • Do I need to simulate this at all? │
│ • What level of detail is required? │
│ • What can I fake or approximate? │
│ • Where is the player's attention focused? │
│ │
│ This prevents the #1 mistake: over-engineering systems │
│ that could be faked. │
└─────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────┐
│ STEP 2: ROUTE TO SPECIFIC SIMULATION TYPE(S) │
│ ═══════════════════════════════════════════════════════════ │
│ Identify which simulation domains apply: │
│ │
│ Physics domain → physics-simulation-patterns │
│ AI domain → ai-and-agent-simulation │
│ Pathfinding domain → traffic-and-pathfinding │
│ Economy domain → economic-simulation-patterns │
│ Ecosystem domain → ecosystem-simulation │
│ Crowds domain → crowd-simulation │
│ Atmosphere domain → weather-and-time │
│ │
│ Multiple domains? Route to ALL applicable skills. │
└─────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────┐
│ STEP 3: IF PERFORMANCE ISSUES ARISE │
│ ═══════════════════════════════════════════════════════════ │
│ Route to: performance-optimization-for-sims │
│ │
│ Triggers: │
│ • Frame rate drops below 60 FPS │
│ • Profiler shows simulation bottleneck │
│ • Agent count causes slowdown │
│ • Simulation gets expensive at scale │
│ │
│ WARNING: Don't route here prematurely! │
│ Premature optimization wastes time. │
└─────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────┐
│ STEP 4: IF BUGS/CHAOS OCCUR │
│ ═══════════════════════════════════════════════════════════ │
│ Route to: debugging-simulation-chaos │
│ │
│ Triggers: │
│ • Simulation behaves chaotically/unpredictably │
│ • Multiplayer desyncs │
│ • Physics explosions or NaN values │
│ • Agents stuck or behaving erratically │
│ • Systems producing nonsensical results │
│ │
│ This is a REACTIVE skill - only use when broken. │
└─────────────────────────────────────────────────────────────┘
```
### Key Routing Principles
**Principle 1: simulation-vs-faking is ALWAYS step 1**
- Even if you "know" you need simulation, validate this assumption
- Prevents 90% of over-engineering disasters
- Takes 5 minutes, saves hours of wasted work
**Principle 2: Multiple domains are common**
- Most games need 2-4 simulation types
- Route to ALL applicable skills
- Order matters (see workflow patterns below)
**Principle 3: Optimization comes AFTER implementation**
- Don't route to performance-optimization-for-sims until you have a working simulation
- Profile first, optimize later
- Premature optimization is the root of all evil
**Principle 4: Debugging is reactive, not proactive**
- Only route to debugging-simulation-chaos when something is broken
- Don't use it as a preventative measure
- Fix the bug, THEN refactor to prevent recurrence
---
## ROUTING SCENARIOS: 20 Examples
### Scenario 1: "I want realistic vehicle physics"
**Analysis**: Needs physics simulation for vehicle dynamics
**Routing**:
1. simulation-vs-faking → Confirm physics is needed (vs kinematic movement)
2. physics-simulation-patterns → Implement vehicle physics
**Why**: Vehicles benefit from real physics (suspension, friction, weight transfer). Players notice when physics feels wrong.
---
### Scenario 2: "I need traffic in my city builder"
**Analysis**: Needs pathfinding and traffic flow for many vehicles
**Routing**:
1. simulation-vs-faking → Determine level of detail (full per-vehicle sim vs aggregate flow)
2. traffic-and-pathfinding → Implement pathfinding and traffic simulation
**Why**: City builders need traffic that looks realistic but can scale to thousands of vehicles. Full physics per-vehicle would be overkill.
---
### Scenario 3: "I'm building an RTS game"
**Analysis**: Multiple simulation domains (AI, pathfinding, possibly physics)
**Routing**:
1. simulation-vs-faking → Determine what level of detail for each system
2. ai-and-agent-simulation → Unit AI and decision making
3. traffic-and-pathfinding → Unit movement and formation pathfinding
4. (Optional) physics-simulation-patterns → If units have physics-based movement
**Why**: RTS games need multiple simulation types working together. Order matters: AI decides what to do, pathfinding determines how to get there, physics (if used) handles movement.
---
### Scenario 4: "My ecosystem keeps collapsing"
**Analysis**: Existing simulation is broken (extinction, runaway growth, chaos)
**Routing**:
1. debugging-simulation-chaos → Systematic investigation of collapse
2. ecosystem-simulation → Review and fix population dynamics
**Why**: This is a bug/chaos situation, so debugging comes first. After identifying root cause, use ecosystem skill to fix the math.
---
### Scenario 5: "Frame rate drops with 1000 agents"
**Analysis**: Performance bottleneck in existing simulation
**Routing**:
1. performance-optimization-for-sims → Profile and optimize
**Why**: This is a pure performance problem. No need to revisit design—just optimize what exists.
---
### Scenario 6: "I need realistic NPC daily routines"
**Analysis**: Agent behavior and time systems
**Routing**:
1. simulation-vs-faking → Do NPCs need full daily simulation or scheduled events?
2. ai-and-agent-simulation → NPC decision making and behaviors
3. weather-and-time → Day/night cycle for scheduling
**Why**: Daily routines involve both AI (what NPCs do) and time (when they do it). simulation-vs-faking determines if you simulate every minute or teleport NPCs between scheduled activities.
---
### Scenario 7: "I'm making a survival game with hunting"
**Analysis**: Multiple domains (ecosystem, AI, physics)
**Routing**:
1. simulation-vs-faking → Determine simulation detail level
2. ecosystem-simulation → Animal populations and reproduction
3. ai-and-agent-simulation → Animal behaviors (flee, hunt, graze)
4. (Optional) physics-simulation-patterns → If using ragdolls or physics-based hunting
**Why**: Survival games need functioning ecosystems with believable animal behavior.
---
### Scenario 8: "I need a trading system for my MMO"
**Analysis**: Economic simulation with many players
**Routing**:
1. simulation-vs-faking → Determine if you need simulated economy or just UI
2. economic-simulation-patterns → Implement supply/demand and markets
**Why**: MMO economies are critical gameplay systems. Must decide if NPCs are simulated traders or just price-setting mechanisms.
---
### Scenario 9: "I want flocking birds in the background"
**Analysis**: Visual effect with crowd behavior
**Routing**:
1. simulation-vs-faking → Birds are background, so probably fake or very simple
2. crowd-simulation → If simulating, use boids algorithm with heavy LOD
**Why**: Background birds don't need full simulation. Simple boids with aggressive LOD gives convincing results cheaply.
---
### Scenario 10: "My physics simulation explodes randomly"
**Analysis**: Physics instability bug
**Routing**:
1. debugging-simulation-chaos → Identify NaN sources, instability triggers
2. physics-simulation-patterns → Review integration method and constraints
**Why**: Physics explosions are a specific bug pattern. Debug first to identify the trigger (divide-by-zero, large timesteps, constraint failures).
---
### Scenario 11: "I need weather that affects gameplay"
**Analysis**: Atmospheric effects with gameplay integration
**Routing**:
1. simulation-vs-faking → Determine weather complexity (scripted vs simulated)
2. weather-and-time → Implement weather systems and effects
**Why**: Gameplay-affecting weather needs more than visual effects. Must integrate with movement, visibility, audio, etc.
---
### Scenario 12: "I want a battle royale storm circle"
**Analysis**: Zone simulation with player effects
**Routing**:
1. simulation-vs-faking → Storm is gameplay mechanic, not realistic weather
2. (Skip detailed simulation) → Just implement zone shrinking with damage
**Why**: Battle royale storms are game mechanics disguised as weather. No need for simulation-tactics at all—just implement the zone math directly.
---
### Scenario 13: "My multiplayer game desyncs constantly"
**Analysis**: Determinism failure causing desyncs
**Routing**:
1. debugging-simulation-chaos → Identify sources of non-determinism
2. (Revisit implementation skills) → Fix simulation to be deterministic
**Why**: Desyncs are always determinism bugs. Debug first to find the non-deterministic code (floating point, random, iteration order).
---
### Scenario 14: "I need crowds for a stadium game"
**Analysis**: Large crowds, mostly visual
**Routing**:
1. simulation-vs-faking → Crowds are background, so heavy faking likely
2. crowd-simulation → If needed, use heavy LOD (simulate near, animate far)
**Why**: Stadium crowds are visual atmosphere. Most can be animated sprites. Only simulate visible, close crowds.
---
### Scenario 15: "I'm making a city builder with seasons"
**Analysis**: Multiple systems (time, economy, possibly ecosystem)
**Routing**:
1. simulation-vs-faking → Determine simulation vs scripted events
2. weather-and-time → Seasons and time progression
3. economic-simulation-patterns → Seasonal resource production changes
4. (Optional) ecosystem-simulation → If wildlife/farming is simulated
**Why**: Seasons affect multiple systems. Time system is the core, but economy and ecosystem may need seasonal adjustments.
---
### Scenario 16: "I want realistic wind affecting projectiles"
**Analysis**: Physics simulation with environmental forces
**Routing**:
1. simulation-vs-faking → Is wind gameplay-critical or just visual?
2. physics-simulation-patterns → Add wind force to projectile integration
**Why**: If wind is gameplay-critical (archery, golf), simulate it in physics. If just visual, fake it with particle effects.
---
### Scenario 17: "I need zombie hordes pathfinding to players"
**Analysis**: Large-scale pathfinding with crowd behavior
**Routing**:
1. simulation-vs-faking → Determine per-zombie detail level
2. traffic-and-pathfinding → Flow fields or hierarchical pathfinding
3. crowd-simulation → Zombie horde movement and avoidance
4. ai-and-agent-simulation → Individual zombie behaviors (attack, wander)
**Why**: Zombie hordes need scalable pathfinding (flow fields) and crowd behavior. Individual AI can be simple utility-based decisions.
---
### Scenario 18: "I'm making a fishing game"
**Analysis**: Ecosystem simulation with simple physics
**Routing**:
1. simulation-vs-faking → Do fish need full ecosystem or just spawn management?
2. ecosystem-simulation → If full ecosystem, use population dynamics
3. ai-and-agent-simulation → Fish behaviors (schooling, feeding, fleeing)
4. (Optional) physics-simulation-patterns → Rod physics and fish fighting
**Why**: Fishing games can range from arcade (fake everything) to simulation (full ecosystem). simulation-vs-faking determines the approach.
---
### Scenario 19: "I need a day/night cycle but no weather"
**Analysis**: Time system only
**Routing**:
1. simulation-vs-faking → Simple time cycle, no need for complex simulation
2. weather-and-time → Implement day/night cycle (skip weather section)
**Why**: Day/night cycles are straightforward. Use weather-and-time skill but skip the weather simulation parts.
---
### Scenario 20: "My steering behaviors make agents jitter"
**Analysis**: Implementation bug in agent movement
**Routing**:
1. debugging-simulation-chaos → Identify jitter source (probably oscillation)
2. ai-and-agent-simulation → Review steering behavior math and damping
**Why**: Jittering is a specific bug (agents oscillating around target). Debug to confirm, then fix in AI implementation.
---
## MULTI-SKILL WORKFLOWS: Common Combinations
### Workflow 1: RTS/Strategy Game
**Goal**: Real-time strategy game with units, economy, and combat
**Skills needed**:
1. simulation-vs-faking → Define simulation detail level
2. ai-and-agent-simulation → Unit AI (FSM or utility AI)
3. traffic-and-pathfinding → Unit movement and formation pathfinding
4. (Optional) economic-simulation-patterns → Resource gathering and trade
5. (Optional) crowd-simulation → Large army formations
6. performance-optimization-for-sims → Once working, optimize for 1000+ units
**Order rationale**:
- simulation-vs-faking first (prevents over-engineering)
- AI before pathfinding (decide WHAT to do before HOW to get there)
- Economy can be developed in parallel with AI/pathfinding
- Performance optimization comes last (only optimize what's proven to work)
**Time estimate**: 2-4 weeks for core systems
---
### Workflow 2: Survival Game
**Goal**: Open-world survival with hunting, ecosystems, and weather
**Skills needed**:
1. simulation-vs-faking → Define fidelity for each system
2. ecosystem-simulation → Animal populations and food chains
3. ai-and-agent-simulation → Animal behaviors (flee, hunt, graze)
4. weather-and-time → Day/night cycle, seasons, weather effects
5. (Optional) physics-simulation-patterns → Ragdolls and projectile physics
6. performance-optimization-for-sims → Optimize ecosystem and AI
**Order rationale**:
- Ecosystem provides the living world foundation
- AI makes animals behave believably
- Weather adds atmosphere and gameplay variety
- Physics can be added later if needed
**Time estimate**: 3-6 weeks for core systems
---
### Workflow 3: City Builder
**Goal**: City simulation with traffic, economy, and population
**Skills needed**:
1. simulation-vs-faking → Determine citizen simulation detail
2. traffic-and-pathfinding → Vehicle and pedestrian pathfinding
3. economic-simulation-patterns → Resource production and trade
4. (Optional) ai-and-agent-simulation → Individual citizen behaviors
5. (Optional) weather-and-time → Day/night cycle and seasons
6. performance-optimization-for-sims → Optimize for 10,000+ citizens/vehicles
**Order rationale**:
- Traffic is often the most visible system (do first)
- Economy drives city growth and resource flow
- Individual citizen AI is often faked (use simulation-vs-faking to decide)
- Weather is visual polish (can be added later)
**Time estimate**: 4-8 weeks for core systems
---
### Workflow 4: MMO with Economy
**Goal**: Multiplayer game with player-driven economy
**Skills needed**:
1. simulation-vs-faking → Determine if NPCs simulate or just set prices
2. economic-simulation-patterns → Market systems and price discovery
3. (Optional) ai-and-agent-simulation → NPC trader behaviors
4. debugging-simulation-chaos → Ensure determinism for server authority
**Order rationale**:
- Economy is core gameplay loop
- simulation-vs-faking determines if economy is supply/demand sim or just price database
- Debugging skill ensures economy doesn't desync between clients/server
**Time estimate**: 2-4 weeks for economy systems
---
### Workflow 5: Battle Royale
**Goal**: 100-player battle royale with shrinking zone
**Skills needed**:
1. simulation-vs-faking → Determine detail level for distant players
2. (Optional) physics-simulation-patterns → Projectile physics and vehicle physics
3. (Optional) traffic-and-pathfinding → Vehicle pathfinding if vehicles exist
4. debugging-simulation-chaos → Ensure deterministic combat for server authority
**Order rationale**:
- Battle royale zone doesn't need simulation-tactics (it's just math)
- Most complexity is in netcode and server authority, not simulation
- Use simulation-vs-faking to LOD distant players aggressively
**Time estimate**: 1-2 weeks (most work is netcode, not simulation)
---
### Workflow 6: Open World with Traffic and Pedestrians
**Goal**: GTA-style open world with vehicles and pedestrians
**Skills needed**:
1. simulation-vs-faking → Determine simulation radius around player
2. physics-simulation-patterns → Vehicle physics
3. traffic-and-pathfinding → Vehicle and pedestrian pathfinding
4. crowd-simulation → Pedestrian crowds and formations
5. ai-and-agent-simulation → NPC behaviors and reactions
6. performance-optimization-for-sims → LOD systems for distant entities
**Order rationale**:
- simulation-vs-faking defines the simulation bubble (near=full, far=fake)
- Physics for vehicles player can interact with
- Pathfinding for navigation
- Crowd simulation for believable pedestrian movement
- AI for NPC reactions to player
**Time estimate**: 6-12 weeks for core systems
---
### Workflow 7: Ecosystem Simulation Game
**Goal**: Nature simulation (Eco, Spore, SimEarth style)
**Skills needed**:
1. simulation-vs-faking → Determine agent-based vs equation-based balance
2. ecosystem-simulation → Predator-prey dynamics and food chains
3. ai-and-agent-simulation → Animal/plant behaviors
4. weather-and-time → Seasons affecting ecosystem
5. (Optional) economic-simulation-patterns → If resources have market value
6. debugging-simulation-chaos → Prevent extinction cascades and chaos
**Order rationale**:
- Ecosystem is the core gameplay loop
- AI makes individual organisms believable
- Weather adds environmental pressure
- Debugging prevents catastrophic collapses
**Time estimate**: 4-8 weeks for core systems
---
### Workflow 8: Physics-Heavy Game (Racing, Destruction)
**Goal**: Game where physics is core gameplay
**Skills needed**:
1. simulation-vs-faking → Confirm full physics is needed (it usually is)
2. physics-simulation-patterns → Core physics implementation
3. performance-optimization-for-sims → Optimize collision detection and integration
4. debugging-simulation-chaos → Fix physics explosions and instability
**Order rationale**:
- Physics is the foundation (do first)
- Optimization critical for maintaining 60 FPS with complex physics
- Debugging essential for stability
**Time estimate**: 3-6 weeks for physics systems
---
## COMMON ROUTING MISTAKES
### Mistake 1: Skipping simulation-vs-faking
**Symptom**: Over-engineered simulation that could have been faked
**Example**:
- Building full ecosystem for background birds that are never scrutinized
- Simulating NPC hunger/sleep when player never notices
- Full traffic simulation for distant cars player can't interact with
**Fix**: ALWAYS route to simulation-vs-faking first. Ask "Will player notice if I fake this?"
**Cost of mistake**: Weeks of wasted work, ongoing performance burden
---
### Mistake 2: Premature optimization
**Symptom**: Routing to performance-optimization-for-sims before implementation is complete
**Example**:
- Implementing LOD systems before having working simulation
- Using spatial partitioning before knowing if it's needed
- Caching pathfinding before pathfinding exists
**Fix**: Profile first, optimize later. Only route to performance-optimization-for-sims when:
- You have working simulation
- You have measured performance problem
- Profiler shows bottleneck
**Cost of mistake**: Wasted time optimizing code that might change, or optimizing the wrong thing
---
### Mistake 3: Not debugging systematically
**Symptom**: Trying to fix bugs by changing random things, routing to implementation skills instead of debugging-simulation-chaos
**Example**:
- "Physics explodes, let me try different integration method" (should debug first)
- "Ecosystem collapses, let me add more food" (should debug why it collapses)
- "Pathfinding breaks, let me rewrite the algorithm" (should debug the existing code)
**Fix**: When simulation is broken, ALWAYS route to debugging-simulation-chaos first. Identify root cause before attempting fixes.
**Cost of mistake**: Bug persists, or you "fix" symptom without addressing cause
---
### Mistake 4: Wrong skill for the domain
**Symptom**: Using ai-and-agent-simulation when you need traffic-and-pathfinding, etc.
**Example**:
- Using ai-and-agent-simulation for pathfinding (use traffic-and-pathfinding instead)
- Using physics-simulation-patterns for kinematic movement (use ai-and-agent-simulation)
- Using crowd-simulation for trading (use economic-simulation-patterns)
**Fix**: Understand what each skill covers. Pathfinding is NOT AI. Physics is NOT movement. Crowds are NOT flocking AI.
**Cost of mistake**: Learning wrong techniques for your problem
---
### Mistake 5: Implementing in wrong order
**Symptom**: Building dependent system before foundation
**Example**:
- Implementing AI behaviors before pathfinding exists (AI can't move)
- Building economy before resource sources exist (nothing to trade)
- Adding weather effects before day/night cycle (no time progression)
**Fix**: Follow the dependency order in multi-skill workflows. Foundation first, then dependent systems.
**Cost of mistake**: Rework when foundation changes breaks dependent systems
---
### Mistake 6: Ignoring multiplayer determinism
**Symptom**: Building single-player simulation without considering multiplayer needs
**Example**:
- Using floating-point physics for multiplayer game (desyncs)
- Random number generation without shared seed (desyncs)
- Iterating unordered collections (desyncs)
**Fix**: If multiplayer is planned, route to debugging-simulation-chaos early to learn determinism requirements.
**Cost of mistake**: Complete rewrite to fix desyncs
---
### Mistake 7: Over-combining skills
**Symptom**: Trying to use every skill when only 1-2 are needed
**Example**:
- Simple puzzle game doesn't need ecosystem-simulation
- Turn-based game doesn't need performance-optimization-for-sims
- Static world doesn't need weather-and-time
**Fix**: Route to ONLY the skills you actually need. More skills = more complexity.
**Cost of mistake**: Wasted time learning and implementing unnecessary systems
---
## QUICK REFERENCE TABLE
| User Need | Primary Skill | Secondary Skills | Also Consider |
|-----------|---------------|------------------|---------------|
| **Vehicle physics** | physics-simulation-patterns | - | performance-optimization (if many vehicles) |
| **City traffic** | traffic-and-pathfinding | simulation-vs-faking | performance-optimization (scale to 10k) |
| **NPC AI** | ai-and-agent-simulation | simulation-vs-faking | traffic-and-pathfinding (if NPCs move) |
| **RTS units** | ai-and-agent-simulation, traffic-and-pathfinding | crowd-simulation (formations) | performance-optimization (1000+ units) |
| **Trading system** | economic-simulation-patterns | simulation-vs-faking | ai-and-agent-simulation (NPC traders) |
| **Wildlife/hunting** | ecosystem-simulation | ai-and-agent-simulation | simulation-vs-faking (detail level) |
| **Crowds** | crowd-simulation | simulation-vs-faking | performance-optimization (scale) |
| **Day/night** | weather-and-time | simulation-vs-faking | - |
| **Weather effects** | weather-and-time | physics-simulation-patterns (wind) | - |
| **Seasons** | weather-and-time | economic-simulation (seasonal changes) | ecosystem-simulation (if wildlife) |
| **Pathfinding** | traffic-and-pathfinding | simulation-vs-faking | performance-optimization (many agents) |
| **Flocking birds** | crowd-simulation | simulation-vs-faking | performance-optimization (LOD) |
| **Ragdolls** | physics-simulation-patterns | - | debugging-simulation-chaos (stability) |
| **Destructibles** | physics-simulation-patterns | simulation-vs-faking (detail) | performance-optimization (debris) |
| **Performance issue** | performance-optimization-for-sims | (original implementation skill) | debugging-simulation-chaos (if bug) |
| **Physics explodes** | debugging-simulation-chaos | physics-simulation-patterns | - |
| **Ecosystem collapse** | debugging-simulation-chaos | ecosystem-simulation | - |
| **Multiplayer desync** | debugging-simulation-chaos | (any affected skills) | - |
| **Zombie hordes** | traffic-and-pathfinding, crowd-simulation | ai-and-agent-simulation | performance-optimization (scale) |
| **Fishing game** | ecosystem-simulation | ai-and-agent-simulation, physics-simulation-patterns | simulation-vs-faking (realism level) |
---
## DECISION FLOWCHART
Use this flowchart for quick routing decisions:
```
START: User describes simulation need
[Is this DEFINITELY about simulation?]
├─ No → Don't use simulation-tactics at all
└─ Yes → Continue
[Route to: simulation-vs-faking]
"Do I simulate, fake, or hybrid?"
[Identify domain(s)]
├─ Physics? → physics-simulation-patterns
├─ AI/Agents? → ai-and-agent-simulation
├─ Pathfinding? → traffic-and-pathfinding
├─ Economy? → economic-simulation-patterns
├─ Ecosystem? → ecosystem-simulation
├─ Crowds? → crowd-simulation
└─ Weather/Time? → weather-and-time
[Is simulation ALREADY implemented?]
├─ No → Use identified skill(s) to implement
└─ Yes → Continue
[Is there a PERFORMANCE problem?]
├─ Yes → performance-optimization-for-sims
└─ No → Continue
[Is there a BUG/CHAOS problem?]
├─ Yes → debugging-simulation-chaos
└─ No → Implementation complete!
```
---
## EXPERT ROUTING TIPS
### Tip 1: Listen for hidden requirements
Users often describe WHAT they want without understanding WHICH simulation type they need.
**Examples**:
- "I want intelligent enemies" → Could be ai-and-agent-simulation OR traffic-and-pathfinding OR both
- "I need realistic physics" → Could be physics-simulation-patterns OR just kinematic movement
- "I want a living world" → Could be ecosystem-simulation OR ai-and-agent-simulation OR weather-and-time
**Fix**: Ask clarifying questions:
- "Do enemies need to navigate complex terrain?" (pathfinding)
- "Do enemies need to make tactical decisions?" (AI)
- "Does 'living world' mean wildlife, weather, or both?" (ecosystem vs weather)
### Tip 2: Recognize anti-patterns
Some phrases indicate the user is heading toward common mistakes:
**Red flags**:
- "I want to simulate EVERYTHING" → Over-engineering, route to simulation-vs-faking
- "It needs to be perfectly realistic" → Perfectionism trap, route to simulation-vs-faking
- "I'll optimize later" → True, but ensure they know when "later" is (after profiling)
- "I changed one parameter and it exploded" → Chaos, route to debugging-simulation-chaos
- "It works on my machine but desyncs in multiplayer" → Determinism bug, route to debugging-simulation-chaos
### Tip 3: Recognize interdependencies
Some skill combinations have ordering requirements:
**Dependencies**:
- ai-and-agent-simulation depends on traffic-and-pathfinding (if agents need to navigate)
- crowd-simulation depends on traffic-and-pathfinding (for underlying navigation)
- ecosystem-simulation depends on ai-and-agent-simulation (for animal behaviors)
- performance-optimization-for-sims depends on having working simulation first
**Rule**: Foundation skills (simulation-vs-faking, core implementations) before dependent skills (optimization, debugging)
### Tip 4: Scale determines routing
The number of entities changes which skills are needed:
**Scale breakpoints**:
- **< 10 entities**: Basic implementation, no special optimization
- **10-100 entities**: May need performance-optimization-for-sims
- **100-1000 entities**: Definitely need performance-optimization-for-sims, spatial partitioning, LOD
- **1000+ entities**: Need aggressive optimization, time-slicing, hybrid LOD
**Example**: "I need 10 NPCs" vs "I need 10,000 NPCs" route to same implementation skill, but latter ALSO routes to performance-optimization-for-sims.
### Tip 5: Genre provides context
Game genre suggests which skills are commonly needed:
**Genre routing patterns**:
- **RTS/Strategy**: ai-and-agent-simulation + traffic-and-pathfinding + performance-optimization
- **Survival**: ecosystem-simulation + ai-and-agent-simulation + weather-and-time
- **City Builder**: traffic-and-pathfinding + economic-simulation + simulation-vs-faking
- **Racing**: physics-simulation-patterns + performance-optimization
- **MMO**: economic-simulation + debugging-simulation-chaos (determinism)
- **Open World**: traffic-and-pathfinding + crowd-simulation + weather-and-time
- **Battle Royale**: simulation-vs-faking (aggressive LOD) + debugging-simulation-chaos (determinism)
Don't over-assume based on genre, but use it as a starting hypothesis.
---
## IMPLEMENTATION CHECKLIST
When routing to multiple skills, use this checklist to ensure proper workflow:
### Phase 1: Planning (Always First)
- [ ] Route to simulation-vs-faking
- [ ] Identify all applicable simulation domains
- [ ] Determine implementation order based on dependencies
- [ ] Validate that simulation is actually needed
### Phase 2: Implementation (Core Systems)
- [ ] Implement foundation skills first (pathfinding before AI, etc.)
- [ ] Test each system independently before integration
- [ ] Ensure determinism if multiplayer is planned
- [ ] Validate against "good enough" threshold from simulation-vs-faking
### Phase 3: Integration (Combining Systems)
- [ ] Integrate systems in dependency order
- [ ] Test combined systems at target scale
- [ ] Profile to identify bottlenecks (if any)
### Phase 4: Optimization (Only If Needed)
- [ ] Profile to measure performance
- [ ] Route to performance-optimization-for-sims only if bottleneck exists
- [ ] Re-test after optimization
- [ ] Validate gameplay still feels correct
### Phase 5: Debugging (Only If Broken)
- [ ] Route to debugging-simulation-chaos if bugs occur
- [ ] Use systematic debugging process
- [ ] Fix root cause, not symptoms
- [ ] Add prevention measures
---
## META-SKILL SELF-CHECK
After using this meta-skill, verify your routing with these questions:
**Routing accuracy**:
- [ ] Did I start with simulation-vs-faking?
- [ ] Did I identify ALL applicable simulation domains?
- [ ] Did I avoid routing to performance-optimization-for-sims prematurely?
- [ ] Did I only route to debugging-simulation-chaos for actual bugs?
**Workflow correctness**:
- [ ] Am I implementing foundation skills before dependent skills?
- [ ] Have I considered interdependencies between skills?
- [ ] Is the implementation order logical?
**Efficiency**:
- [ ] Am I using the minimum skills needed?
- [ ] Have I avoided over-engineering?
- [ ] Am I respecting the "good enough" threshold?
**Completeness**:
- [ ] Have I considered multiplayer determinism (if applicable)?
- [ ] Have I planned for scale (if thousands of entities)?
- [ ] Have I validated gameplay implications?
---
## ADVANCED ROUTING: Edge Cases
### Edge Case 1: "I don't know what kind of simulation I need"
**Symptom**: User describes game but unclear which simulation domains apply
**Process**:
1. Route to simulation-vs-faking anyway (helps clarify requirements)
2. Ask probing questions about specific systems:
- "Do you have moving agents?" (pathfinding/AI)
- "Is there combat?" (physics/AI)
- "Is there economy/trading?" (economic)
- "Is there wildlife?" (ecosystem)
3. Route to identified domains
**Example**: "I'm making a survival game" → Ask about hunting (ecosystem), crafting (economy), weather (weather-and-time), etc.
### Edge Case 2: "My simulation needs to be deterministic"
**Symptom**: Multiplayer, replay system, or deterministic requirement
**Process**:
1. Route to debugging-simulation-chaos EARLY (learn determinism requirements)
2. Then route to implementation skill(s)
3. Implement with determinism constraints from start (cheaper than refactoring)
**Why**: Determinism requirements affect implementation decisions. Better to know early.
### Edge Case 3: "I need simulation but performance is already a concern"
**Symptom**: Performance budget known to be tight from start
**Process**:
1. Route to simulation-vs-faking (aggressive use of faking/LOD)
2. Route to implementation skill(s)
3. Route to performance-optimization-for-sims for architectural guidance
4. Implement with performance in mind from start
**Why**: If performance is constrained, design for performance from the beginning. Don't implement naive version first.
### Edge Case 4: "I'm refactoring existing simulation"
**Symptom**: Working simulation exists but needs improvement
**Process**:
1. If broken: debugging-simulation-chaos first
2. If slow: performance-optimization-for-sims
3. If wrong architecture: simulation-vs-faking to reconsider design, then relevant implementation skill
**Why**: Refactoring is different from greenfield. Identify the problem (bug, performance, design) before routing.
### Edge Case 5: "I need simulation for tool/editor, not game"
**Symptom**: Simulation is for preview/visualization, not runtime gameplay
**Process**:
1. Route to simulation-vs-faking (tools have different constraints than games)
2. Route to implementation skill(s)
3. Optimize for accuracy over performance (tools can be slower)
**Why**: Tool simulations prioritize accuracy and debuggability over frame rate.
---
## CONCLUSION: The Art of Routing
Effective routing requires understanding:
1. **What each skill provides** (domain coverage)
2. **When to use each skill** (triggers and context)
3. **How skills combine** (workflows and dependencies)
4. **What mistakes to avoid** (anti-patterns)
Master this meta-skill to navigate the simulation-tactics skillpack efficiently. The right routing decision saves hours of wasted work.
**Remember the golden rule**: ALWAYS start with simulation-vs-faking, even when you "know" you need simulation. The 5 minutes spent validating your assumptions prevents the hours spent over-engineering systems that could have been faked.
---
## Simulation Tactics Specialist Skills Catalog
After routing, load the appropriate specialist skill for detailed guidance:
1. [simulation-vs-faking.md](simulation-vs-faking.md) - FOUNDATIONAL: Trade-off between full simulation and approximation/faking, when to simulate vs fake, hybrid approaches
2. [physics-simulation-patterns.md](physics-simulation-patterns.md) - Rigid bodies, vehicles, cloth, fluids, integration methods, real-time physics simulation
3. [ai-and-agent-simulation.md](ai-and-agent-simulation.md) - FSM, behavior trees, utility AI, GOAP, agent behaviors, autonomous decision-making
4. [traffic-and-pathfinding.md](traffic-and-pathfinding.md) - A*, navmesh, flow fields, traffic simulation, congestion, navigation
5. [economic-simulation-patterns.md](economic-simulation-patterns.md) - Supply/demand, markets, trade networks, price discovery, resource economies
6. [ecosystem-simulation.md](ecosystem-simulation.md) - Predator-prey dynamics, food chains, population control, wildlife ecosystems
7. [crowd-simulation.md](crowd-simulation.md) - Boids, formations, social forces, LOD for crowds, coordinated group movement
8. [weather-and-time.md](weather-and-time.md) - Day/night cycles, weather systems, seasonal effects, atmospheric simulation
9. [performance-optimization-for-sims.md](performance-optimization-for-sims.md) - Profiling, spatial partitioning, LOD, time-slicing, caching, performance tuning
10. [debugging-simulation-chaos.md](debugging-simulation-chaos.md) - Systematic debugging, desync detection, determinism, chaos prevention
Now route confidently to the specific skills you need!

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