behavior-trees

name	behavior-trees
description	Behavior tree design and implementation skill for game AI. Enables creation of behavior tree structures, custom nodes, decorators, composites, and integration with game engines for NPC and enemy AI systems.
allowed-tools	Read, Grep, Write, Bash, Edit, Glob, WebFetch
graph	{"domains":["domain:gaming"],"specializations":["specialization:game-development"],"skillAreas":["skill-area:game-ai-pathfinding","skill-area:gameplay-programming"],"roles":["role:game-developer"]}

Behavior Trees Skill

Comprehensive behavior tree design and implementation for game AI systems, supporting multiple engines and frameworks.

Overview

This skill provides capabilities for designing and implementing behavior trees for game AI. It covers the creation of tree structures, custom nodes, blackboard systems, and integration with Unity, Unreal Engine, and Godot behavior tree implementations.

Capabilities

Tree Design

• Design behavior tree structures from specifications
• Create hierarchical AI behaviors
• Balance between reactive and goal-oriented behaviors
• Optimize tree execution for performance

Node Types

• Composite Nodes: Sequence, Selector, Parallel, Random
• Decorator Nodes: Inverter, Repeater, Cooldown, Conditional
• Leaf Nodes: Actions, Conditions, Services

Blackboard System

• Design blackboard schemas
• Implement blackboard observers
• Manage shared AI state
• Handle blackboard key types

Engine Integration

• Unity: NodeCanvas, Behavior Designer, custom implementations
• Unreal: Behavior Tree Editor, custom tasks and services
• Godot: Beehave, LimboAI, custom implementations

Debugging

• Tree visualization
• Node state tracking
• Execution logging
• Performance profiling

Prerequisites

Unity (Node Canvas)

# Install via Package Manager or Asset Store
# Node Canvas, Behavior Designer, or similar

Unreal Engine (Built-in)

// Enable AI Module in Build.cs
PublicDependencyModuleNames.AddRange(new string[] {
    "AIModule",
    "GameplayTasks"
});

Godot (Beehave)

# Install via Asset Library
Beehave or LimboAI

Usage Patterns

Basic Behavior Tree Structure

Root
└── Selector (Try behaviors until one succeeds)
    ├── Sequence (Attack if possible)
    │   ├── Condition: HasTarget
    │   ├── Condition: InAttackRange
    │   └── Action: Attack
    ├── Sequence (Chase target)
    │   ├── Condition: HasTarget
    │   ├── Decorator: Cooldown(0.5s)
    │   │   └── Action: MoveToTarget
    │   └── Service: UpdateTargetLocation
    └── Sequence (Patrol)
        ├── Action: MoveToPatrolPoint
        └── Action: Wait(2s)

Unity Implementation (Custom)

// BehaviorTree.cs
public class BehaviorTree : MonoBehaviour
{
    private BTNode _root;
    private Blackboard _blackboard;

    private void Start()
    {
        _blackboard = new Blackboard();
        _root = BuildTree();
    }

    private void Update()
    {
        _root?.Execute(_blackboard);
    }

    private BTNode BuildTree()
    {
        return new Selector(
            new Sequence(
                new HasTargetCondition(),
                new InRangeCondition(attackRange: 2f),
                new AttackAction()
            ),
            new Sequence(
                new HasTargetCondition(),
                new Cooldown(0.5f,
                    new MoveToTargetAction()
                )
            ),
            new Sequence(
                new PatrolAction(),
                new WaitAction(2f)
            )
        );
    }
}

// BTNode.cs
public abstract class BTNode
{
    public enum NodeState { Running, Success, Failure }
    public NodeState State { get; protected set; }
    ;
}


   : 
{
      BTNode[] _children;

    
    {
        _children = children;
    }

    
    {
         ( child  _children)
        {
             state = child.Execute(blackboard);
             (state != NodeState.Failure)
            {
                State = state;
                 State;
            }
        }
        State = NodeState.Failure;
         State;
    }
}


   : 
{
      BTNode[] _children;
      _currentIndex;

    
    {
        _children = children;
    }

    
    {
         (_currentIndex < _children.Length)
        {
             state = _children[_currentIndex].Execute(blackboard);
             (state == NodeState.Failure)
            {
                _currentIndex = ;
                State = NodeState.Failure;
                 State;
            }
             (state == NodeState.Running)
            {
                State = NodeState.Running;
                 State;
            }
            _currentIndex++;
        }
        _currentIndex = ;
        State = NodeState.Success;
         State;
    }
}


  
{
      Dictionary<, > _data = ();

     => _data[key] = ;
     => _data.TryGetValue(key,   ) ? (T) : ;
     => _data.ContainsKey(key);
     => _data.Remove(key);
}

Unreal Engine Implementation (C++)

// BTTask_AttackTarget.h
#pragma once

#include "CoreMinimal.h"
#include "BehaviorTree/BTTaskNode.h"
#include "BTTask_AttackTarget.generated.h"

UCLASS()
class MYGAME_API UBTTask_AttackTarget : public UBTTaskNode
{
    GENERATED_BODY()

public:
    UBTTask_AttackTarget();

    virtual EBTNodeResult::Type ExecuteTask(UBehaviorTreeComponent& OwnerComp, uint8* NodeMemory) override;

protected:
    UPROPERTY(EditAnywhere, Category = "Attack")
    float AttackDamage = 10.0f;

    UPROPERTY(EditAnywhere, Category = "Attack")
    float AttackDuration = 1.0f;

    UPROPERTY(EditAnywhere, Category = "Blackboard")
    FBlackboardKeySelector TargetKey;
};

// BTTask_AttackTarget.cpp
#include "BTTask_AttackTarget.h"
#include "AIController.h"
#include "BehaviorTree/BlackboardComponent.h"

UBTTask_AttackTarget::UBTTask_AttackTarget()
{
    NodeName = "Attack Target";
    bNotifyTick = true;
}

EBTNodeResult::Type 
{
    AAIController* AIController = OwnerComp.();
     (!AIController)
    {
         EBTNodeResult::Failed;
    }

    UBlackboardComponent* BlackboardComp = OwnerComp.();
    AActor* TargetActor = <AActor>(BlackboardComp->(TargetKey.SelectedKeyName));

     (!TargetActor)
    {
         EBTNodeResult::Failed;
    }

    
    

     EBTNodeResult::Succeeded;
}








()
  UBTService_UpdateTargetLocation :  UBTService
{
    ()

:
    ();

:
    ;

    (EditAnywhere, Category = )
    FBlackboardKeySelector TargetKey;

    (EditAnywhere, Category = )
    FBlackboardKeySelector TargetLocationKey;
};








()
  UBTDecorator_InRange :  UBTDecorator
{
    ()

:
    ();

:
    ;

    (EditAnywhere, Category = )
     AcceptableRadius = ;

    (EditAnywhere, Category = )
    FBlackboardKeySelector TargetKey;
};

Godot Implementation (GDScript with Beehave)

# enemy_ai.gd
extends CharacterBody2D

@onready var behavior_tree: BeehaveTree = $BeehaveTree
@onready var blackboard: Blackboard = $Blackboard

func _ready() -> void:
    blackboard.set_value("patrol_points", $PatrolPoints.get_children())
    blackboard.set_value("current_patrol_index", 0)

# has_target_condition.gd
extends ConditionLeaf
class_name HasTargetCondition

func tick(actor: Node, blackboard: Blackboard) -> int:
    var target = blackboard.get_value("target")
    if target != null and is_instance_valid(target):
        return SUCCESS
    return FAILURE

# in_attack_range_condition.gd
extends ConditionLeaf
class_name InAttackRangeCondition

@export var attack_range: float = 50.0

func tick(actor: Node, blackboard: Blackboard) -> int:
    var target = blackboard.get_value("target")
    if target == null:
        return FAILURE

    var distance = actor.global_position.distance_to(target.global_position)
    if distance <= attack_range:
        return SUCCESS
    return FAILURE

# attack_action.gd
extends ActionLeaf
class_name AttackAction

@export var damage: int = 10
@export var attack_duration: float = 0.5

var _attack_timer: float = 0.0
var _is_attacking: bool = false

func tick(actor: Node, blackboard: Blackboard) -> int:
    if not _is_attacking:
        _start_attack(actor, blackboard)
        return RUNNING

    _attack_timer -= get_process_delta_time()
    if _attack_timer <= 0:
        _finish_attack(actor, blackboard)
        return SUCCESS

    return RUNNING

func _start_attack(actor: Node, blackboard: Blackboard) -> void:
    _is_attacking = true
    _attack_timer = attack_duration
    # Play attack animation, etc.

func _finish_attack(actor: Node, blackboard: Blackboard) -> void:
    _is_attacking = false
    var target = blackboard.get_value("target")
    if target and target.has_method("take_damage"):
        target.take_damage(damage)

# move_to_target_action.gd
extends ActionLeaf
class_name MoveToTargetAction

@export var move_speed: float = 100.0
@export var arrival_distance: float = 10.0

func tick(actor: Node, blackboard: Blackboard) -> int:
    var target = blackboard.get_value("target")
    if target == null:
        return FAILURE

    var target_pos = target.global_position
    var distance = actor.global_position.distance_to(target_pos)

    if distance <= arrival_distance:
        return SUCCESS

    var direction = (target_pos - actor.global_position).normalized()
    actor.velocity = direction * move_speed
    actor.move_and_slide()

    return RUNNING

Integration with Babysitter SDK

Task Definition Example

const behaviorTreeTask = defineTask({
  name: 'behavior-tree-design',
  description: 'Design and implement behavior tree for AI',

  inputs: {
    engine: { type: 'string', required: true }, // unity, unreal, godot
    aiType: { type: 'string', required: true }, // enemy, npc, companion
    behaviors: { type: 'array', required: true },
    outputPath: { type: 'string', required: true }
  },

  outputs: {
    treePath: { type: 'string' },
    nodeFiles: { type: 'array' },
    success: { type: 'boolean' }
  },

  async run(inputs, taskCtx) {
    return {
      kind: 'skill',
      title: `Design behavior tree for ${inputs.aiType}`,
      skill: {
        name: 'behavior-trees',
        context: {
          operation: ,
          : inputs.,
          : inputs.,
          : inputs.,
          : inputs.
        }
      },
      : {
        : ,
        : 
      }
    };
  }
});

Common Behavior Patterns

Combat AI

Selector
├── Sequence [Flee if low health]
│   ├── Condition: HealthBelowThreshold(20%)
│   └── Action: FleeFromTarget
├── Sequence [Attack in range]
│   ├── Condition: HasTarget
│   ├── Condition: InAttackRange
│   └── Action: Attack
├── Sequence [Approach target]
│   ├── Condition: HasTarget
│   └── Action: MoveToTarget
└── Action: SearchForTarget

Patrol AI

Selector
├── Sequence [Investigate disturbance]
│   ├── Condition: HeardNoise
│   ├── Action: MoveToNoiseLocation
│   └── Action: LookAround
├── Sequence [Patrol]
│   ├── Action: MoveToNextPatrolPoint
│   ├── Action: Wait(2s)
│   └── Action: AdvancePatrolIndex
└── Action: Idle

Companion AI

Selector
├── Sequence [Help player in combat]
│   ├── Condition: PlayerInCombat
│   ├── Condition: HasTarget
│   └── Action: AttackPlayerTarget
├── Sequence [Heal player]
│   ├── Condition: PlayerHealthLow
│   ├── Condition: HasHealAbility
│   └── Action: HealPlayer
├── Sequence [Follow player]
│   ├── Condition: TooFarFromPlayer
│   └── Action: MoveToPlayer
└── Action: IdleNearPlayer

Best Practices

1. Keep Trees Shallow: Deep trees are harder to debug and maintain
2. Use Services: Update blackboard values in services, not conditions
3. Fail Fast: Put cheap conditions before expensive ones
4. Blackboard Keys: Use typed keys and validate at design time
5. Modular Nodes: Create reusable, single-purpose nodes
6. Debug Visualization: Always implement tree visualization for debugging

Performance Considerations

Optimization	Description
Conditional Aborts	Stop lower-priority branches when conditions change
Service Intervals	Don't update every frame if not needed
Blackboard Observers	React to changes instead of polling
Node Pooling	Reuse node instances for dynamic trees

References

• Behavior Trees in Game AI
• Unreal Engine Behavior Trees
• Beehave (Godot)
• ClaudeAI Plugin for UE5 - Generates Behavior Trees
• Understanding Behavior Trees