Behavior Trees, Utility AI
Builds behavior-tree and utility-AI decision systems for game agents.
Install
npx skills add gamedev-skills/awesome-gamedev-agent-skills --skill ai-behavior-trees-utility-ai -g -a claude-code -y- Repository
- gamedev-skills/awesome-gamedev-agent-skills6.4k
- Category
- Engineering
- Updated
- 8d ago
- License
- Apache-2.0
- Context cost
- Mediumabout 2,096 tokens
- Runs scripts
- No, instructions only
What it does
Build a production behavior-tree runtime (Blackboard, action/condition leaves, sequence/selector/parallel composites, decorators) and a Utility AI system (response curves, linear, exponential, sigmoid, quadratic, considerations, and action evaluators), plus hybrid BT-drives-Utility agents. Use when implementing a reusable behavior-tree or utility-based decision system, or tuning enemy/NPC decisions beyond a simple FSM, or when the user mentions behavior tree, blackboard, decorator, selector, sequence, tick status, utility AI, response/scoring curve, or consideration. For choosing between FSM/BT/steering or for pathfinding, use game-ai; for Unreal's BehaviorTree/Blackboard assets, use unreal-behavior-trees.
Behavior Trees & Utility AI
Two complementary ways to structure NPC decision-making, plus how to combine them. A behavior tree (BT) expresses structured, prioritized, reactive logic as a tree that is "ticked" each step. Utility AI answers "how much do I want each option right now?" by scoring actions with normalized curves and picking the best. Ship believable agents by using a BT for structure and Utility AI where graded trade-offs matter.
This skill is the implementation companion to game-ai (which helps you choose between
FSM / BT / steering / pathfinding). Read game-ai to pick a model; read this to build the
runtime.
When to use
- Use to build a reusable BT runtime: a
Blackboard,Nodebase, action/condition leaves,Sequence/Selector/Parallelcomposites, and decorators (Inverter, Cooldown, Repeat). - Use to build a Utility AI decider: response curves, considerations, and an evaluator that scores and selects actions (max, softmax, or weighted-random for variety).
- Use to build hybrid AI, a BT whose leaf delegates the "which attack / which target" choice to a utility evaluator.
When not to use: to choose between FSM, BT, steering, or pathfinding, and for A*/navmesh
routing, use game-ai. For Unreal's asset-based BehaviorTree/Blackboard, BTTask/BTService
and AIController, use unreal-behavior-trees. For the navmesh agent that moves the NPC, use
unity-navmesh or the engine's navigation node.
