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game-ai

Agent skill fromgamedev-skills/awesome-gamedev-agent-skills

Design NPC and enemy decision-making with finite state machines, behavior trees, steering behaviors, and A* pathfinding — engine-neutral algorithms that pair with the detected engine's navigation API. Use when building enemy AI, an FSM or behavior tree, steering/flocking, or pathfinding, or when the user mentions state machine, behavior tree, blackboard, A*, navmesh, seek, or patrol/chase.

How to install game-ai

install game-ai
# install the awesome-gamedev-agent-skills pack with the skills CLI
npx skills add gamedev-skills/awesome-gamedev-agent-skills

# or add only this skill to Claude Code: copy the folder

skills/disciplines/game-ai/

# into

~/.claude/skills/game-ai/ (all projects)

.claude/skills/game-ai/ (one project)

skills/disciplines/game-ai/SKILL.md

Apache-2.0Full file
1# Game AI: decisions, steering, and pathfinding
2
3Build believable NPC behavior from three separable layers: **decide** (what to
4do), **steer** (how to move there), and **path** (how to route around the map).
5Keep them decoupled — a behavior tree picks a target, the pathfinder produces
6waypoints, steering follows them. This skill teaches the engine-neutral
7algorithms; bind them to your engine via the related skills below.
8
9## When to use
10
11- Use when implementing enemy/NPC logic: patrols, chase/flee, guard states,
12 group movement, or "find a path to the player".
13- Use to choose between an **FSM** (few clear states), a **behavior tree** (many
14 reactive behaviors with priorities), or **steering** (smooth local movement).
15- Use when integrating pathfinding: A* on a grid/graph, or driving an engine
16 navmesh agent.
17
18**When *not* to use:** for the engine's concrete navmesh/agent API and baking,
19use `unity-navmesh`, `unreal-behavior-trees`, or Godot's `NavigationAgent2D/3D`
20(see that engine skill). For movement/collision feel, use `physics-tuning`. For
21spawning waves along lanes, see the `tower-defense` genre skill.
22
23## Core workflow
24
251. **Pick the decision model by complexity.** 2–5 states with obvious
26 transitions → FSM. Many behaviors, priorities, interruption, reuse → behavior
27 tree. Continuous "how strongly do I want each option" → utility scoring.
282. **Separate decision from motion.** The decision layer outputs an *intent*
29…

Excerpt shown under the repository's Apache-2.0 license.

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