behavior-trees

behavior-trees is a skill for Claude Code, Codex from kevinpbuckley/VibeUE. It costs 86 tokens per session (1,972 once invoked), scanned A, original, MIT.

A tool for building and inspecting Unreal Engine Behavior Trees and Blackboards. A Behavior Tree organizes an AI character’s decisions, while a Blackboard stores the values those decisions use, such as a target or location.

In plain words
What is it for?
Use it to create AI decision trees, add composites, tasks, decorators, and services, create and manage Blackboard keys, bind keys to nodes, and validate the resulting assets.
Why use it?
It keeps AI decision logic and its shared data organized. Creating the Blackboard first also helps ensure that tree nodes refer to the correct keys and data types.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to create AI decision trees, add composites, tasks, decorators, and services, create and manage Blackboard keys, bind keys to nodes, and validate the resulting assets.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/kevinpbuckley/vibeue/behavior-trees
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add kevinpbuckley/VibeUE --skill behavior-trees
Clone the repo
git clone --depth 1 https://github.com/kevinpbuckley/VibeUE

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for behavior-trees

README.md
[![agentmods](https://agentmods.dev/badge/skills/kevinpbuckley/vibeue/behavior-trees/github.svg)](https://agentmods.dev/skills/kevinpbuckley/vibeue/behavior-trees)
Your own site
<a href="https://agentmods.dev/skills/kevinpbuckley/vibeue/behavior-trees"><img src="https://agentmods.dev/badge/skills/kevinpbuckley/vibeue/behavior-trees/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for behavior-trees

Your own site · 80×15
<a href="https://agentmods.dev/skills/kevinpbuckley/vibeue/behavior-trees"><img src="https://agentmods.dev/badge/skills/kevinpbuckley/vibeue/behavior-trees.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 86 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,972 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00086 $0.01972
Opus 5 $0.00043 $0.00986
Sonnet 5 $0.00017 $0.00394
Haiku 4.5 $0.00009 $0.00197

Measured 9d ago against content hash f3708c3491c8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

behavior-trees scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Content/Skills/behavior-trees/SKILL.md · 149 lines

How it starts

The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.

🧠 Brains complement: IF an unreal-engine-skills-manager tool (external MCP) exists in this session, call it with {action: "load", skill: "ai-and-navigation"} for UE domain knowledge on Behavior Trees — architecture, node semantics, best practices. If no such tool is available, skip this line entirely and proceed with this skill alone — do NOT attempt the call.

Behavior Trees Skill

Two services, reachable from Python (unreal.BehaviorTreeService.*, unreal.BlackboardService.*) and as AICallable tools:

BlackboardService     → UBlackboardData assets: create, key CRUD, metadata, re-parenting
BehaviorTreeService   → UBehaviorTree assets: structure, sub-nodes, properties, build, validate

Discover exact signatures with discover_python_class('unreal.BehaviorTreeService') — this skill teaches the concepts and the gotchas, not the call shapes.

The golden workflow

import unreal
BT = unreal.BehaviorTreeService
BB = unreal.BlackboardService

# 1. Blackboard first — key bindings resolve against the TREE'S board, so assign it at creation.
BB.create_blackboard("/Game/AI/BB_Guard")
BB.add_blackboard_key("/Game/AI/BB_Guard", "TargetActor", "Object")
BB.set_blackboard_key_object_class("/Game/AI/BB_Guard", "TargetActor", "/Script/Engine.Actor")

# 2. Tree on that board.
BT.create_behavior_tree("/Game/AI/BT_Guard", "/Game/AI/BB_Guard")

# 3. Structure. Every mutator returns the new node's PATH (or "ERROR: ...").
sel = BT.add_node("/Game/AI/BT_Guard", "Root", "BTComposite_Selector")          # Root/Selector[0]
seq = BT.add_node("/Game/AI/BT_Guard", sel, "BTComposite_Sequence")
wait = BT.add_node("/Game/AI/BT_Guard", seq, "BTTask_Wait")

# 4. Properties and bindings.
BT.set_node_property_value("/Game/AI/BT_Guard", wait, "WaitTime", '(DefaultValue=3.5,Key="")')
dec = BT.add_decorator("/Game/AI/BT_Guard", seq, "BTDecorator_Blackboard")
BT.set_node_blackboard_key("/Game/AI/BT_Guard", dec, "BlackboardKey", "TargetActor")

# 5. Verify.
print(BT.validate_tree("/Game/AI/BT_Guard"))   # [] == clean
print(BT.get_tree("/Game/AI/BT_Guard"))        # whole tree as JSON

Read the full file on GitHub · 149 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 149 lines · 86 tokens per session scan A f3708c3491c8

Subscribe to this mod's changes

behavior-trees is a skill published in the GitHub repository kevinpbuckley/VibeUE (659 stars, last pushed 5d ago), licensed MIT. It adds 86 tokens to every session and 1,972 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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