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.
npx agentmods add commands/sponticelli/gamedev-claude-plugins/behavior-treegit clone --depth 1 https://github.com/sponticelli/gamedev-claude-pluginsWrote 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.
[](https://agentmods.dev/commands/sponticelli/gamedev-claude-plugins/behavior-tree)<a href="https://agentmods.dev/commands/sponticelli/gamedev-claude-plugins/behavior-tree"><img src="https://agentmods.dev/badge/commands/sponticelli/gamedev-claude-plugins/behavior-tree.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00013 | $0.00732 |
| Opus 5 | $0.00006 | $0.00366 |
| Sonnet 5 | $0.00003 | $0.00146 |
| Haiku 4.5 | $0.00001 | $0.00073 |
Grade A, and why
behavior-tree 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Behavior Tree Generator
Create a behavior tree design for game AI.
Context Gathering
Before generating the behavior tree, understand the context:
Analyze the NPC
- What type of entity? (Enemy, companion, neutral NPC)
- What's their role in gameplay?
- What actions can they perform?
- What should they prioritize?
Understand Game Context
- What game genre and style?
- What other AI exists for reference?
- What level of complexity is appropriate?
- What debugging tools are available?
Check Technical Requirements
- What behavior tree system is used?
- What node types are available?
- Performance constraints?
- Integration with other systems?
Identify Key Behaviors
- What must this AI do?
- What's the highest priority?
- What's the fallback behavior?
- What triggers special behaviors?
Use this context to design appropriate behavior tree.
Output Format
# Behavior Tree: [NPC/Enemy Type]
## Overview
**Entity type:** [Enemy/Companion/NPC]
**Complexity:** [Simple/Medium/Complex]
**Priority focus:** [Combat/Patrol/Service/etc.]
## Tree Visualization
[Root: Selector] ├─ [Priority 1: Sequence] │ ├─ [Condition] │ └─ [Action] ├─ [Priority 2: Selector] │ ├─ [Sequence] │ │ ├─ [Condition] │ │ └─ [Action] │ └─ [Fallback] └─ [Default: Action]
## Node Definitions
### Composite Nodes
| Node | Type | Children | Purpose |
|------|------|----------|---------|
| [Name] | [Selector/Sequence/Parallel] | [Names] | [What it does] |
### Condition Nodes
| Node | Check | Success | Failure |
|------|-------|---------|---------|
| [Name] | [What's evaluated] | [When true] | [When false] |
### Action Nodes
| Node | Action | Duration | Exit |
|------|--------|----------|------|
| [Name] | [What it does] | [Time/Condition] | [Success/Fail/Running] |
### Decorator Nodes
| Node | Child | Modification |
|------|-------|--------------|
| [Name] | [Which node] | [How it modifies] |
## Behavior Breakdown
### [High Priority Behavior]
**Trigger:** [What activates this branch]
**Sequence:**
1. [Check condition]
2. [Perform action]
3. [Continue or exit]
### [Medium Priority Behavior]
**Trigger:** [What activates this branch]
**Sequence:**
[Steps]
### [Fallback Behavior]
**When:** [All else fails]
**Action:** [What they do]
## Blackboard Variables
| Variable | Type | Set By | Used By |
|----------|------|--------|---------|
| [Name] | [Type] | [What sets it] | [What reads it] |
## State Transitions
[How the AI moves between major behavioral states]
## Debug Information
**Key breakpoints:** [Where to check behavior]
**Log points:** [What to log]
**Visualization:** [What to show in debug view]
## Edge Cases
| Scenario | Handling |
|----------|----------|
| [Edge case] | [How the tree handles it] |
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.
- 4d ago First seen · 125 lines · 13 tokens per session scan A a9f6dec7b78f
behavior-tree is a command published in the GitHub repository sponticelli/gamedev-claude-plugins (15 stars, last pushed 7mo ago), licensed MIT. It adds 13 tokens to every session and 732 once invoked, about $0.0001 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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