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 skills add bullish0x/GameStudio --skill ai-systemgit clone --depth 1 https://github.com/bullish0x/GameStudioWrote 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/skills/bullish0x/gamestudio/ai-system)<a href="https://agentmods.dev/skills/bullish0x/gamestudio/ai-system"><img src="https://agentmods.dev/badge/skills/bullish0x/gamestudio/ai-system/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.
<a href="https://agentmods.dev/skills/bullish0x/gamestudio/ai-system"><img src="https://agentmods.dev/badge/skills/bullish0x/gamestudio/ai-system.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00022 | $0.04979 |
| Opus 5.5 | $0.00009 | $0.01992 |
| Sonnet 5.5 | $0.00004 | $0.00996 |
| Haiku 4.5 | $0.00002 | $0.00498 |
Grade A, and why
ai-system 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 2mo 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 — 829 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI System
When to Use
Use this skill when:
- Creating enemy AI
- Implementing NPC behavior
- Building autonomous agents
- Creating steering and pathfinding
- Implementing decision-making systems
- Building tactical AI
Core Principles
- Separation of Logic: AI separate from rendering/physics
- Hierarchical Behavior: Break complex behaviors into simple tasks
- State-Driven: Use FSMs or behavior trees
- Performance-Aware: Update frequency based on importance
- Debuggable: Visualize AI state and decisions
- Data-Driven: Configure AI in data files
AI System Implementation
1. Finite State Machine (FSM)
// ai/StateMachine.ts
export interface State {
name: string;
onEnter?: (entity: Entity) => void;
onUpdate?: (entity: Entity, deltaTime: number) => void;
onExit?: (entity: Entity) => void;
}
export interface Transition {
from: string;
to: string;
condition: (entity: Entity) => boolean;
}
export class StateMachine {
private states = new Map<string, State>();
private transitions: Transition[] = [];
private currentState: State | null = null;
addState(state: State): void {
this.states.set(state.name, state);
}
addTransition(transition: Transition): void {
this.transitions.push(transition);
}
start(stateName: string, entity: Entity): void {
const state = this.states.get(stateName);
if (!state) {
console.warn(`State not found: ${stateName}`);
return;
}
if (this.currentState?.onExit) {
this.currentState.onExit(entity);
}
this.currentState = state;
if (this.currentState.onEnter) {
this.currentState.onEnter(entity);
}
}
update(entity: Entity, deltaTime: number): void {
if (!this.currentState) return;
// Update current state
if (this.currentState.onUpdate) {
this.currentState.onUpdate(entity, deltaTime);
}
// Check transitions
for (const transition of this.transitions) {
if (transition.from === this.currentState.name && transition.condition(entity)) {
this.start(transition.to, entity);
break;
}
}
}
getCurrentStateName(): string | null {
return this.currentState?.name ?? null;
}
}
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.
- 2mo ago First seen · 829 lines · 22 tokens per session scan A 3890ea04df58
ai-system is a skill published in the GitHub repository bullish0x/GameStudio (26 stars, last pushed 5mo ago), licensed MIT. It adds 22 tokens to every session and 4,979 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-31.
ai-system compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| ai-systembullish0x/GameStudio | Skill | 26 | 5mo ago | MIT | A | 22 | Claude Code |
| ar-vr-xrtravisjneuman/.claude | Skill | 110 | yesterday | MIT | A | 50 | Claude Code |
| game-developmenttravisjneuman/.claude | Skill | 110 | yesterday | MIT | A | 34 | Claude Code |
| agent-game-developertravisjneuman/.claude | Skill | 110 | yesterday | MIT | A | 24 | Claude Code |
| unity-agent-workflowshashgraph-online/awesome-codex-plugins | Skill | 1.6k | yesterday | Apache-2.0 | A | 158 | Codex |
| using-bgs-archivehashgraph-online/awesome-codex-plugins | Skill | 1.6k | yesterday | Apache-2.0 | A | 75 | Claude Code, Codex |
| marketingtravisjneuman/.claude | Skill | 110 | yesterday | MIT | A | 49 | Claude Code |