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 ecs-performancegit 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/ecs-performance)<a href="https://agentmods.dev/skills/bullish0x/gamestudio/ecs-performance"><img src="https://agentmods.dev/badge/skills/bullish0x/gamestudio/ecs-performance/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/ecs-performance"><img src="https://agentmods.dev/badge/skills/bullish0x/gamestudio/ecs-performance.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 | $0.00023 | $0.04571 |
| Opus 5 | $0.00012 | $0.02286 |
| Sonnet 5 | $0.00005 | $0.00914 |
| Haiku 4.5 | $0.00002 | $0.00457 |
Grade A, and why
ecs-performance 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 7d 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 — 782 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ECS Performance Optimization
When to Use
Use this skill when:
- Scaling to thousands of entities
- Optimizing frame time
- Reducing memory allocations
- Improving cache coherency
- Debugging performance issues
- Targeting mobile devices
Core Principles
- Data-Oriented: Organize data for cache efficiency
- Minimize Allocations: Pool and reuse objects
- Batch Operations: Process similar entities together
- Profile First: Measure before optimizing
- Lazy Evaluation: Compute only when needed
- Archetype-Based: Group entities by components
Performance Optimization Techniques
1. Archetype Optimization
// core/Archetype.ts
export interface Archetype {
signature: string;
entities: Entity[];
componentData: Map<ComponentConstructor<any>, any[]>;
}
export class ArchetypeStorage {
private archetypes = new Map<string, Archetype>();
getArchetype(componentTypes: ComponentConstructor<any>[]): Archetype {
const signature = this.getSignature(componentTypes);
let archetype = this.archetypes.get(signature);
if (!archetype) {
archetype = {
signature,
entities: [],
componentData: new Map(),
};
// Pre-allocate component arrays
for (const type of componentTypes) {
archetype.componentData.set(type, []);
}
this.archetypes.set(signature, archetype);
}
return archetype;
}
addEntity(entity: Entity, componentTypes: ComponentConstructor<any>[]): void {
const archetype = this.getArchetype(componentTypes);
archetype.entities.push(entity);
// Add component data to arrays
for (const type of componentTypes) {
const component = entity.getComponent(type);
const array = archetype.componentData.get(type)!;
array.push(component);
}
}
removeEntity(entity: Entity, componentTypes: ComponentConstructor<any>[]): void {
const archetype = this.getArchetype(componentTypes);
const index = archetype.entities.indexOf(entity);
if (index !== -1) {
// Remove from entity array
archetype.entities.splice(index, 1);
// Remove from component arrays
for (const [type, array] of archetype.componentData) {
array.splice(index, 1);
}
}
}
// Iterate cache-friendly
iterateArchetype<T extends any[]>(
componentTypes: ComponentConstructor<any>[],
callback: (components: T, entity: Entity) => void
): void {
const archetype = this.getArchetype(componentTypes);
const componentArrays = componentTypes.map((type) =>
archetype.componentData.get(type)
);
const length = archetype.entities.length;
for (let i = 0; i < length; i++) {
const components = componentArrays.map((arr) => arr![i]) as T;
callback(components, archetype.entities[i]);
}
}
private getSignature(componentTypes: ComponentConstructor<any>[]): string {
return componentTypes
.map((t) => t.name)
.sort()
.join(':');
}
}
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.
- 7d ago First seen · 782 lines · 23 tokens per session scan A 78c3de2bbab9
ecs-performance is a skill published in the GitHub repository bullish0x/GameStudio (12 stars, last pushed 3mo ago), licensed MIT. It adds 23 tokens to every session and 4,571 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 2026-09-03.
Other skills, from other repositories
game-development
Game development with Unity, Unreal Engine, and Godot. Use when building games, implementing game mechanics, physics, AI, or working with game engines.
ar-vr-xr
AR/VR/XR development with Unity XR, WebXR, ARKit, ARCore, Meta Quest SDK, and spatial computing. Use when building augmented reality, virtual reality, mixed reality applications, or spatial experiences.
sdf
SDFormat/SDF model and world authoring, validation, and simulator handoff. Use for .sdf files, SDFormat XML, models, worlds, links, joints, poses, frames, inertials, visual/collision geometry, mesh URIs, sensors, lights, physics, plugins, includes, Gazebo, static SDF review, or simulator-specific metadata. Do not use…
unity-agent-workflows
Use for AI-assisted Unity work that needs live repo discovery, project-derived routing, runtime-owner proof, runtime-visible output hard stops, runtime numeric proof for repeated visible-output failures, state-step guards, multi-agent scope ownership, modular C#/asmdef safety, UI/scene/visual asset gates, data-first…
using-bgs-archive
Use when the user wants to inspect, list, extract, unpack, or repack Bethesda BA2/BSA archives; determine archive format/version/compression; or build archive assets for an MO2 overlay. Triggers - "unpack BA2", "extract BSA", "pack archive", "inspect archive", "bgs-archive".
ai-ml-development
AI and machine learning development with PyTorch, TensorFlow, and LLM integration. Use when building ML models, training pipelines, fine-tuning LLMs, or implementing AI features.