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 manhvann/codexkit --skill threejsgit clone --depth 1 https://github.com/manhvann/codexkitWrote 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/manhvann/codexkit/threejs)<a href="https://agentmods.dev/skills/manhvann/codexkit/threejs"><img src="https://agentmods.dev/badge/skills/manhvann/codexkit/threejs/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/manhvann/codexkit/threejs"><img src="https://agentmods.dev/badge/skills/manhvann/codexkit/threejs.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00093 | $0.01290 |
| Opus 5.5 | $0.00037 | $0.00516 |
| Sonnet 5.5 | $0.00019 | $0.00258 |
| Haiku 4.5 | $0.00009 | $0.00129 |
Grade A, and why
ck:threejs 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 1mo 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 — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Three.js Development
Build high-performance 3D web applications using Three.js. Contains 556 searchable examples across 13 categories, 60 API classes, and 20 use-case templates.
When to Use
- Building 3D scenes, games, or visualizations
- Loading 3D models (GLTF, FBX, OBJ)
- Implementing animations, physics, or VR/XR
- Creating particle effects or custom shaders
- Optimizing rendering performance
Search Examples & API
Use the search CLI to find relevant examples and API references:
python3 .agents/skills/threejs/scripts/search.py "<query>" [--domain <domain>] [-n <max_results>]
Search Domains
| Domain | Use For | Example Query |
|---|---|---|
examples |
Find code examples | "particle effects gpu" |
api |
Class/method reference | "PerspectiveCamera" |
use-cases |
Project recommendations | "product configurator" |
categories |
Browse categories | "webgpu" |
Quick Examples
# Find particle/compute examples
python3 .agents/skills/threejs/scripts/search.py "particle compute webgpu"
# Search API for camera classes
python3 .agents/skills/threejs/scripts/search.py "camera" --domain api
# Get examples for a use case
python3 .agents/skills/threejs/scripts/search.py "product configurator" --use-case
# Filter by category
python3 .agents/skills/threejs/scripts/search.py --category webgpu -n 10
# Filter by complexity
python3 .agents/skills/threejs/scripts/search.py --complexity high -n 5
Example Categories
| Category | Count | Description |
|---|---|---|
webgl |
216 | Standard WebGL rendering |
webgpu (wip) |
190 | Modern WebGPU + compute shaders |
webgl / advanced |
48 | Low-level GPU, custom shaders |
webgl / postprocessing |
27 | Bloom, SSAO, SSR, DOF |
webxr |
26 | VR/AR experiences |
physics |
13 | Physics simulation |
Common Use Cases
| Use Case | Recommended | Complexity |
|---|---|---|
| Product Configurator | GLTF, PBR, EnvMaps | Medium |
| Game Development | Animation, Physics, Controls | High |
| Data Visualization | BufferGeometry, Points | Medium |
| 360 Panorama | Equirectangular, WebXR | Low |
| Architectural Viz | GLTF, HDR, CSM Shadows | High |
What ships with it
28 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- data/api-reference.csv 8.3 KB
- data/categories.csv 1.9 KB
- data/examples-all.csv 129 KB
- data/use-cases.csv 4.2 KB
- references/00-fundamentals.md 11 KB
- references/01-getting-started.md 3.7 KB
- references/02-loaders.md 4.0 KB
- references/03-textures.md 4.1 KB
- references/04-cameras.md 4.8 KB
- references/05-lights.md 4.3 KB
- references/06-animations.md 4.7 KB
- references/07-math.md 5.1 KB
- references/08-interaction.md 6.6 KB
- references/09-postprocessing.md 5.3 KB
- references/10-controls.md 5.8 KB
- references/11-materials-advanced.md 5.9 KB
- references/11-materials.md 13 KB
- references/12-performance.md 6.5 KB
- references/13-node-materials.md 6.7 KB
- references/14-physics-vr.md 6.7 KB
- references/15-specialized-loaders.md 7.4 KB
- references/16-webgpu.md 7.0 KB
- references/17-shader.md 14 KB
- references/18-geometry.md 13 KB
- scripts/core.py 7.7 KB runs code
- scripts/extract_examples.py 41 KB runs code
- scripts/generate_csv_from_json.py 4.7 KB runs code
- scripts/search.py 2.7 KB runs code
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.
- 1mo ago First seen · 143 lines · 93 tokens per session scan A 9b9d695c38d0
ck:threejs is a skill published in the GitHub repository manhvann/codexkit (89 stars, last pushed 1mo ago), licensed MIT. It adds 93 tokens to every session and 1,290 once invoked, about $0.0004 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 2026-08-30.
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