name: 4d-compression-core version: 1.0.2 description: "把长内容压缩成结构化向量——节省 60-80% Token,保留核心信息" metadata: { "openclaw": { "emoji": "🌀", "requires": { "bins": ["jq", "awk"] }, "triggers": ["压缩", "4d",...
日本語の概要は準備中です。原文の説明を表示しています。
Other tools need perfect images. CellCog turns ideas into 3D models. From rough sketches, text descriptions, or product photos — production-ready GLB files for games, AR/VR, e-commerce, and 3D printing.
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
Other tools need perfect images. CellCog turns ideas into 3D models.
Most 3D generation tools need a single, perfectly composed reference image. CellCog takes anything — a text description, a rough sketch, a product photo, even a spreadsheet of 50 items — and handles the entire pipeline: reasoning about what you need, generating optimized reference images, and converting them into production-ready GLB files.
This skill requires the cellcog skill for SDK setup and API calls.
clawhub install cellcog
Read the cellcog skill first for SDK setup. This skill shows you what's possible.
Quick pattern (v1.0+):
# Fire-and-forget - returns immediately
result = client.create_chat(
prompt="[your 3D generation request]",
notify_session_key="agent:main:main",
task_label="3d-gen",
chat_mode="agent"
)
# Daemon notifies you when complete - do NOT poll
The power of CellCog isn't image-to-3D — everyone does that. The power is any-to-any.
| What You Send | What CellCog Does | What You Get |
|---|---|---|
| Text description | Reasons about the object → generates optimized reference image → converts to 3D | Production-ready GLB |
| Rough sketch | Enhances into a clean, detailed reference → converts to 3D | Production-ready GLB |
| Product photo | Assesses quality, enhances if needed → converts to 3D | Production-ready GLB |
| High-quality concept art | Converts directly to 3D | Production-ready GLB |
| List of 10 items | Generates 10 reference images → converts all to 3D | 10 GLB files |
Need 10 low-poly weapons for your RPG? 20 furniture models for your room designer? 50 product models for your e-commerce catalog?
One prompt. Multiple 3D models. CellCog's agents generate each reference image with the right composition, angle, and detail level — then convert each to a textured 3D model.
prompt = """
Create 3D models (GLB format) for these 5 fantasy weapons:
1. Enchanted longsword with blue crystal blade
2. Dwarven war hammer with rune inscriptions
3. Elven bow with living vine decorations
4. Shadow dagger with smoke effects on the blade
5. Holy mace with golden sunburst head
Low poly (~10,000 polygons each), game-ready, with PBR materials.
"""
All 3D models are delivered as GLB files (binary glTF) — the universal web standard for 3D:
<model-viewer> or Three.js| Scenario | Recommended Mode |
|---|---|
| Single 3D object from a clear description or image | "agent" |
| Batch generation (5-20 objects from a list) | "agent" |
| Complex game asset pipeline with style consistency | "agent team" |
Use "agent" for most 3D work. It handles everything from single objects to batch generation.
Use "agent team" when you need cross-asset consistency — like generating a full set of fantasy weapons that all share the same art style, or building a complete room of furniture that matches a design language.
Single object from description:
"Create a 3D model of a steampunk pocket watch with exposed brass gears, an etched glass face, and a chain attachment. GLB format, high detail."
From a reference image:
"Convert this product photo into a 3D model for our online store:
<SHOW_FILE>/photos/sneaker_product.png</SHOW_FILE>Output as GLB, enable PBR materials for realistic rendering."
Batch generation:
"Generate 3D models for these 8 pieces of modern furniture:
- Minimalist sofa (3-seater, light gray)
- Round coffee table (walnut wood, glass top)
- Floor lamp (arc style, brass finish)
- Bookshelf (5 tiers, oak wood)
- Dining chair (Scandinavian, white)
- Side table (concrete, cylindrical)
- Desk (standing desk, white with birch legs)
- TV console (low profile, dark walnut)
All low-poly (~15,000 polygons), with PBR materials. GLB format."
From a rough sketch:
"Here's my rough sketch of a robot character:
<SHOW_FILE>/sketches/robot_concept.jpg</SHOW_FILE>Turn this into a polished 3D model. It's a friendly service robot — round body, simple limbs, LED face display. Style: Overwatch/Pixar clean 3D. Output as GLB."
Game asset set:
"I'm building a dungeon crawler. Create 3D models for these dungeon props:
- Wooden treasure chest (open and closed variants)
- Iron torch holder with flame
- Stone altar with carved runes
- Wooden barrel (intact and broken)
- Skull pile
Style: Dark fantasy, hand-painted textures. Low poly for mobile game (~8,000 polygons each)."
Be specific about materials: "brushed aluminum", "aged leather", "polished marble" — CellCog uses these to generate better reference images and textures.
Specify your target platform: "low-poly for mobile game" vs "high-detail for cinematic render" changes the approach completely.
Send reference images when possible: Even imperfect references give CellCog a head start over pure text descriptions.
For batch jobs, describe style once: "All in a cohesive hand-painted fantasy style" keeps your assets consistent.
Request PBR materials for realism: If you need metallic, roughness, and normal maps — say so. Essential for game engines and realistic rendering.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
name: 4d-compression-core version: 1.0.2 description: "把长内容压缩成结构化向量——节省 60-80% Token,保留核心信息" metadata: { "openclaw": { "emoji": "🌀", "requires": { "bins": ["jq", "awk"] }, "triggers": ["压缩", "4d",...
日本語の概要は準備中です。原文の説明を表示しています。
Use cheap, TEE-verified AI models from the 0G Compute Network as OpenClaw providers. Discover available models and compare pricing vs OpenRouter, verify provider integrity via hardware attestation (Intel TDX), manage your 0G wallet and sub-accounts, and configure models in OpenClaw with one workflow. Supports DeepSeek, GLM-5, Qwen, and other models available on the 0G marketplace.
日本語の概要は準備中です。原文の説明を表示しています。
Send and receive P2P messages using disposable numbers and PINs. No servers, no accounts. Use for human notifications, approval flows, and agent-to-agent communication.
日本語の概要は準備中です。原文の説明を表示しています。
Query historical crypto market data from 0xArchive across Hyperliquid, Lighter.xyz, and HIP-3. Covers orderbooks, trades, candles, funding rates, open interest, liquidations, and data quality. Use when the user asks about crypto market data, orderbooks, trades, funding rates, or historical prices on Hyperliquid, Lighter.xyz, or HIP-3.
日本語の概要は準備中です。原文の説明を表示しています。
Find and complete paid tasks on the 0xWork decentralized marketplace (Base chain, USDC escrow). Use when: the agent wants to earn money/USDC by doing work, discover available tasks, claim a bounty, submit deliverables, check earnings or wallet balance, or set up as a 0xWork worker. Task categories: Writing, Research, Social, Creative, Code, Data. NOT for: posting tasks (use the website), managing the 0xWork platform, or frontend development.
日本語の概要は準備中です。原文の説明を表示しています。
Patterns and practices that dramatically accelerate development velocity. Covers parallel execution, automation, feedback loops, workflow optimization, and anti-pattern avoidance. Use when starting projects, planning sprints, optimizing workflows, or onboarding developers.
日本語の概要は準備中です。原文の説明を表示しています。