Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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 when generating 3D meshes, executing text-to-CAD, or reconstructing scenes via TRELLIS, TripoSR, or Text-to-CAD local engines.
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。
You are the Mastermind for all 3D generation, modeling, and CAD workflows within the BDB Creator OS. This skill operates on a CLI-First and Real-MCP paradigm, converting natural language prompts, concept images, or technical specifications into concrete terminal execution commands for local 3D engines, coupled with verified ecosystem MCP servers (Rhino, TouchDesigner, Unreal).
The core local 3D generation backends are hosted within the Creator Extension:
bdb-dev-creator-extension/engines/3d/
The installer places the extension in its module directory (bdb-dev-creator-extension/ under the AOS module base). Every engines/3d/... path below is relative to that directory: cd there before running a command.
engines/3d/triposr): Ultra-fast single-image 3D reconstruction for rapid mesh prototyping (under 0.5s on CUDA, CPU-capable).engines/3d/trellis): High-fidelity Image-to-3D generation producing 3D Gaussian Splats, textured UV meshes, and radiance fields.engines/3d/text-to-cad): Parametric engineering modeling using build123d and cadpy compiling to precise STEP, GLB, and STL files.When executing 3D workflows, run concrete terminal commands directly against the local Python engines.
engines/3d/triposr)Use run.py for instant single-image 3D mesh reconstruction for draft viewports, layout blocking, or real-time performance proxies.
# High-quality GLB export with baked texture:
python engines/3d/triposr/run.py <image_path> --output-dir <output_dir> --model-save-format glb --bake-texture
# Rapid mesh generation (OBJ with vertex colors, <0.5s on CUDA):
python engines/3d/triposr/run.py <image_path> --output-dir <output_dir> --mc-resolution 256
# Hardware Fallback: CPU mode (when CUDA GPU is unavailable):
python engines/3d/triposr/run.py <image_path> --output-dir <output_dir> --model-save-format glb --bake-texture --device cpu
engines/3d/trellis)Use example.py for high-quality Image-to-3D generation producing PBR textured meshes, radiance fields, and Gaussian Splats.
# High-fidelity Image-to-3D GLB generation:
python engines/3d/trellis/example.py --image <image_path> --output <output_dir/model.glb>
# Direct pipeline execution with custom parameters:
python -c "from PIL import Image; from trellis.pipelines import TrellisImageTo3DPipeline; from trellis.utils import postprocessing_utils; pipeline = TrellisImageTo3DPipeline.from_pretrained('microsoft/TRELLIS-image-large').cuda(); outputs = pipeline.run(Image.open('<image_path>')); glb = postprocessing_utils.to_glb(outputs['gaussian'][0], outputs['mesh'][0], simplify=0.95, texture_size=2048); glb.export('<output_dir/model.glb>')"
engines/3d/text-to-cad)Generate parametric CAD geometries and mechanical parts using build123d python scripts and the step compilation CLI.
# Step 1: Write parametric build123d script (<generator.py>):
# e.g., define geometry with build123d and export or pass to compiler
# Step 2: Compile generator script to STEP and GLB:
python engines/3d/text-to-cad/skills/cad/scripts/step <generator.py> -o <model.step> --glb <model.glb>
# Step 3: Inspect geometry facts and bounding planes (optional QA):
python engines/3d/text-to-cad/skills/cad/scripts/inspect refs <model.step> --facts --planes
Select the appropriate engine and command pipeline based on input fidelity and hardware availability:
Rapid Real-Time Proxies / Draft Meshes (<1s):
python engines/3d/triposr/run.py <image_path> --output-dir <output_dir> --model-save-format glb --bake-texture)..glb or .obj for immediate stage placement.High-Fidelity Visual Props & Hero Assets:
python engines/3d/trellis/example.py --image <image_path> --output <output_dir/model.glb>)..glb with UV maps for Unreal Engine or TouchDesigner.Parametric Engineering & Mechanical Parts:
build123d generator, then compile with python engines/3d/text-to-cad/skills/cad/scripts/step <generator.py> -o <model.step> --glb <model.glb>..step CAD model and companion .glb.Execute directly via verified fallback mechanisms when hardware constraints or specific geometry requirements dictate:
CUDA Acceleration Unavailable (CPU-Only Environments):
--device cpu:
python engines/3d/triposr/run.py <image_path> --output-dir <output_dir> --model-save-format glb --bake-texture --device cpucomfyui-mcp (AOS ships no config for it: check it is configured in the harness first, as pb-image-to-3d does) or use an external cloud inference API endpoint.Parametric CAD & Complex NURBS Modeling:
build123d is unsuitable for complex freeform surfaces, use bdb_rhino_mcp_fallback (Rhino Grasshopper solvers, NURBS surfaces, curves, boolean operations, STEP/IGES export).High-Fidelity Scene Assembly & Spatial Staging:
bdb_unreal_mcp or bdb_td_minddesigner (create_3d_scene, create_point_cloud) to arrange, light, and render generated 3D assets in real time.Godmode 3D Creation generates 3D assets, meshes, and CAD models using local Python CLI engines (TripoSR, TRELLIS, Text-to-CAD) and verified ecosystem MCP servers (Rhino, TouchDesigner, Unreal).
.glb, .obj, or .step output file on disk.| Rationalization | Reality |
|---|---|
| "I'll use TRELLIS for this quick draft." | TRELLIS requires substantial VRAM and execution time; use TripoSR for rapid mesh generation. |
| "I'll just guess the Text-to-CAD dimensions." | Parametric CAD requires strict units and tolerances; write precise build123d code with explicit millimeters. |
| "It previewed fine as an OBJ, we don't need textures." | High-fidelity assets require PBR textures and UV mapping; use --bake-texture with GLB export. |
| "CUDA is missing, so 3D generation is impossible." | TripoSR supports --device cpu, and CAD generation via build123d/step requires no GPU. |
--device cpu when running TripoSR on non-CUDA systems.cuda or cpu) is specified..glb, .obj, .step) matches the target pipeline.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
Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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 when a hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
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。
Reference for how BDB structures autonomous software engineering work — the seven-node dispatcher graph (Architect, TechLead, UI/UX, Engineering, Media/EventTech, Reviewer, Shipping) that /startcycle-graph actually runs. Use when you need the high-level lifecycle framing without inventing your own process.
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。
Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling.
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。
Harness patterns for coding agents — memory, permissions, context engineering, delegation, skills, hooks, bootstrap.
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。
agenttrail: live map of a multi-agent build in the browser: which plan component is being worked on, by which agent or harness, what is done and what is stuck. Use when a multi-agent pipeline starts (/startcycle, /startcycle-graph, /teamwork-preview) or after a plan-canvas approve, when the user asks to see what the agents are doing ("live map", "build board", "who is running now"), or by yourself whenever a multi-agent run is under way — no user prompt needed.
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。