Implicit.js is an open source library that lets agents generate CAD with code + mathematical functions representing surfaces. No CAD kernels, no STEP files — just agents using math + code to directly generate 3D models.
Some awesome things about implicit CAD:
• No CAD kernels (Parasolid, OpenCascade, etc.): the math + code is the model.
• They are FAST: the https://www.implicit.sh/ demo compiles and renders models from GLSL in the browser in realtime.
• Representations are small: implicit code can be 100x smaller than STEP files.
Implicits are great at:
• Manipulating complex geometry
• Producing high resolution, scaled CAD models
• Boolean / offset operations
But they are really hard for humans to intuit, which is why we prefer vanilla CAD that works more like LEGO: faces, edges, holes, cuts, fillets, etc., with human-readable topology.
Agents, on the other hand, are very, very good at coding and math — the two key ingredients for implicits.
The third ingredient is visual / spatial reasoning. While lacking today, I believe for many reasons (including robotics) this will be the next frontier that labs pursue.
To caveat: agents aren’t great at implicits today. Frontier models are still pretty blind, so implicits break down on complex parts/assemblies with visual feedback (code → model → screenshot → repeat). There is also no easy toolchain to inspect implicits because they lack topology.
That said, 6 months ago the models couldn’t write reliable code. Things are changing fast, and I think 2026 will be the year the models solve 3D design.
I also think it’s possible (and even probable) that implicit CAD becomes the preferred way for models to do 3D design.
Special thanks to Blake Courter and the Gradient Control team for teaching me about implicits and sharing the Python primitives used to build this library. Blake is the GOAT of implicit CAD and gave an excellent talk on this exact topic at Kinetic a few weeks ago.
step.parts is an open source directory of 12,000+ STEP parts for your next CAD project.
Many CAD tools like Autodesk have huge closed libraries of standard mechanical and electrical parts.
The goal is to build an equivalent catalog for the open source CAD community (that’s easy for humans and agents to use).
The directory is seeded from dozens of existing open source catalogs and generators, catalogued and organised by family, standard, size, etc.
The directory also includes an API, llms.txt and skill to make it easy for agents to download relevant STEP files in generative CAD tools. I’ve added the skill to my text-to-cad repository:
Not intentionally deceptive, the prompts are just too big to include on the home page!
I actually used GPT 5.5 Pro to generate the prompts from simpler one sentence prompts, so hypothetically it’s just an extra step in the harness for an agent to unpack / add detail to a prompt based on the user’s goal.
Hi all, repo author here, appreciate the kind words and feedback!
I'm brushing up on robotics after spending the last 10 years working in software land. After being humbled by modern CAD tools like Onshape, I built this harness / skill to help me generate some basic CAD models for a 7dof robot arm I'm designing.
It ended up working much better than I expected, particularly on the latest GPT 5.5 and Opus 4.7 models. It's been a lot of fun to work on. I've learned a lot about how STEP files work (opencascade, breps, etc) as well as 3d rendering tools like threejs.
I don't have much intention of turning this into a business, it's really just a fun open source tool that I'll continue to maintain as long as myself and others find it useful. Very open to ideas and contributions.
P.S. I just pushed a major update that improves the workflow and scripts/tools for the CAD skill. I also added some basic benchmarks to start measuring performance over time.
The purpose of this repo (harness and skills) is really to just give the models more direct tools to generate and inspect STEP files. It basically generates a topology sidecar for every STEP file that can be used to quickly read the BREP (faces/edges/vertexes) without loading in the full STEP.
There's also a bunch of work going into the SKILL.md to plan for more complex parts (this is mostly a stop gap while the models don't have amazing spatial reasoning).
I appreciate that effort, seeing Claude start to prototype physical objects that can get mass-produced is unbelievable but wow it uses up tokens like crazy.
I'm using Opus 4.7 w/ the 1M context option on the vibrating mesh nebulizer repo and have hit compacting pretty often which is a restart-the-conversation flag for me on relatively small OpenSCAD files like the adapters and enclosures here which are like 10-40kb: https://github.com/dmchaledev/VibratingMeshNebulizerControll...
Used about 200k tokens in 30 minutes. You can view the generated implicit model here: https://www.cad.fun/?file=implicits%2Fpelican-bicycle.implic...
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