text-to-cad
A library of agent skills for CAD, CAE and CAM
Not yet verifiedsource: GitHubPythonMITcommit 4eaf7459a95c
Python, MIT licensed. The project labels itself: agents, ai agents, cad, mechanical engineering, robotics, step, stl and stp.
text-to-cad has not been verified yet.
Measured by Argusic on a fresh machine every time. Every number links to its evidence. Argusic Score 20 of 100 (the mean of this project's run scores).
At a glance
Subject data from GitHub, linked at the top of this page. Test data by Argusic (CC BY 4.0); every number links to a run page with the full log, the recording, and their sha256 hashes.
What was measured
From the most recent recorded attempt, which did not reach a verdict. Every line is a recorded value, not an estimate.
- Cold machine to finish
- 56 minutes
- Errors hit and fixed
- 0 hit, 0 fixed with no human help
- Exact commit tested
- 4eaf7459a95c
- Container image
- sha256:cdd920bce783
What was not measured
The other half, so you can see exactly how far this evidence goes. A gap is printed as a gap and never filled in.
- Install time
- the run did not report one
- How the result was proved
- runs before 2026-09-07 did not record the command used to check the result
- Peak GPU memory
- this ran on a CPU machine, so there was no GPU to sample
- Model tokens used
- not recorded for this run
- Behaviour over a long run
- each attempt uses the smallest documented settings and a fixed time budget, so this measures whether it runs, not how it holds up under load
- Whether it works at all
- this run verified nothing, so this page makes no claim either way
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
const bytes=encode(component);
const changed=encode({...component,scale:component.scale+1});
console.log(JSON.stringify({key,bytes:Buffer.from(bytes).toString('base64'),
changed:Buffer.from(changed).toString('base64'),
changedSurface:Buffer.from(encode(component,'b'.repeat(64))).toString('base64'),
facts:{schemaVersion:1,object:createHash('sha256').update(bytes).digest('hex'),...api.tessellatio…
}));
"""
result = subprocess.run([node, "--input-type=module", "-e", script, CODEC.as_uri()], capture_ou…
if result.returncode:
raise RuntimeError(result.stderr)
return json.loads(result.stdout)Replay the whole session, every command from a clean machine to this point.
How it was tested
One agent, one container, no human help. It installs the project the way its own documentation says to, runs it, and fixes what breaks. Everything below is recorded as it happened: the terminal session, the log and the exact commit. The full method.
Also tested, in the same area
Every one of these was installed and run by Argusic on a clean machine. Nothing appears here that was not tested.
Run history
| tested by | attempt | outcome | score | cost USD | when |
|---|---|---|---|---|---|
| Argusic Runner | 1/3 | Did not run | 20.00 | 0.13 |
Topics (from GitHub)
agentsai-agentscadmechanical-engineeringroboticsstepstlstptext-to-cad
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/text-to-cad)Questions
- Does text-to-cad run?
- text-to-cad has not been fully verified yet. No recorded run has produced a verdict yet.
- How did Argusic test text-to-cad?
- On a fresh, disposable machine, with every command recorded. One attempt is recorded, and the full method is on the methodology page.
- Where is the evidence for text-to-cad?
- The recorded run is on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.