Best prompts for text-to-CAD: what I've learned so far

Around prompt number fifty, I started keeping a spreadsheet. Nothing fancy. Just the prompt text, which tool I used, a rating from 1 to 5 on how usable the output was, and a short note about what went right or wrong. I did this because I was losing track of which phrasing produced good results and which phrasing produced the geometric equivalent of a drunk guess. My desk had a growing folder of STEP files labeled things like "bracket_v7_better.step" and "bracket_v8_actually_worse.step" and I needed to stop relying on my memory, which is unreliable at the best of times and completely useless after six hours of staring at imported solids.

After a few hundred prompts, logged and rated, patterns show up. Some types of prompts consistently produce parts worth importing. Others consistently produce garbage, and no amount of rewording fixes them. This post is the good ones. The prompts that have actually worked for me, with enough context that you can adapt them to your own parts.

For the theory behind why these work, the text-to-CAD prompt engineering post covers the principles. This is the recipe book.

The plate prompt#

This is the one I come back to most often, because plates with holes are the bread and butter of fixturing, test rigs, and prototype assemblies. It's also the category where text-to-CAD is most reliable.

Prompt: "Rectangular plate, 80mm x 50mm x 5mm. Four M4 counterbore holes at the corners, hole centers 5mm from each edge. Counterbore diameter 8mm, counterbore depth 3mm, through-hole diameter 4.3mm. 2mm x 45° chamfer on all edges of the top face."

This prompt consistently produces a usable part. The plate dimensions come back close to correct. The counterbores are usually the right diameter and depth. The hole positions are within a millimeter of where they should be, which is close enough to fix quickly. The chamfers sometimes get applied to the wrong edges or only to some edges, which is a common text-to-CAD failure mode, but the overall part is 85-90% correct.

Why it works: every dimension is explicit. The feature type (counterbore) is named correctly. The hole positions are given as distances from edges, which is unambiguous. The chamfer spec uses standard notation.

The L-bracket prompt#

Brackets are the second most common thing I generate with text-to-CAD, and L-brackets specifically are well within the AI's comfort zone.

Prompt: "L-shaped bracket, 3mm thick. Vertical leg 40mm tall by 30mm wide. Horizontal leg 50mm long by 30mm wide. Inside bend radius 3mm. Two 4.2mm through-holes on the vertical leg, centered horizontally, 10mm and 30mm from the top edge. Two 4.2mm through-holes on the horizontal leg, centered across the width, 10mm and 40mm from the bend."

Typical result: the overall shape is correct. The thickness is spot on. Leg dimensions are usually within a millimeter. The holes are close but I've seen the spacing drift by up to 2mm, especially on the horizontal leg where the "from the bend" reference seems to confuse some tools. The bend fillet appears most of the time, though occasionally it comes out as a sharp corner. Fix time is usually under three minutes.

Why it works: the L-shape is described by its legs rather than as an abstract shape. Each leg has its own dimensions. Hole positions reference specific edges. The bend radius is specified.

The standoff prompt#

Small cylindrical parts test whether the AI can produce clean bodies of revolution, and standoffs are simple enough that the results are usually good.

Prompt: "Cylindrical standoff, 15mm outer diameter, 25mm tall. M4 internal thread (4.2mm through-hole for clearance). 1mm chamfer on both ends of the outer diameter."

The through-hole comes back correct almost every time. The outer diameter is reliable. The height is usually right. The chamfers are the weak point, sometimes only applied to one end or not at all. No tool I've tested actually generates thread geometry, so you get a smooth bore, which is what I expected. Fix time is under a minute if the chamfers need redoing.

Why it works: simple geometry with a single axis of symmetry. All dimensions are absolute. The feature list is short.

The electronics enclosure prompt#

This is where things get harder, and the prompt has to work harder to compensate.

Prompt: "Rectangular open-top box, outer dimensions 80mm x 50mm x 25mm. Wall thickness 2mm, bottom thickness 2mm. Four M2.5 boss features at the inside corners, boss outer diameter 5mm, boss height 20mm (from inside bottom), with 2.8mm through-holes centered on each boss. Two M3 mounting tabs extending 8mm from the bottom of the long sides, centered on each side, 3mm thick, with 3.5mm through-holes centered on each tab."

This is the longest prompt in my regular rotation, and the results are the most inconsistent. About half the time, the box comes out with correct outer dimensions and wall thickness. The bosses appear most of the time but their positions are sometimes wrong, floating near the corners rather than actually at the corners. The mounting tabs are the most common failure: they either don't appear, appear on the wrong faces, or appear at the wrong dimensions.

On a good generation, this prompt saves me ten minutes of modeling. On a bad generation, I throw it away and model from scratch. The hit rate is about 50-50, which I'll admit is borderline for whether it's worth bothering. I keep using it because the good results save real time and the bad results are obvious within thirty seconds of importing.

Why it sometimes works: the dimensions are specific and the features are described in detail. Why it sometimes doesn't: the AI struggles with features that reference the inside of a shell, and boss placement at corners requires understanding containment relationships that current tools handle unreliably.

The mounting plate prompt#

A simpler version of the plate prompt, optimized for the case where you need a flat part with a specific bolt pattern and a central feature.

Prompt: "Square plate, 60mm x 60mm x 3mm. Central through-hole 22mm diameter, centered. Four 3.2mm through-holes on a 31mm square bolt pattern, centered on the plate. 1mm chamfer on all edges of both faces."

This is my NEMA 17 motor mount prompt, and I've used it enough times that I know its failure modes by heart. The central hole is always correct. The plate dimensions are always close. The bolt pattern comes back within a millimeter of 31mm about 70% of the time, and off by 2-3mm about 30% of the time. The chamfers sometimes only appear on the top face. Fix time: two to four minutes, mostly spent correcting the bolt pattern when it drifts.

The cable clip prompt#

I keep this one around for quick desk and test rig accessories. Cable management parts are the guilty pleasure of text-to-CAD because they're simple, low-stakes, and satisfying when they work.

Prompt: "Cable clip for 8mm cable. C-shaped profile, 12mm outer diameter, 8.5mm inner diameter, 3mm wall thickness, opening gap 5mm. Base tab extending 10mm below the clip, 12mm wide, 2mm thick, with a 3.5mm mounting hole centered on the tab, 5mm from the bottom edge."

This produces usable geometry about 75% of the time. The C-profile is recognizable. The inner and outer diameters are usually close. The opening gap varies more than I'd like, sometimes 4mm, sometimes 6mm. The base tab is the most reliable part. Overall, it's the kind of part where "close enough" actually is close enough, especially for 3D printing.

The shelf bracket prompt#

A slightly more complex bracket that tests the AI's ability to handle three orthogonal features.

Prompt: "Right-angle shelf bracket. Vertical plate 60mm tall, 40mm wide, 3mm thick. Horizontal shelf 50mm deep, 40mm wide, 3mm thick. Triangular gusset connecting the vertical plate to the shelf, 30mm along each leg, 3mm thick. Two 5mm through-holes on the vertical plate, centered horizontally, 10mm and 50mm from the bottom. One 5mm through-hole on the horizontal shelf, centered across the width, 25mm from the back edge."

The gusset is what makes this interesting. About half the time, the AI includes it with roughly correct dimensions. The other half, it either omits the gusset entirely or produces something that vaguely resembles a triangle but isn't attached properly to both plates. When the gusset works, the part is genuinely useful. When it doesn't, the bracket is still a valid L-bracket with holes, just missing the reinforcement.

Prompt patterns that consistently work#

After logging all these prompts and results, here are the patterns I've noticed.

Describe the overall shape first, then features. The AI seems to build the base geometry from the first part of the prompt and add features from the rest. Starting with "rectangular plate, 80mm x 50mm x 5mm" and then adding holes works better than starting with "a part with four holes and chamfers that is 80mm by 50mm."

Use absolute positions, not relative ones. "10mm from the left edge" works better than "evenly spaced" or "near the corners." Every time I use relative language, the AI interprets "near" differently than I do.

Reference edges, not abstractions. "Centered across the 30mm width" works better than "centered horizontally," because "horizontally" depends on orientation. Edge references are unambiguous.

Repeat the total count of features. "Four M4 through-holes" is better than listing four holes individually. Pattern language matches CAD operations and produces more consistent spacing.

State symmetry explicitly. "Two slots, symmetric about the vertical center plane" produces more consistent results than describing two slots with mirrored coordinates.

Keep prompts under about 100 words for simple parts and under about 150 words for complex ones. Beyond that length, the AI starts losing track of earlier details. If your prompt needs to be longer than 150 words, the part might be too complex for current text-to-CAD tools.

Prompt patterns that consistently fail#

Vague sizing. "A small bracket," "a medium-sized plate," "about yay big." The AI has no idea what these mean and neither does your machinist.

Relative positioning without anchors. "The holes should be evenly spaced" without saying how many, what the spacing is, or what they're evenly spaced relative to.

Multi-part descriptions. "A box with a snap-fit lid" always fails. Always. Generate them separately.

Functional descriptions instead of geometric ones. "A bracket that can hold 5kg" tells the AI nothing about geometry. It doesn't know physics. It doesn't know load paths. Describe the shape, not the job.

Complex curves. "An airfoil shape" or "a smooth organic transition" or anything involving splines. Current tools don't generate reliable freeform surfaces from text.

Referencing standards without dimensions. "An M5 counterbore" works sometimes because the AI has seen M5 specifications in training data. "A counterbore for a #10-32 socket head cap screw" is too specific to a lookup table and usually fails. When in doubt, provide the actual dimensions rather than expecting the AI to look up standards.

My personal favorites#

If I had to pick five prompts to demonstrate text-to-CAD to someone who's never tried it, I'd use these:

1. The plate prompt from above. It works 90% of the time and demonstrates that the tool can produce genuinely useful geometry.

2. The L-bracket prompt. Shows that the AI handles multi-feature parts with position references.

3. "Cylinder, 20mm diameter, 40mm tall, with a 6mm through-hole centered on the axis and a 1mm chamfer on both ends of the outer diameter." Simple body of revolution. Works nearly every time.

4. "Rectangular tube, outer dimensions 30mm x 20mm x 80mm long. Wall thickness 2mm. Open on both ends." Tests shell geometry without complex features. Usually correct.

5. The cable clip prompt. Shows that the AI can handle C-shaped profiles and attached tabs.

For more prompt/output pairs with detailed analysis, the text-to-CAD examples post shows ten prompts and what they actually produced. For the underlying theory, the text-to-CAD prompt engineering post explains why these patterns work. And the text-to-CAD guide puts all of this in the context of the broader technology and workflow.

The honest bottom line: good prompts produce good starting points, not finished parts. But the difference between a good starting point and a bad one is the difference between a three-minute fix and a ten-minute rebuild. Over a week of prototyping, those minutes add up. My spreadsheet says I've saved about four hours total across two months of regular use. Not life-changing. But not nothing, either. And the prompts keep getting better as I learn what the tools respond to. That's the part that keeps me trying the next one, even when the last one came back looking like the AI had a bad day.