What makes Agentcad Skill V050.Ta0dYt notable?

2K downloads. Trust evidence available

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Agentcad Skill V050.Ta0dYt

CAD tool for AI agents. Use when the user asks you to design, model, or build a 3D object. agentcad executes build123d Python scripts and produces STEP files, PNG renders, mesh exports (STL/GLB/OBJ), and geometric metrics. Skill: Agentcad Skill V050.Ta0dYt Owner: jdilla1277 Summary: CAD tool for AI agents. Use when the user asks you to design, model, or build a 3D object. agentcad executes build123d Python scripts and produces STEP files, PNG renders, mesh exports (STL/GLB/OBJ), and geometric metrics. Tags: cad:0.5.0, latest:0.5.0, stable:0.5.0 Version history: v0.5.0 | 2026-09-03T10:24:10.235Z | user Clearer, safer CAD editing v0.4.1

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

2.0k

Updated

Oct 9, 2026

Version

0.5.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 2K downloads reported by the source. Last updated 10/9/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 9, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 9, 2026
Adoption signal: 2K downloadsadoption · observed Oct 9, 2026
Latest release: 0.5.0release · observed Sep 3, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s17a7cme8f0cnkjade7j6fmns1858ej4:agentcad

Setup complexity is classified as HIGH. You must provision dedicated cloud infrastructure or an isolated VM. Do not run this directly on your local workstation.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-jdilla1277-agentcad/snapshot"

Documentation

CLAWHUB

117,566 characters of source documentation, loaded on request.

Extracted files

4 files captured from the source.

SKILL.md

---
name: agentcad
description: 'CAD tool for AI agents. Use when the user asks you to design, model,
  or build a 3D object. agentcad executes build123d Python scripts and produces STEP
  files, PNG renders, mesh exports (STL/GLB/OBJ), and geometric metrics.

  '
compatibility: Requires Python 3.10-3.12 and agentcad installed (pip install agentcad).
allowed-tools: Bash(agentcad:*)
version: 0.5.0
metadata:
  openclaw:
    requires:
      bins:
      - agentcad
      anyBins:
      - python3.12
      - python3.11
      - python3.10
---

# agentcad — CAD tool for AI agents

You have access to `agentcad`, a CLI that turns build123d Python scripts into 3D
geometry. All output is JSON. Every command returns `"command"` and `"status"` keys.

## First-time setup

```bash
agentcad init --name <project_name>
agentcad --help   # Read the built-in how-to guide and command reference
```

## Core workflow

1. **Write a script.** No imports needed — build123d primitives,
   `show_object`, and agentcad edit helpers are pre-injected by default.
   `show_object(result)` is required.

2. **Dry-run first** to check metrics without consuming a version:
   ```bash
   agentcad run script.py --label test --dry-run
   ```
   Check `volume`, `dimensions`, `is_valid` in the response.

3. **Run for real.** Visual feedback is on by default:
   ```bash
   agentcad run script.py --label label
   ```
   A normal successful iteration can produce (paths in the JSON response):
   - `preview.png` — balanced top, bottom, upper-iso, and lower-iso composite.
     **Read this** to confirm the part looks right before iterating. The lower
     views expose geometry that a top view can hide.
   - `diff.side_by_side` — side-by-side PNG vs the most recent successful prior
     version, when one exists and automatic diff is enabled. **Read this** when
     iterating to see what your change did.
   - `diff.overlay` — centered 2D visual-overlap map (coincident gray,
     reference-only blue, candidate-only orange). It helps locate silhouette
     changes but does not prove physical correctness or shared 3D volume.
   - `viewer.html` — interactive 3D review viewer for the user unless viewer
     artifacts are disabled (humans only;
     you can't render HTML). It opens automatically after a successful run.
     From v2, A=previous and B=current are already loaded with synchronized
     A/B, side-by-side, overlay, diff-image, and Parts-tab change review.

   Pass `--no-preview` only for tight parametric sweeps where latency matters.
   Pass `--no-view` only when browser launch would disrupt an unattended or
   high-volume run.

   For a core-only iteration, pass
   `--no-preview --no-diff --no-view`. This writes `output.step`, the saved
   script, `meta.json` (including metrics), and explicitly requested exports
   without generating previews, automatic comparisons, viewer assets, or
   opening a browser. You can still run an explicit
   `agentcad diff OLD NEW` later.

   When a comparison is s

README.md

# agentcad-skill

The **agent skill manifest** for [agentcad](https://agentcad.dev) — a CLI-based CAD tool for AI agents.

This repo is the public entry point for agent skill marketplaces ([ClawHub](https://clawhub.ai/), [skills.sh](https://skills.sh)). It contains only the `SKILL.md` manifest — the agentcad CLI itself lives at [jdilla1277/agentcad](https://github.com/jdilla1277/agentcad) and ships via PyPI.

## Install

### skills.sh (Vercel)

```bash
npx skills add jdilla1277/agentcad-skill
```

### ClawHub (OpenClaw)

```bash
clawhub install jdilla1277/agentcad
```

### Manually (Claude Code)

Install the CLI and let it drop the skill into your project:

```bash
pip install agentcad
agentcad skill install
```

## What agentcad does

Agents write bad 3D geometry on the first try. agentcad gives them a tight feedback loop — run, render, inspect, fix — so they converge on printable geometry without you babysitting.

- **Execute** — run CadQuery Python scripts, produce versioned STEP files + geometric metrics
- **Render** — PNG views from any angle for visual verification
- **Export** — STL, GLB, OBJ for 3D printing and web viewers
- **Validate** — pre-execution checks catch errors in <100ms
- **Inspect** — topology report for debugging geometry issues
- **Diff** — compare versions to track design iteration

See [agentcad.dev](https://agentcad.dev) for the full pitch and live gallery.

## Requirements

- Python 3.10–3.12 (CadQuery/OpenCascade does not support 3.13+)
- `agentcad` CLI on `$PATH` (`pip install agentcad`)

## License

The skill manifest in this repo is licensed under Apache-2.0.

The agentcad CLI itself is open source under [Apache-2.0](https://github.com/jdilla1277/agentcad/blob/main/LICENSE).

## Source

- CLI source: [github.com/jdilla1277/agentcad](https://github.com/jdilla1277/agentcad), distributed via [PyPI](https://pypi.org/project/agentcad/).
- Skill manifest: this repo. Generated from the public CLI repo on each release.
- Feedback / issues: run `agentcad feedback "your message"` from inside a project, or file an issue here.

_meta.json

{
  "ownerId": "kn7e37871wa8zg6kgsfctevr59859sx9",
  "slug": "agentcad",
  "version": "0.5.0",
  "publishedAt": 1788431050235
}

skill-card.md

## Description:

CAD tool for AI agents that helps design, model, and build 3D objects by executing build123d Python scripts and producing STEP files, PNG renders, mesh exports, and geometric metrics.

This skill is ready for commercial/non-commercial use.

## Publisher:

[jdilla1277](https://clawhub.ai/user/jdilla1277)

### License/Terms of Use:

MIT-0

## Use Case:

Developers and engineers use this skill to create and iterate on CAD models through agent-authored Python scripts, visual previews, geometry metrics, inspection, measurement, diffing, and export workflows.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: The skill runs the local agentcad CLI and depends on the installed agentcad package.

Mitigation: Install agentcad from a trusted source and pin or verify the package where possible.

Risk: Default successful runs may open a browser viewer and create preview, diff, and viewer artifacts.

Mitigation: Use --no-view, or --no-preview --no-diff --no-view, in automation or sensitive environments.

Risk: Generated CAD geometry can be invalid, visually misleading, or fail explicit dimensional requirements.

Mitigation: Review previews and metrics, then use inspect, measure, diff, and check-spec before final handoff.

## Reference(s):

- [ClawHub skill page](https://clawhub.ai/jdilla1277/skills/agentcad)
- [agentcad documentation and gallery](https://agentcad.dev)
- [agentcad PyPI package](https://pypi.org/project/agentcad/)

## Skill Output:

**Output Type(s):** [code, shell commands, configuration, guidance]

**Output Format:** [Markdown guidance with Python and shell command snippets; agentcad CLI commands return JSON and generated CAD artifacts.]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [Can guide creation of STEP files, PNG previews, STL/GLB/OBJ mesh exports, viewer artifacts, meta.json metrics, and spec.json checks through the agentcad CLI.]

## Skill Version(s):

0.5.0 (source: frontmatter and server release metadata)

## Ethical Considerations:

Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.

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