Openclaw Skills' Drawing Diff Analyzer compares 2D engineering drawings with 3D models, detects dimension and outline mismatches, and generates review-ready JSON and Markdown reports.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install skill-drawing-diff-analyzer
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install skill-drawing-diff-analyzer using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Drawing Diff Analyzer?
Openclaw Skills' Drawing Diff Analyzer is a script-driven quality review skill for engineering teams that need to verify a 2D drawing against a 3D model before release. It extracts measurable geometry, recognizes dimension notation such as Ø, R, and ±, and highlights differences that could impact fit, function, or manufacturability.
It supports common CAD and document formats including DWG, DXF, PDF, STL, STEP, and IGES, then turns the comparison into both structured machine-readable output and a readable Markdown summary. The result is a faster, more repeatable design-review workflow with less manual checking and clearer handoff for downstream stakeholders.
Drawing Diff Analyzer Use Cases
- Reviewing a 2D engineering drawing against a 3D model during design approval
- Catching dimension drift, contour deviation, and GD&T inconsistencies before release
- Parsing DWG, DXF, or PDF drawings and comparing them to STL, STEP, or IGES models
- Running repeatable quality checks in a scripted workflow with a tolerance gate
- Producing both JSON for downstream automation and Markdown for human review
- Rechecking precision parts with tighter thresholds such as
--tolerance 0.05
How Drawing Diff Analyzer Works
- Load the 2D file and extract entities, annotations, dimension types, and geometric tolerances from the drawing source.
- Load the 3D file and extract vertices, edges, faces, and bounding-box dimensions from the model source.
- Normalize both feature sets, identify notation such as Ø, Φ, DIA, R, and ±, and prepare the data for comparison.
- Compare the drawing and the model using the configured tolerance; the default threshold is 0.1 mm, and 3D-to-2D projection defaults to orthographic projection.
- Generate
diff_report.jsonanddiff_report.md, then flag GD&T items and unusual files for manual verification.
Drawing Diff Analyzer Setup
- Create and activate a Python environment.
python -m venv .venv
source .venv/bin/activate
- Install the parser dependencies used by the skill.
pip install ezdxf pdfplumber pymupdf numpy-stl trimesh cadquery
Place the 2D and 3D source files in your working directory and keep paths relative to the project root.
Run the pipeline in order.
python scripts/parse_2d.py --input blueprint.pdf --output features_2d.json
python scripts/parse_3d.py --input model.stl --output features_3d.json
python scripts/compare.py --features-2d features_2d.json --features-3d features_3d.json --output diff_report --tolerance 0.1
- Adjust
--tolerancefor tighter review gates when working with precision parts, for example0.05mm.
Drawing Diff Analyzer Data Schema & Taxonomy
Input artifacts
| Type | Supported formats | Purpose |
|---|---|---|
| 2D drawing | DWG, DXF, PDF | Source for contour, dimension, and tolerance extraction |
| 3D model | STL, STEP, IGES | Source for geometry and bounding-box extraction |
Generated files
| File | Produced by | Key contents | Notes |
|---|---|---|---|
features_2d.json |
parse_2d.py |
entities, dimensions, geometric_tolerances |
Captures lines, circles, arcs, dimensions, and GD&T callouts |
features_3d.json |
parse_3d.py |
vertices, edges, faces, bounding-box dimensions | Represents the measurable 3D model feature set |
diff_report.json |
compare.py |
structured difference results, deviation values, tolerance status | Best for automation, gating, and downstream tooling |
diff_report.md |
compare.py |
human-readable review summary and findings | Best for design-review sharing and sign-off |
Metadata taxonomy
- Dimension types: linear, angular, diameter (Ø / Φ / DIA), radius (R), and toleranced dimensions (±)
- Geometric tolerances: position, perpendicularity, parallelism, flatness, straightness, circularity, cylindricity, concentricity, symmetry, angularity
- Comparison dimensions: size deviation, outline deviation, tolerance gate result, and manual review flag
- Validation rule: geometric tolerances are recorded and marked for human verification; they are not fully auto-approved by the 3D model
- Projection rule: 2D comparisons assume orthographic projection by default
Data flow
parse_2d.py and parse_3d.py create normalized feature files, and compare.py consumes those files to produce the final diff artifacts used in Openclaw Skills workflows.
Drawing Diff Analyzer Advanced Features
- Tolerance-driven comparisons with per-run threshold control via
--tolerance - Dual-format reporting:
diff_report.jsonfor automation anddiff_report.mdfor stakeholder review - Multi-format ingestion across DWG/DXF/PDF and STL/STEP/IGES
- Dimension-aware parsing that understands Ø, Φ, DIA, R, and ± notation
- GD&T recognition for position, perpendicularity, parallelism, flatness, and related callouts, with human-in-the-loop validation
- Script-first pipeline that can be embedded in larger quality-control or release workflows
- Reference-backed formatting guidance through
references/format-guide.md
SKILL.md
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