lab-hardware-cad
No security findings. Scanned 1 time, most recently 2026-10-21.
Second scanner: NVIDIA SkillSpector
Independent static run, no language model, over the same files as the Cisco scan above. How the two scanners compare across the whole corpus: Two scanners, one corpus.
What this skill does
Designs custom laboratory hardware as parametric build123d models and exports fabrication artifacts as STEP, STL, and DXF files - microfluidic chips and molds, optomechanical mounts and breadboard adapters, cuvette and microplate holders, tube racks, animal-behavior rigs, and 3D-printed instrument fixtures. Use when a research task needs a physical part that must mate with standardized labware, an optical table, a cage system, or a printer, CNC, or laser process.
- Package
- 13 files, 184 KB
- SKILL.md
- 3223 words, 12+ sections
- Code
- Python (4)
- Allowed tools
ReadWriteEditBashGlobGrep- License
- MIT
- Compatibility
- Python 3.11-3.14 with build123d 0.13.0 and matplotlib for snapshots. Geometry commands require build123d; the standards lookup and the interface check run on the standard library alone. Network needed for installation and current vendor drawings; local geometry checks run offline.
SKILL.md covers: Lab Hardware CAD · When to use · Setup · Required workflow · 1. Route to a device family · 2. Establish the interface dimensions before any geometry · 3. Choose the process before choosing the geometry · 4. Author a parametric model · --- INTERFACE (fixed by standard; do not tune) --- · --- DESIGN (free) --- · 5. Generate and run the checks · 6. Snapshot and actually look at it
Findings
No findings. SAFE
What is in the package
| File | Kind | Size |
|---|---|---|
SKILL.md | doc | 22 KB |
assets/standards.json | config | 17 KB |
references/behavior-rigs.md | doc | 7.6 KB |
references/build123d-patterns.md | doc | 18 KB |
references/fabrication-limits.md | doc | 9.0 KB |
references/labware-adapters.md | doc | 11 KB |
references/microfluidics.md | doc | 9.5 KB |
references/optomechanics.md | doc | 7.2 KB |
references/validation.md | doc | 6.7 KB |
scripts/_common.py | script | 27 KB |
scripts/check.py | script | 28 KB |
scripts/gen.py | script | 10 KB |
scripts/snapshot.py | script | 11 KB |
External hosts referenced
www.slas.org www.thorlabs.com arxiv.org build123d.readthedocs.io formlabs.com www.hellma.com www.iso.org documents.thermofisher.com doi.org export.arxiv.org github.com nc3rs.org.uk occt3d.com shop.brand.de www.idex-hs.com www.thermofisher.com
Hostnames that appear in the skill's files. Referencing a host is not a finding; compare against the findings above and the skill's stated purpose.
Package contents recorded 2026-10-22 at commit 593377bb0487. The scan above ran against the version current at scan time; the two can differ if the skill has since been updated.
What we checked
- Static analyzer. Pattern rules over SKILL.md and bundled files: known-bad commands, exfiltration URLs, secrets, obfuscation.
- Bytecode analyzer.
- Pipeline analyzer.
- Correlation analyzer.
- Behavioral analyzer. Checks what the skill asks the agent to do against what its description claims it does.
- Trigger analyzer. Looks for instructions that fire on conditions the user did not ask for.
What we did not check
- Runtime behaviour. The skill was not executed; findings come from reading its files.
- Anything fetched at install or run time, including remote scripts, package dependencies, and URLs the skill tells the agent to open.
- Content the analyzers cannot read: images, binaries, and some non-English text.
- Known scanner bypass classes. See the methodology and limitations page.
Sources
- Repository: https://github.com/K-Dense-AI/scientific-agent-skills
- Raw scan result: skills-lab-hardware-cad-scan.json
- Badge for your README:
- Request a re-scan