Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/k-dense-ai/scientific-agent-skills/lab-hardware-cadnpx skills add K-Dense-AI/scientific-agent-skills --skill lab-hardware-cadgit clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-skillsWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00106 | $0.05094 |
| Opus 5 | $0.00053 | $0.02547 |
| Sonnet 5 | $0.00021 | $0.01019 |
| Haiku 4.5 | $0.00011 | $0.00509 |
Grade A, and why
lab-hardware-cad scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 373 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lab Hardware CAD
Design physical research hardware as parametric Python source, export STEP as the authoritative artifact, and verify the result both numerically and visually before anything is fabricated.
The hard part of lab hardware is almost never the geometry. It is that the part must mate with equipment whose dimensions are fixed by a published standard or a vendor drawing. A holder that is 0.5 mm too wide does not fit the plate reader; a channel with the wrong aspect ratio collapses during bonding; a mount whose bolt pattern is 25.4 mm instead of 25.0 mm will not reach the optical table. This skill exists to keep those numbers correct and checked.
When to use
Use for any request to design, model, or fabricate a physical part for a lab: chip, mold, mount, adapter, holder, rack, bracket, enclosure, jig, fixture, arena, or maze. Also use to inspect or modify an existing STEP file.
Do not use for finite-element analysis, computational fluid dynamics, molecular structure, or scientific plotting. Those are different skills.
Setup
uv venv --python 3.12 .venv-labcad
uv pip install --python .venv-labcad/bin/python "build123d==0.11.1" "matplotlib>=3.8"
build123d 0.11.1 requires Python >=3.10,<3.15 and pulls in the OpenCascade kernel through
cadquery-ocp-novtk. The wheel is large; install once per project and reuse it.
All bundled scripts take --help. check.py standards runs without build123d installed.
Model files are executed, not parsed. gen.py, check.py, and snapshot.py import a
*_model.py and call its build(), which runs arbitrary Python in the current environment. That
is inherent to parametric CAD — the source is the design. Only run model files authored in this
session or supplied by the user from a trusted location. If a model came from the internet, a
shared drive, or an untrusted colleague, read it before running it and say that you did.
Required workflow
Follow these steps in order. Steps 5 and 6 are not optional, and step 6 is not waived by step 5 passing.
What ships with it
12 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- assets/standards.json 13 KB
- references/behavior-rigs.md 7.2 KB
- references/build123d-patterns.md 16 KB
- references/fabrication-limits.md 7.9 KB
- references/labware-adapters.md 9.3 KB
- references/microfluidics.md 8.3 KB
- references/optomechanics.md 7.0 KB
- references/validation.md 6.5 KB
- scripts/_common.py 24 KB runs code
- scripts/check.py 27 KB runs code
- scripts/gen.py 11 KB runs code
- scripts/snapshot.py 11 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 373 lines · 106 tokens per session scan A b89d796cfc8e
lab-hardware-cad is a skill published in the GitHub repository K-Dense-AI/scientific-agent-skills (40,390 stars, last pushed yesterday), licensed MIT. It adds 106 tokens to every session and 5,094 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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