MCP HubMCP Hub
SKILL·49DDA1

lab-hardware-cad

K-Dense-AI
Обновлено 15 days ago
7 просмотров
38,996
3,647
38,996
Посмотреть на GitHub
Метаdesign

О программе

Этот навык создает параметрические 3D-модели для нестандартного лабораторного оборудования с использованием библиотеки Python build123d. Он генерирует детали, предназначенные для соединения со стандартным лабораторным оборудованием, и экспортирует их в готовые для производства форматы, такие как STEP и STL. Используйте его, когда исследовательская задача требует изготовления нестандартного физического компонента, который должен сопрягаться с существующей лабораторной посудой или механизмами.

Быстрая установка

Claude Code

Рекомендуется
Основной
npx skills add K-Dense-AI/claude-scientific-skills -a claude-code
Команда плагинаАльтернативный
/plugin add https://github.com/K-Dense-AI/claude-scientific-skills
Git клонированиеАльтернативный
git clone https://github.com/K-Dense-AI/claude-scientific-skills.git ~/.claude/skills/lab-hardware-cad

Скопируйте и вставьте эту команду в Claude Code для установки этого навыка

Документация

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.

1. Route to a device family

Read the request, classify it, and load exactly one family reference. Do not load all four — they are long, and mixing conventions between families is a common source of error.

If the part isLoad
A chip, mold, channel network, flow cell, gasket, or anything with fluid portsreferences/microfluidics.md
A mount, post, breadboard adapter, cage-system part, filter or sample holder in a beam pathreferences/optomechanics.md
An adapter, insert, rack, or holder for plates, cuvettes, tubes, slides, or dishesreferences/labware-adapters.md
An arena, maze, head-fixation part, spout, tether, or extrusion-mounted enclosure for animal workreferences/behavior-rigs.md

If the part genuinely spans two families — a microfluidic chip that bolts to an optical table — load the family that owns the critical interface, then read only the interface section of the second. State in your response which family you routed to.

2. Establish the interface dimensions before any geometry

Every part has at least one mating interface. Before writing code, write down for each interface:

  • the source of the dimension: a published standard, a vendor drawing, or a user measurement;
  • the nominal value and tolerance;
  • the clearance or interference you intend, and why.

Look the number up in assets/standards.json or the family reference. Never write an interface dimension from memory. If the number is not in the standards file or the reference, ask the user for the vendor drawing or the measurement rather than guessing. A guessed interface dimension is the single most expensive failure mode in this skill.

A feature that must receive a standardised component is sized against that component's maximum material condition — nominal plus its plus-tolerance — and only then given clearance. Sized from nominal instead, it fits only the smaller half of conforming parts.

python scripts/check.py standards --list
python scripts/check.py standards --show slas-microplate-footprint

3. Choose the process before choosing the geometry

Read references/fabrication-limits.md. Process determines minimum wall, minimum feature, achievable tolerance, and whether the part survives autoclaving or contact with your solvent. FDM cannot hold ±0.05 mm; SLA resin is generally not safe for cell contact without post-cure and testing. Record the process and material in the model docstring.

4. Author a parametric model

Write <part>_model.py. The source is the authoritative artifact — never hand-edit an exported STEP file, and never regenerate from a mesh.

Requirements:

  • Every dimension that a user might change is a module-level named constant with units in the name: bore_d_mm, wall_t_mm, post_h_mm. No bare numbers in the body except 0, 1, and 2.
  • Expose build() -> Part. gen.py calls it.
  • Group parameters into an INTERFACE block (dimensions fixed by a standard, annotated with the standard ID) and a DESIGN block (dimensions you are free to choose).
  • Derive every computed dimension inside a function, never at module level, so --param overrides actually reach it.
  • Declare an interfaces() function returning the dimensions the part must fit, each with its standard ID and intent. This is what makes the interface machine-checkable in step 5.
  • Put the process, material, and every interface source in the module docstring.
"""SLAS microplate carrier for a custom stage insert.

Process: FDM, PETG, 0.2 mm layer.  Tolerance budget +/-0.3 mm.
Interfaces:
  - Plate pocket: ANSI/SLAS 1-2004 (R2012) footprint 127.76 x 85.48 mm, +/-0.25.
  - Stage bolts: user-measured, 40.0 mm centres (drawing in docs/stage.pdf).
"""
from build123d import *

# --- INTERFACE (fixed by standard; do not tune) ---
plate_l_mm = 127.76   # ANSI/SLAS 1-2004 nominal
plate_w_mm = 85.48    # ANSI/SLAS 1-2004 nominal
plate_tol_mm = 0.25   # ANSI/SLAS 1-2004; the pocket is sized to nominal + this
# --- DESIGN (free) ---
pocket_clearance_mm = 0.40   # per-side; FDM, see fabrication-limits.md
wall_t_mm = 3.0
floor_t_mm = 2.5
body_h_mm = 12.0


def pocket_mm() -> tuple[float, float]:
    """Pocket at the plate's maximum material condition plus clearance per side.

    A pocket sized from nominal jams on roughly half of conforming plates.
    """
    growth = plate_tol_mm + 2 * pocket_clearance_mm
    return plate_l_mm + growth, plate_w_mm + growth


def interfaces() -> list[dict]:
    """What this part must fit. `check.py interfaces` verifies every entry."""
    pocket_l, pocket_w = pocket_mm()
    return [
        {"feature": "plate pocket length", "standard": "slas-microplate-footprint",
         "dimension": "footprint_length", "value": pocket_l,
         "intent": "envelope", "clearance": 2 * pocket_clearance_mm},
        {"feature": "plate pocket width", "standard": "slas-microplate-footprint",
         "dimension": "footprint_width", "value": pocket_w,
         "intent": "envelope", "clearance": 2 * pocket_clearance_mm},
    ]


def build() -> Part:
    pocket_l, pocket_w = pocket_mm()
    with BuildPart() as carrier:
        Box(pocket_l + 2 * wall_t_mm, pocket_w + 2 * wall_t_mm, body_h_mm)
        with Locations((0, 0, floor_t_mm)):
            Box(pocket_l, pocket_w, body_h_mm, mode=Mode.SUBTRACT,
                align=(Align.CENTER, Align.CENTER, Align.MIN))
    return carrier.part

See references/build123d-patterns.md for the builder-vs-algebra choice, the interfaces() contract, sketching, selectors, fillets, and threaded-insert bores.

5. Generate and check the interfaces

python scripts/gen.py carrier_model.py --outdir out/
python scripts/check.py facts out/carrier.step
python scripts/check.py interfaces out/carrier.manifest.json

gen.py writes carrier.step (authoritative), carrier.stl (mesh preview and printing), and carrier.manifest.json recording the source hash, resolved parameters, declared interfaces, library versions, and measured bounding box, volume, and validity. The manifest is the provenance record — keep it with the artifact.

check.py facts reports is_valid, bounding box, volume, surface area, centre of mass, and solid count. A part that reports is_valid: false is broken geometry; fix the source before going further.

check.py interfaces is the check that gates fabrication. It evaluates every entry the model declared against the standards database and exits non-zero on failure. Use it rather than check.py fit for anything internal: the interface is almost always a pocket, bore, or slot, and none of those appear in the part's outer bounding box. fit measures that outer envelope, so running it on a carrier reports the outside of the walls and fails against the plate footprint. Reach for fit only to check one number by hand, or when the part's own outline is the interface — a gasket cut to a plate footprint, for instance:

# check one dimension by hand, without a geometry kernel
python scripts/check.py fit --standard slas-microplate-footprint \
  --intent envelope --clearance 0.8 --value footprint_length=128.81

For assemblies, check that parts do not interfere:

python scripts/check.py clearance out/carrier.step out/lid.step --min 0.3

6. Snapshot and actually look at it

python scripts/snapshot.py out/carrier.step --out out/carrier.png

Then read the PNG. This step is mandatory after every generation and every modification. Deterministic checks passing is not a reason to skip it: is_valid and a correct bounding box are both fully consistent with a pocket cut on the wrong face, an inverted mold polarity, a boss placed outside the body, or a fillet that ate a feature. Those errors are obvious in a picture and invisible in the numbers.

The six views are true orthographic projections, and the outlines are the model's real edges drawn without hidden-line removal. So a circle visible "through" material is a bore on the far side, not a window — the part is not transparent. Read it that way rather than reporting a hole that is not there.

State in your response what you saw in the snapshot, not merely that you generated one.

7. Repair through the source

If any check fails, edit the parameters or the model code, rerun gen.py, and rerun both step 5 and step 6. Never patch the STEP.

8. Report before fabrication

Work through references/validation.md and give the user: the process and material, every interface dimension with its source and tolerance, the clearances chosen, what the snapshot showed, and any check that did not pass.

Flag explicitly every interface the automatic check could not cover — a vendor drawing, a user measurement, a standard not in the bundled database. check.py interfaces reports only what the model declared against a known standard, so silence there is not confirmation; a dimension nobody could check has to be named as such.

Units

build123d is unitless internally and everything in this skill is millimetres and degrees. export_step is called with Unit.MM. Imperial hardware appears throughout optomechanics (1/4-20 screws, 1 inch grids, SM1 threads); convert to millimetres in a single named constant at the point of definition and never mix systems inside an expression. 1 inch is exactly 25.4 mm, and a 25 mm metric optical grid is not interchangeable with a 1 inch imperial grid — the error accumulates to 1.6 mm over four holes.

Tolerances and fits

A nominal dimension is not a fit. Every mating dimension needs a deliberate clearance chosen from the process tolerance in references/fabrication-limits.md. Common defaults, per side:

FitFDMSLACNC
Free-sliding (plate in a pocket)0.40 mm0.20 mm0.10 mm
Located but removable0.25 mm0.10 mm0.05 mm
Press / interference-0.05 mm-0.03 mm-0.02 mm

These are starting points for a first article, not guarantees. Say so when you report them, and recommend printing a test coupon of the critical interface before committing to a full part.

Scientific caveats

  • Material compatibility governs. A geometrically perfect part in the wrong polymer fails in service: autoclave cycles distort PLA, many solvents craze acrylic, and uncured SLA resin is cytotoxic. Check references/fabrication-limits.md before recommending a material for anything contacting cells, tissue, solvents, or heat.
  • Optical parts have non-geometric requirements. Autofluorescence, surface roughness, and stray-light scatter are not visible in a STEP file. Black resin is not automatically low-scatter.
  • Vendor labware varies. The SLAS standards fix the plate footprint but not well geometry, skirt profile, or lid fit, and consumable tubes differ between suppliers. Design to the standard where one exists; otherwise require a measurement.
  • A passing bounding box is not a passing part. fit checks the dimensions it is given. It cannot see a missing feature, and it does not replace the snapshot.

References

FileContents
references/microfluidics.mdChannel cross-sections and aspect ratios, mold vs chip polarity, minimum features by process, port and tubing interfaces, bonding lands, dead volume
references/optomechanics.mdBreadboard grids and screw clearances, post and pedestal heights, 30 mm cage geometry, SM lens-tube threads, beam height
references/labware-adapters.mdANSI/SLAS 1-4 microplate dimensions, cuvettes, tubes, slides, dishes, deck and stage constraints
references/behavior-rigs.mdArena and maze geometry, head-fixation interfaces, spouts and ports, T-slot extrusion, cleaning and durability
references/fabrication-limits.mdProcess tolerances, minimum walls and features, clearance and thread inserts, materials, autoclave and solvent and biocompatibility
references/validation.mdPre-fabrication checklist and the failure modes each item catches
references/build123d-patterns.mdbuild123d 0.11.1 API cookbook: builder vs algebra, sketches, selectors, joints, exports

Scripts

CommandPurpose
gen.py <model.py> --outdir DIRRun build(), export STEP and STL, write the provenance manifest
gen.py <model.py> --dxf [--dxf-z MM]Also slice a 2D DXF profile for laser cutting (default plane: mid-height)
check.py facts <step>Validity, bounding box, volume, area, centre of mass, solid count
check.py interfaces <manifest|model.py>Check every interface the model declares; non-zero exit on failure
check.py fit --standard ID --value DIM=MMCheck one dimension by hand, or a part whose outer envelope is the interface
check.py clearance <a> <b> --min MMMinimum distance between two solids; detects interference
check.py standards [--list|--show ID]Browse the bundled standards data (standard library only)
snapshot.py <step> --out PNGSix-view orthographic and isometric render for visual review

All commands accept --json for machine-readable output and write progress to stderr. check.py standards, and check.py interfaces on a manifest, run without build123d installed.

GitHub репозиторий

K-Dense-AI/claude-scientific-skills
Путь: skills/lab-hardware-cad
0
agent-skillsai-scientistbioinformaticschemoinformaticsclaudeclaude-skills
FAQ

Часто задаваемые вопросы

Что такое Skill lab-hardware-cad?

lab-hardware-cad — это Claude Skill от K-Dense-AI. Skills объединяют инструкции и ресурсы, которые Claude загружает по мере необходимости, чтобы выполнять задачи, связанные с lab-hardware-cad, без дополнительных запросов.

Как установить lab-hardware-cad?

Используйте команды установки на этой странице: добавьте lab-hardware-cad в Claude Code как плагин или клонируйте репозиторий в каталог skills, затем перезапустите Claude, чтобы загрузить Skill.

К какой категории относится lab-hardware-cad?

lab-hardware-cad относится к категории Мета.

Можно ли использовать lab-hardware-cad бесплатно?

Да. lab-hardware-cad размещён на AIMCP и доступен для бесплатной установки.

Похожие навыки

content-collections
Мета

Этот навык предоставляет проверенную в продакшене настройку для Content Collections — TypeScript-ориентированного инструмента, который преобразует файлы Markdown/MDX в типобезопасные коллекции данных с валидацией Zod. Используйте его при создании блогов, сайтов документации или контентных приложений на Vite + React для обеспечения типобезопасности и автоматической проверки содержимого. Он охватывает всё: от настройки плагина Vite и компиляции MDX до оптимизации развертывания и валидации схем.

Просмотреть навык
polymarket
Мета

Этот навык позволяет разработчикам создавать приложения на платформе прогнозных рынков Polymarket, включая интеграцию с API для торговли и получения рыночных данных. Он также обеспечивает потоковую передачу данных в реальном времени через WebSocket для отслеживания текущих сделок и рыночной активности. Используйте его для реализации торговых стратегий или создания инструментов, обрабатывающих обновления рынка в реальном времени.

Просмотреть навык
creating-opencode-plugins
Мета

Этот навык помогает разработчикам создавать плагины OpenCode, которые подключаются к более чем 25 типам событий, таким как команды, файлы и операции LSP. Он предоставляет структуру плагина, спецификации API событий и шаблоны реализации для модулей на JavaScript/TypeScript. Используйте его, когда вам нужно перехватывать, отслеживать или расширять жизненный цикл ассистента OpenCode AI с помощью пользовательской событийно-ориентированной логики.

Просмотреть навык
sglang
Мета

SGLang — это высокопроизводительный фреймворк для обслуживания больших языковых моделей (LLM), специализирующийся на быстрой структурированной генерации JSON, regex и рабочих процессов агентов с использованием кэширования префиксов RadixAttention. Он обеспечивает значительно более высокую скорость вывода, особенно для задач с повторяющимися префиксами, что делает его идеальным для сложных структурированных результатов и многократных диалогов. Выбирайте SGLang вместо альтернатив, таких как vLLM, когда вам требуется ограниченное декодирование или вы создаете приложения с интенсивным совместным использованием префиксов.

Просмотреть навык