cad 是做什麼的？
建立、修改、檢查與驗證以 STEP 為首的參數化 CAD 零件與組合件。適用於自然語言 CAD 規格、參考圖像、2D 技術圖紙、STEP/STP 生成或直接檢查、Python CAD 原始碼、來源層級接合、選取器參考、幾何事實、量測、配對差異、快照，以及從 CAD 幾何產生的次要 STL/3MF/原生 GLB 輸出。
建立、修改、檢查與驗證以 STEP 為首的參數化 CAD 零件與組合件。適用於自然語言 CAD 規格、參考圖像、2D 技術圖紙、STEP/STP 生成或直接檢查、Python CAD 原始碼、來源層級接合、選取器參考、幾何事實、量測、配對差異、快照，以及從 CAD 幾何產生的次要 STL/3MF/原生 GLB 輸出。
此技能「earthtojake/cad」專為開發者與 AI 代理者設計，用於處理以 STEP 格式為基礎的參數化 CAD 零件與組合件。它支援從自然語言規格、參考圖像或 2D 技術圖紙產生 STEP/STP 檔案，亦可直接檢查與修改現有 CAD 幾何。技能涵蓋 Python CAD 原始碼、來源層級接合、選取器參考、幾何事實與量測，並能處理配對差異與快照。最終可輸出 STL、3MF 或原生 GLB 等次要格式，適用於 Claude Code 等支援 AI 代理開發環境的平台。其核心優勢在於將複雜的 CAD 操作轉化為可透過自然語言或程式碼驅動的工作流程，大幅提升工程設計與驗證的效率。
npx skills add https://github.com/earthtojake/text-to-cad/tree/main/skills/cadInstalled? Explore more 影像 skills: steipete/songsee, affaan-m/frontend-design, mattpocock/improve-codebase-architecture · View all 6 →
建立、修改、檢查與驗證以 STEP 為首的參數化 CAD 零件與組合件。適用於自然語言 CAD 規格、參考圖像、2D 技術圖紙、STEP/STP 生成或直接檢查、Python CAD 原始碼、來源層級接合、選取器參考、幾何事實、量測、配對差異、快照，以及從 CAD 幾何產生的次要 STL/3MF/原生 GLB 輸出。
This repo contains 6 individual skills — each has its own dedicated page.
Start or reuse the CAD Explorer viewer, return review links, and create saved snapshots for explicit CAD and robot-description files. Use when rendering or visually reviewing `.step`, `.stp`, `.glb`, `.stl`, `.3mf`, `.dxf`, `.urdf`, `.srdf`, or `.sdf` files, especially when handed off from CAD, URDF, SRDF, or SDF generation skills.
SDFormat/SDF model and world generation, validation, and simulator handoff. Use for `.sdf` files, SDFormat XML, Python `gen_sdf()` sources, models, worlds, links, joints, poses, frames, inertials, visual/collision geometry, mesh URIs, sensors, lights, physics, plugins, includes, Gazebo, static SDF review, or simulator-specific metadata. Do not use for signed-distance-field geometry.
Review DXF and STEP/STP uploads for SendCutSend.com orders using its ordering guide, catalog, and specs. Use only for SendCutSend.com preflight reports covering upload readiness, selected material/SKU/thickness/service availability, and service-specific checks for laser cutting, CNC routing, bending, tapping, countersinking, hardware insertion, and finishing.
MoveIt2 SRDF generation, validation, and planning-semantics workflow. Use when creating, editing, regenerating, inspecting, or validating `.srdf` files, `gen_srdf()` sources, MoveIt planning groups, virtual joints, passive joints, end effectors, group states, disabled collisions, URDF-linked planning semantics, or SRDF handoff for live review. Use the URDF skill for robot structure, the SDF skill for simulator descriptions, and the cad-viewer skill for rendering, live review links, and optional MoveIt2 controls.
Find, evaluate, and download common purchasable CAD parts from step.parts, including named off-the-shelf actuators, servos, motors, electronics boards, connectors, screws, bolts, nuts, washers, bearings, standoffs, and other catalog components. Use when Codex needs to search the hosted step.parts catalog before creating simplified placeholder geometry, resolve fuzzy part names, standards, aliases, or dimensions, choose a matching part, fetch a canonical .step file, verify checksums, or use the step.parts API/OpenAPI/catalog endpoints for standard part discovery.
URDF robot description generation and default generation-time validation. Use when creating, editing, regenerating, inspecting, or debugging `.urdf` files, Python `gen_urdf()` sources, robot links, joints, limits, inertials, visual/collision geometry, mesh references, frame conventions, or generated robot-description artifacts. Use the SRDF skill for MoveIt2 semantic groups and IK/path-planning semantics; use the cad-viewer skill for local MoveIt2 server controls; use the CAD skill for STEP/STL/3MF/DXF/GLB outputs.
Generate spectrograms and feature-panel visualizations from audio with the songsee CLI.
Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.
Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
Add documentation for a new AI provider — usage docs, env vars, Docker config, image resources.
Tests in real browsers via Chrome DevTools MCP. Use when building or debugging anything that runs in a browser. Use when you need to inspect the DOM, capture console errors, analyze network requests, profile performance, or verify visual output with real runtime data. Requires the chrome-devtools MCP server to be configured.
This skill should be used when the user wants to visualize data. It intelligently selects the most suitable chart type from 26 available options, extracts parameters based on detailed specifications, and generates a chart image using a JavaScript script.