SDFormat/SDF 모델 및 월드 생성, 검증, 시뮬레이터 연동. `.sdf` 파일, SDFormat XML, Python `gen_sdf()` 소스, 모델, 월드, 링크, 조인트, 포즈, 프레임, 관성, 시각/충돌 형상, 메시 URI, 센서, 조명, 물리, 플러그인, 인클루드, Gazebo, 정적 SDF 검토 또는 시뮬레이터별 메타데이터에 사용됩니다. signed-distance-field 형상에는 사용하지 마십시오.
이 스킬은 SDFormat(Simulation Description Format) 기반의 `.sdf` 모델 및 월드 파일을 생성, 검증, 그리고 Gazebo와 같은 시뮬레이터로 전달하는 작업을 전문적으로 처리합니다. 사용자는 SDFormat XML 스키마, Python `gen_sdf()` 함수, 모델/월드 구조(링크, 조인트, 포즈, 프레임, 관성), 시각/충돌 형상, 메시 URI, 센서, 조명, 물리 파라미터, 플러그인, 인클루드 등 시뮬레이션에 필요한 모든 요소를 정의하고 검증할 수 있습니다. Gazebo 및 다양한 시뮬레이터별 메타데이터를 지원하며, 정적 SDF 파일의 검토 및 수정에도 유용합니다. 단, signed-distance-field(SDF) 형상과는 관련이 없으므로 주의해야 합니다.
npx skills add https://github.com/earthtojake/text-to-cad/tree/main/skills/sdfInstalled? Explore more 이미지 skills: steipete/songsee, affaan-m/frontend-design, mattpocock/improve-codebase-architecture · View all 6 →
SDFormat/SDF 모델 및 월드 생성, 검증, 시뮬레이터 연동. .sdf 파일, SDFormat XML, Python gen_sdf() 소스, 모델, 월드, 링크, 조인트, 포즈, 프레임, 관성, 시각/충돌 형상, 메시 URI, 센서, 조명, 물리, 플러그인, 인클루드, Gazebo, 정적 SDF 검토, 또는 시뮬레이터별 메타데이터에 사용됩니다. signed-distance-field 형상에는 사용하지 마십시오.
This repo contains 6 individual skills — each has its own dedicated page.
Create, modify, inspect, and validate STEP-first parametric CAD parts and assemblies. Use for natural-language CAD specs, reference images, 2D technical drawings, STEP/STP generation or direct inspection, Python CAD source, source-level joints, selector references, geometry facts, measurements, mating deltas, snapshots, and secondary STL/3MF/native GLB outputs from CAD geometry.
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.
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.