190 件 ・ 関連度順
概要と使いどころ
Create/edit parametric CAD models, organize CAD projects, export STEP/STL/3MF/GLB files, resolve prompt references, and measure geometry with cadgen. Open and visually review existing STEP/STP, STL, 3MF and GLB files in CAD Viewer.
日本語の概要は準備中です。原文の説明を表示しています。
Make an engineering drawing of a part as a PDF - orthographic views with hidden lines and centre marks, real dimensions, hole callouts, notes and a title block on ISO sheets, all projected from the part's geometry so the drawing follows the model. Use when the user asks for a drawing, a dimensioned sheet, shop or manufacturing drawings, a print, or "2D views of this part".
日本語の概要は準備中です。原文の説明を表示しています。
Create, migrate, improve, or debug detailed vehicle assets for CARLA using Blender and Unreal, including reference-based geometry, materials, wheels, physics, lights, and runtime validation. Use for vehicle asset authoring rather than ordinary traffic spawning or map decoration.
日本語の概要は準備中です。原文の説明を表示しています。
Imports a custom RoadRunner map (FBX geometry + XODR OpenDRIVE) into a CARLA source build as a drivable map — reads the map from the directory the user names, runs CARLA's Import.py to cook the level, Traffic Manager graph and (standard maps only) pedestrian navmesh, and verifies it loads on a server. Handles both standard maps and large tiled maps; large maps get no navmesh, matching upstream CARLA. Use when the user asks to "import a map into CARLA", "add a custom/RoadRunner map", "ingest an FBX+XODR map", "make import", bring in a "large/tiled map", or fix missing walkers / a missing pedestrian navmesh.
日本語の概要は準備中です。原文の説明を表示しています。
Gets actor and level 3D bounding boxes and projects them into a camera image as 2D boxes — the dataset-annotation workflow. Lists box geometry, draws 3D boxes in the world via debug, or captures one camera frame and writes an annotated PNG plus a JSON of 2D boxes for matching actors. Use when the user asks to "get bounding boxes", "draw boxes around the cars", "project boxes onto the camera", or "generate a detection dataset / annotations".
日本語の概要は準備中です。原文の説明を表示しています。
Generate architecture procedurally in Three.js and film it assembling — a small geometry vocabulary that builds pagodas, castles, domes and spires from parameters instead of mesh files, hip roofs with flying eaves driven by a single profile function, and a clipping-plane build animation where everything below a rising line is finished work and scaffolding stands above it. Use for construction studies, architectural title sequences, procedural landmarks, or any hero object that should build itself rather than fade in.
日本語の概要は準備中です。原文の説明を表示しています。
Create a light-mode technical design system with warm paper surfaces, dark outer framing, subtle diagonal texture, precise bracketed geometry, and restrained accent signals.
日本語の概要は準備中です。原文の説明を表示しています。
Reveal Three.js geometry with an expanding world-space scan whose wire cage leads the solid surface, then burns away. Use for wireframe scanning, radial mesh reveals, survey pulses, holographic assembly, topology intros, and 3D model entrances where a plain opacity wipe does not explain the form.
日本語の概要は準備中です。原文の説明を表示しています。
Profile, diagnose, and improve Three.js or WebGL game performance without regressing gameplay. Use for frame-time drops, CPU/GPU pressure, draw calls, texture and geometry budgets, animation loops, adaptive quality, mobile performance, and browser performance verification.
日本語の概要は準備中です。原文の説明を表示しています。
Plan, create, integrate, or audit a hybrid asset pipeline for a Three.js or web game. Use when choosing among imported meshes, procedural 3D geometry, AI-generated reference art, 2D UI media, sprites, VFX, and performance-ready runtime asset delivery.
日本語の概要は準備中です。原文の説明を表示しています。
Build recognizable falling leaves in world space using instanced geometry, independent tumble, coupled sideways drift, shared wind, scene occlusion, and camera-aware recycling. Use for 3D autumn leaves or drifting foliage in Three.js and similar scenes; use falling-leaves for a 2D canvas overlay.
日本語の概要は準備中です。原文の説明を表示しています。
Inverse-fold a backbone with ligand, nucleic-acid, and metal context using LigandMPNN (Dauparas et al. 2023, github.com/dauparas/LigandMPNN). Reach for this skill to redesign the residues lining a binding pocket around a bound small molecule or cofactor, to design metal-coordinating sites where the geometry must be respected, or to get threaded designed-sequence PDBs out of any MPNN run.
日本語の概要は準備中です。原文の説明を表示しています。
Predict small-molecule binding poses with DiffDock-L (Corso et al. 2023/2024, github.com/gcorso/DiffDock) — blind diffusion docking that places a ligand into a protein pocket without a predefined search box and ranks the samples with a learned confidence model. Reach for this skill to dock a SMILES or SDF against a PDB, to generate ranked 3D poses for a small fragment library, or to get a starting pose for downstream rescoring. DiffDock predicts geometry, not affinity.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solving equations algebraically, performing calculus operations (derivatives, integrals, limits), manipulating algebraic expressions, working with matrices symbolically, physics calculations, number theory problems, geometry computations, and generating executable code from mathematical expressions. Apply this skill when the user needs exact symbolic results rather than numerical approximations, or when working with mathematical formulas that contain variables and parameters.
日本語の概要は準備中です。原文の説明を表示しています。
Upgrade of chinese-ppt for Chinese Beamer decks (xelatex + ctex + fandol, CUFE template). Same 7-section outline and X→M→Y framework, but adds (a) mandatory 1.3 line-spacing + 3pt paragraph spacing, (b) overflow-prevention line budget + balanced split-frame rules, (c) prose rewrites that strip AI-ish "关键比较/理论映射" labels and redundant 章节括号注释, (d) stricter CJK-space + middle-dot rules, (e) retrofit workflow for existing chinese-ppt decks, (f) mandatory local linespread reset inside TikZ / table / fixed-geometry frames. Use for "做中文学术PPT 2 版"、"中文 Beamer 改进版"、"答辩 PPT chinese-ppt2"、"防越界 PPT"等请求。用户在 Overleaf 编译，只产出 .tex + figures/，不要附加 compile 脚本。
日本語の概要は準備中です。原文の説明を表示しています。
Computational geometry with Shapely - create geometries, boolean operations, measurements, predicates
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solving equations algebraically, performing calculus operations (derivatives, integrals, limits), manipulating algebraic expressions, working with matrices symbolically, physics calculations, number theory problems, geometry computations, and generating executable code from mathematical expressions. Apply this skill when the user needs exact symbolic results rather than numerical approximations, or when working with mathematical formulas that contain variables and parameters.
日本語の概要は準備中です。原文の説明を表示しています。
Cloud-based quantum chemistry platform with Python API. Preferred for computational chemistry workflows including pKa prediction, geometry optimization, conformer searching, molecular property calculations, protein-ligand docking (AutoDock Vina), and AI protein cofolding (Chai-1, Boltz-1/2). Use when tasks involve quantum chemistry calculations, molecular property prediction, DFT or semiempirical methods, neural network potentials (AIMNet2), protein-ligand binding predictions, or automated computational chemistry pipelines. Provides cloud compute resources with no local setup required.
日本語の概要は準備中です。原文の説明を表示しています。
Screen US stocks for Stockbee-style selling-exhaustion hammer setups using prior momentum, pullback depth, undercut/reclaim, long lower-wick geometry, close-location, volume confirmation, quality/liquidity gates, and risk-distance scoring. Use when the user asks for Stockbee, Pradeep Bonde, exhaustion setup, selling exhaustion, hammer reversal, undercut reclaim, near-close reversal candidates, or pullback entries in high-quality funds-owned stocks.
日本語の概要は準備中です。原文の説明を表示しています。
Professional logo and brand-mark design, from brief to production files. Guides discovery and the design brief, concept generation, choosing a mark type (wordmark, monogram, letterform, pictorial, abstract, emblem, mascot, combination), building clean geometric SVG logos, optical refinement, colour and typography, testing (16 px, one-colour, reversed, shelf test), client presentation, delivery variants and brand guidelines. Includes a searchable library of 1,400+ real-world SVG logos classified by type, technique, geometry and industry, plus scripts that audit SVGs and generate test sheets, presentation boards and export variants. Use this skill whenever the user wants a logo, logotype, wordmark, monogram, brand mark, symbol, app icon or favicon designed, redesigned, refreshed, critiqued or compared; asks for logo ideas or concepts; needs a design brief, logo guidelines, lockups or an identity system; or mentions branding a new company, product, app or project — even if they don't say the word "logo".
日本語の概要は準備中です。原文の説明を表示しています。
Auto-ingest a geospatial file (GeoJSON, Shapefile, GeoPackage, KML/KMZ, FlatGeobuf, CSV-with-geometry) into a PortalJS portal on the user's own machine, with no server. Normalizes CRS to EPSG:4326, derives a PMTiles render tier and a GeoParquet query tier, pushes all three artifacts to Cloudflare R2 via Git LFS, and appends one dual-tier datasets.json entry the showcase auto-renders. Use when the source is a vector geo format that needs a map or spatial-query view.
日本語の概要は準備中です。原文の説明を表示しています。
Use Bio.PDB to parse and analyze protein structures (PDB/mmCIF) for structural bioinformatics tasks; use when you need structure parsing, geometry calculations, or structural comparison/superposition.
日本語の概要は準備中です。原文の説明を表示しています。
Comprehensive PostGIS spatial table design reference covering geometry types, coordinate systems, spatial indexing, and performance patterns for location-based applications
日本語の概要は準備中です。原文の説明を表示しています。
Three.js OBJExporter utility for exporting 3D geometry to Wavefront OBJ format. Use when converting Three.js scenes, meshes, or geometries to OBJ files for use in other 3D software like Blender, Maya, or MeshLab.
日本語の概要は準備中です。原文の説明を表示しています。