「nim」の検索結果

Full-history Godot version migration hub. Use when upgrading any Godot project toward the library target (currently 4.7)—from 1.x/2.x legacy eras through 3→4 and hop-by-hop 4.x minors—or finding Domain Skill-scoped migration notes. Trigger keywords: upgrade Godot, migrate Godot version, Godot 3 to 4, Godot 2 to 3, upgrading_to_godot, version migration, breaking changes, convert-3to4, TileMapLayer, AnimationMixer, engine.cfg, project.godot.

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Expert blueprint for racing games including vehicle physics (VehicleBody3D, suspension, friction), checkpoint systems (prevent shortcuts), rubber-banding AI (keep races competitive), drifting mechanics (reduce friction, boost on exit), camera feel (FOV increase with speed, motion blur), and UI (speedometer, lap timer, minimap). Use for arcade racers, kart racing, or realistic sims. Trigger keywords: racing_game, vehicle_physics, checkpoint_system, rubber_banding, drifting_mechanics, camera_feel.

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 when building in-game HUDs — health bars, score displays, minimap, notifications, and damage numbers

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 Baidu ERNIE-Image / ERNIE-Image-Turbo workflows, primarily TEXT-TO-IMAGE. Pick ERNIE when you need precise multilingual text rendering, posters/signage, manga/anime multi-panel layouts, or strong instruction following for complex multi-object scenes. Also supports denoise-based image-to-image refine (NOT instruction-grounded editing; use Qwen-Image-Edit or Flux Kontext for "change X in this photo" edits).

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Build Qwen Image 2512 text-to-image workflows with QwenImageIntegratedKSampler, separate component loading, lightning LoRAs, and fine-tuned model variants

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。

Disciplined diagnosis loop for hard bugs and performance regressions. Reproduce → minimise → hypothesise → instrument → fix → regression-test. Use when user says "diagnose this" / "debug this", reports a bug, says something is broken/throwing/failing, or describes a performance regression.

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SwiftUI's actual mental model — view identity, lifetime, and dependencies (the Demystify canon), state ownership decision rules, Observation's per-property tracking, body-performance discipline, and the main-actor concurrency contract. Use when state resets mysteriously, views re-render too often, animations glitch between branches, choosing @State vs @Bindable vs plain property, or debugging "why did body 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。

Localization and internationalization strategy for iOS/macOS apps. Covers market prioritization, language tier recommendations, minimum viable localization levels, translation workflows, cultural adaptation, localized ASO, and testing. Use when planning localization, expanding to new markets, deciding which languages to support, or planning translation workflow.

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。

Generates achievement celebration UI with confetti animations, badge unlocks, progress milestones, haptic feedback, and optional share-to-social. Use when user wants to celebrate achievements, show confetti, display milestone badges, or trigger rewards on key thresholds.

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。

Design skills for Apple platform UI — Liquid Glass, animations, game feel (haptics, sound, celebrations), UI prototyping, UX writing, SF Symbols, and typography. Use when implementing design language features, adding juice/feedback, writing interface copy, or choosing type and iconography.

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Implements low-level utilities for single-cell trajectory analysis, primarily intended for re-use inside higher-level packages. Include a function to create a cluster-level minimum spanning tree and data structures to hold pseudotime infere

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omicsViewer visualizes ExpressionSet (or SummarizedExperiment) in an interactive way. The omicsViewer has a separate back- and front-end. In the back-end, users need to prepare an ExpressionSet that contains all the necessary information for the downstream data interpretation. Some extra requirements on the headers of phenotype data or feature data are imposed so that the provided information can be clearly recognized by the front-end, at the same time, keep a minimum modification on the existin

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An implementation, which takes input data and makes it available for proper batch effect removal by ComBat or Limma. The implementation appropriately handles missing values by dissecting the input matrix into smaller matrices with sufficient data to feed the ComBat or limma algorithm. The adjusted data is returned to the user as a rebuild matrix. The implementation is meant to make as much data available as possible with minimal data loss.

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。

Framework for running single-variable cold email experiments. Defines experiment types (list-only, copy-only, combined), confidence weighting, minimum sample sizes, and success criteria. Use when the user wants to improve a campaign, test a new list vs old one, or compare copy variants. Prevents the

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 when a user gives or references a webpage URL and wants to extract, reproduce, port, or locally replay a WebGL, WebGPU, Canvas, shader-like, animated background, interactive 3D, or web visual effect. Locks the target rendering surface group, records shader/resource/render graph/timing/input evidence, builds an evidence-matched local baseline, then projectizes it. Do not use for ordinary DOM/CSS page cloning.

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。

Reduce a change to the minimum that solves the problem. Use when code is over-engineered or a diff is bloated.

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。

Draft, audit, or minimally revise English- or Chinese-language academic prose to reduce formulaic, vacuous, mechanically repetitive, or process-leaking language while preserving claims, evidence strength, logical relations, manuscript-wide terminology identity, document-level pattern variation, and scholarly register. Use for papers, abstracts, grants, cover letters, and reviewer responses when the user asks to de-AI, humanize, audit AI-like phrasing, or rewrite text without changing meaning. English is primary; Chinese is supported. Not for detector evasion, policy circumvention, pure translation, non-academic copy, or adding facts, citations, examples, or author experiences that the source does not contain.

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。

Write the test first, watch it fail, write minimal code to pass

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。

Writes, improves, or rewrites Seedance 2.0 prompts that TRANSFORM footage the user already has (video-to-video), rather than building a scene from scratch. Use whenever a real clip is the starting point and they want to: add a VFX element (set a head or hair on fire, transform a hand, make a limb invisible), swap the environment around a preserved subject (desert, clouds, lava, a neon city), drop a giant photoreal creature behind or onto a subject/landmark, relight or regrade so subject and added elements read as one shot, sync a crash-zoom or push-in to a spoken line or timecode, or generate a matching transformed start frame to animate from. Also use when they paste such a prompt and ask to change its lighting, timing, creature, or runtime, or say 'make a Seedance prompt for this video' with a clip attached. This is the video-to-video specialization; for a brand-new scene from image references with no source clip to preserve, higgsfield-seedance applies instead.

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 whenever the user asks anything about Higgsfield AI — writing or refining video/image prompts, choosing a model (Kling, Veo, Wan, Seedance, Minimax Hailuo, DoP, Soul, Nano Banana, Seedream, Flux, GPT Image, etc.), camera controls, named motion presets, Soul ID character consistency, Cinema Studio 2.5/3.0, Vibe Motion, troubleshooting failed generations, credit optimization, Photodump, or any mention of higgsfield.ai. Also trigger on generic "write me a video prompt" or "make me an AI video prompt" requests when Higgsfield is the user's configured platform.

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。

Turn a feature request into a minimal, file-level implementation plan before any code.

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 a 10–30 second continuous-shot explainer for any product, rendered from code to MP4 with sound. One hero element (a ball, a cursor, a file, a message) travels through the product's workflow laid out as stations on one big canvas; the camera follows it, each station reacts as it passes, then the camera pulls out to reveal the whole journey. Use when someone wants an engaging, story-driven, one-take explainer or a loopable product animation.

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。

Turn a talking-head video and its transcript into motion-graphic B-roll timed to the speaker's words, in a continuous one-shape style (one element that morphs and never cuts, driven by a cursor, spring motion). Use when someone gives a video (and ideally a transcript) and asks for motion graphics, B-roll, animated cutaways or overlays.

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。

文本转语音工具 - 默认 MiniMax TTS，支持切换 Edge TTS 和 Kokoro TTS (v1.1-zh)

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。