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概要と使いどころ
Use when the user mentions SwiftUI performance, janky scrolling, slow animations, or view update issues — expensive bodies, formatters, whole-collection dependencies, and missing lazy containers.
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 the user mentions window resizing support, resizable-window readiness, iPhone Mirroring compatibility, iPhone Duo readiness, scene-lifecycle migration checking, or preparing an app for the 27-cycle resizing model.
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 the user mentions concurrency checking, Swift 6 compliance, data race prevention, or async code review.
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 read-only MongoDB queries (find) or aggregation pipelines using natural language, with collection schema context and sample documents. Use this skill whenever the user asks to write, create, or generate MongoDB queries, wants to filter/query/aggregate data in MongoDB, asks "how do I query...", needs help with query syntax, or discusses finding/filtering/grouping MongoDB documents. Also use for translating SQL-like requests to MongoDB syntax. Does NOT handle Atlas Search ($search operator), vector/semantic search ($vectorSearch operator), fuzzy matching, autocomplete indexes, or relevance scoring - use search-and-ai for those. Does NOT analyze or optimize existing queries - use mongodb-query-optimizer for that. Does NOT handle aggregation pipelines that involve write operations. Requires MongoDB MCP server.
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。
Connect to and acquire images from cameras in MATLAB using Image Acquisition Toolbox. Use this skill when the user wants to: use a webcam, acquire images, capture video, stream from a camera, connect to a GigE Vision camera, preview live video, list available cameras, configure camera properties, use a CoaXPress frame grabber, or use a Camera Link frame grabber. Covers USB webcams, GigE Vision, USB3 Vision, CoaXPress, Camera Link, and GenICam-compliant cameras. Always prefer videoinput from Image Acquisition Toolbox over webcam support package or gigecam.
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。
Guides the agent to reference official MathWorks Documentation and Help. Determine correct function syntax and workflows from user guides when deeper context is needed. Minimize iterations and repetitive trial and error. Use this skill to: Identify correct syntax and configuration details. Retrieve relevant, version-specific (or release-specific) information from official documentation. Consult user guides when conceptual or workflow context is needed. Apply best practices.
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 SPEC, INNOVATE, or VALIDATE (Layer 2) approach hinges on an unverified runtime/library/external mechanism: run a probe from the 8-family taxonomy and produce a VIABLE/NOT-VIABLE/INCONCLUSIVE VERDICT artifact.
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。
Optimize Google Shopping campaigns and product feeds for maximum visibility and ROAS. Feed optimization, bidding strategy, campaign structure, and Performance Max integration.
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。
Orchestrate iOS screenshot automation with xcodebuild/simctl for build-run, AXe for UI actions, JSON settings and plan files, Koubou-based framing (`asc screenshots frame`), and screenshot upload (`asc screenshots upload`). Use when users ask for automated screenshot capture, AXe-driven simulator flows, frame composition, or screenshot-to-upload pipelines.
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。
Rust 开发规范（聚焦 Axum + Tokio 后端栈）。当用户操作 .rs、Cargo.toml、Cargo.lock 文件， 或涉及 Rust 后端开发（Axum、Tokio、sqlx、reqwest）时触发。 包含工具链、命名约定、错误处理、异步陷阱、模块组织、依赖管理、测试规范、unsafe 红线等。
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。
Walk through a live web app AS a real user to find usability + behavioural bugs that static reviews miss. REQUIRES proof of interaction (typing, clicking, sending, observing) before any verdict — a sweep that didn't interact terminates with verdict 'Incomplete'. Walks threads, exercises every element, runs the multi-pane stress matrix, visual polish sweep, component perfection checklist, automated a11y (axe-core), pragmatic performance budget (LCP/CLS/INP), scenario battery (11 scenarios), and stress recipes including the real-flavour data battery. Hard gates: console errors/warnings = 0, network 5xx = 0, layout collapse = 0, axe Critical/Serious = 0, perf budget green. Audit-the-audit meta-check rejects rushed reports. Each finding has reproduction steps, evidence path, and suspected code location. Trigger with 'ux audit', 'walkthrough', 'qa sweep', 'audit the app', 'dogfood this', 'check all pages', 'find what's broken', 'stress the UI'.
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。
Lightweight 3D effects for decorative elements and micro-interactions using Zdog, Vanta.js, and Vanilla-Tilt.js. Use this skill when adding pseudo-3D illustrations, animated backgrounds, parallax tilt effects, decorative 3D elements, or subtle depth effects without heavy frameworks. Triggers on tasks involving Zdog pseudo-3D, Vanta.js backgrounds, Vanilla-Tilt parallax, card tilt effects, hero section animations, or lightweight landing page visuals. Ideal for performance-focused designs.
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。
This skill should be used whenever the user mentions a "semantic model", "data model", or "dataset", or asks to "build", "model", "design", "optimize", "review", or "audit" one, or to "add a measure", "add a relationship", "create a role" / "set up RLS", "add a calculation group", "set up incremental refresh", "fix a star schema", "reduce model size", "prepare a model for Copilot / AI", or "check model quality". Covers the full lifecycle (design, build, refresh, review) and drives every operation through the `te` CLI first, then TOM (connect-pbid) or a model MCP, then TMDL authoring (the tmdl skill). Not for report visuals (use pbir-cli) or isolated DAX query tuning (use the dax skill).
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。
Compare several Japanese NLP libraries, models, or datasets for a keyword (a specific tool name, or a function/task like '形態素解析') across a handful of criteria chosen for that comparison, rendered as a ○/△/✕ table. Use when the user wants a side-by-side comparison of multiple Japanese NLP tools/libraries/datasets, not just the single best one. Trigger phrases include 'X と Y と Z を比較して', '形態素解析ライブラリを比較', 'MeCab と Sudachi どっちがいい', 'どのツールを使うべき', 'compare japanese tokenizers', 'mecab vs sudachi vs janome', 'which embedding model should I use', '日本語NERライブラリの比較表', 'pros and cons of japanese OCR tools'. For a single ranked list use search; for alternatives to one specific tool (or contribution candidates) without a multi-axis table, use discover.
How to actually instrument product analytics correctly. Event taxonomy, property design, naming conventions, schema versioning, identity stitching, funnel design, retention cohorts, North Star metric selection, dashboard hygiene, instrumentation debt, and the failure modes that produce data nobody trusts. Triggers on product analytics setup, event taxonomy, tracking plan, instrumentation, schema versioning, North Star metric, retention cohorts, funnel design, naming conventions, instrument new feature, audit existing analytics, dashboard reconciliation, instrumentation debt, Mixpanel setup, Amplitude setup, PostHog setup, warehouse-native analytics. Also triggers when the team has data but cannot trust it, or when designing instrumentation for a new feature, or when auditing an existing setup that has drifted.
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。
Walk the user through four directional axes (tone register, aesthetic philosophy, audience relationship, sensory ambition) and produce a structured aesthetic brief that downstream content, copy, design, and art-direction skills consume as required input. The aesthetic depth layer, distinct from `creative-brief` (operational kickoff: scope, audience, deliverables, constraints). Use when a project needs aesthetic coherence across many small decisions and the user has only a vague feeling, or when multiple downstream aesthetic-producing skills need a shared brief. Triggers on creative direction, aesthetic direction, set the aesthetic, define the visual direction, what's the vibe, what's the tone, the four axes. Does NOT fire for a general kickoff brief (use `creative-brief`), tactical single-piece work, already-documented direction, purely functional output, or locked production-stage work.
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。
A swirling galaxy of particles. A bold, canvas-based effect from Open Design's html-ppt fx pack — for slides and launch videos. Guards prefers-reduced-motion (does not start). One per screen; on web use sparingly.
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。
Business fundamentals for indie app developers — LLC/entity setup, taxes, Apple Small Business Program, revenue tracking, hiring contractors, and financial planning for sustainability. Use when user asks about business setup, tax implications, hiring, or financial planning for their app business.
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。
Evaluate and plan Amazon marketplace expansion across countries and regions. Use when a seller asks which Amazon marketplace to enter, how to compare international demand and economics, what tax, product-compliance, logistics, localization, account, or launch workstreams to investigate, or how to build a gated global-selling roadmap. Do not use as legal, tax, customs, or certification advice.
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 and build expressive 3D scenes, explainers and interactive models with grounded subject knowledge. Use for 3D creation or edits, including scientific visualization and spatial puzzles.
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 the user asks which model to use, wants to compare models, or needs guidance on selecting between Kling, Wan (incl. Wan 3.0), Seedance (incl. 2.5), Veo 3, Minimax Hailuo / MiniMax H3, FLUX 3 Video, Gemini Omni Flash, Soul, Nano Banana, GPT Image 2.5, or other Higgsfield engines — including which lane edits existing footage (video_edit, Kling 3.0 Omni Edit, FLUX 3 Video Edit, Genjutsu, Ad Multiplier) and which models make one clip longer than 15s.
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 the user mentions GPT Image 2.0 or GPT Image 2.5, gpt-image-2, gpt-image-2.5, gpt_image_2_5, GPT-Image-2 prompts, the Flare / Sunburst variants, a transparent-background image, or wants to generate an image with GPT Image 2.0 or 2.5. Covers when to prefer GPT Image 2.5 over 2.0 (transparent background, xhigh/max quality, extra aspect ratios — from platform and OpenAI facts), the CLI-vs-MCP disagreement on gpt_image_2, the three-format prompt taxonomy (Format A structured JSON for UI mockups and layout-dense images; Format B dense cinematic prose for single-subject scenes; Format C auto-derive meta-prompt for theme-only concepts), per-format craft patterns, output conventions, the 6-item pre-delivery checklist, and cross-surface workflow context (companion static-ads-workflow.md for ad recreation; higgsfield-marketing-studio cross-surface-workflow.md §3 for ms_image / DTC Ads Higgsfield-native alternative).
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。
在Python中复现C#的Quaternion.AngleAxis方法，根据角度和旋转轴计算四元数，且不使用numpy.quaternion库。
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。
Convert a taxonomy (`outline/taxonomy.yml`) into a bullet-only outline (`outline/outline.yml`) with sections/subsections.
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。