Use when integrating Google Gemini API into projects. Covers model selection, multimodal inputs, streaming, function calling, and production 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。
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概要と使いどころ
Use when integrating Google Gemini API into projects. Covers model selection, multimodal inputs, streaming, function calling, and production 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。
Database design principles and decision-making. Schema design, indexing strategy, ORM selection, serverless databases.
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。
Browser automation powers web testing, scraping, and AI agent interactions. The difference between a flaky script and a reliable system comes down to understanding selectors, waiting strategies, and anti-detection patterns.
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 choosing an animation engine, defining motion tokens, adding scroll effects or micro-interactions, or auditing motion for accessibility and performance. Covers engine selection (GSAP, Motion.dev, Anime.js, React-Spring, Three.js, CSS Native), DTCG motion tokens, and the anti-slop/a11y quality gate.
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 one Claude Code session must supervise several others on this machine — adopting sessions the user started by hand, or spawning workers itself. Covers roster, status requests, a GO board, idle notices, and the GO-token protocol. Works with AOS alone; the AO daemon is optional.
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。
Linear multi-agent build pipeline with file hand-offs in production_artifacts/, run after /bdbrainstorm or /grill-me. This is the linear variant — no state.json, no repair loop, no dispatcher graph — distinct from startcycle-graph, which adds durable state and automated escalation. Use when an approved plan should be built, when the user types /startcycle or "run a startcycle", or when you pick a startcycle variant from the situation yourself (no user prompt needed).
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。
API design principles and decision-making. REST vs GraphQL vs tRPC selection, response formats, versioning, pagination.
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。
agenttrail: live map of a multi-agent build in the browser: which plan component is being worked on, by which agent or harness, what is done and what is stuck. Use when a multi-agent pipeline starts (/startcycle, /startcycle-graph, /teamwork-preview) or after a plan-canvas approve, when the user asks to see what the agents are doing ("live map", "build board", "who is running now"), or by yourself whenever a multi-agent run is under way — no user prompt needed.
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。
AI-driven data extraction from 55+ Actors across all major platforms. This skill automatically selects the best Actor for your task.
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。
LLM Agent engineering: pattern selection (12-mode matrix), data simulation, convergence iteration. Covers intent routing, function calling, ReAct, MCP, prompt chaining, guardrails, evaluation.
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。
Frontend design blueprints with craftsmanship scoring, self-critique loops, and engineering handoff. Aesthetic intelligence against AI homogeneity. Use for: UI/UX design specs, design system creation, visual direction exploration, component design review, design-to-engineering handoff.
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。
Choose animation values that feel native on Apple platforms instead of guessing springs. Use when: picking a spring/duration/easing for any transition; an animation "feels off", sluggish, floaty, wobbly, or cheap; tuning a sheet, drawer, panel, selection lens, button press, or drag release; wiring gesture-driven motion; or someone asks "what spring should I use", "why does this feel wrong", "make it feel native/premium", "match Apple's feel". Also fires on hand-picked magic numbers in .spring(), on animations that jump when interrupted, and on motion that only starts after a gesture ends.
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。
Animation, morphing, and shader best practices for Liquid Glass and SwiftUI motion on iOS 26+/macOS 26+ through iOS 27. Use when animating glass or building UI motion: glassEffectID, @Namespace morphing, GlassEffectContainer spacing, glassEffectUnion, glassEffectTransition (.matchedGeometry/.materialize), withAnimation, springs, UnitCurve, PhaseAnimator, KeyframeAnimator, @Animatable, matchedTransitionSource, navigationTransition zoom, scrollTransition, visualEffect, Metal shaders (colorEffect, distortionEffect, layerEffect, [[stitchable]]), accessibilityReduceMotion gating, Instruments/xctrace profiling of hangs and animation hitches. Also fires on symptoms: glass morph not animating, view pops in instead of morphing, glass fades instead of materializing, morph flickers with Reduce Motion, menu glass morphs as a rectangle, animation runs on insert but not removal, PhaseAnimator loops forever or fires once, shader shows clipped edges (maxSampleOffset), animation hitches or main-thread hangs while scrolling glass chrome. For static glass, availability gating, toolbars, UIKit/AppKit glass, or accessibility of the material itself use the liquid-glass skill first.
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。
When designing loosely coupled systems that react to state changes asynchronously.
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。
Collect, download, and verify App Store Connect Analytics reports with asc. Use when users need to discover analytics report requests, select report instances by processing date or granularity, download every segment, or verify downloaded files against Apple's size and MD5 metadata before analysis.
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。
Implement, review, or improve data visualizations using Swift Charts. Use when building bar, line, area, point, pie, or donut charts; when adding chart selection, scrolling, or annotations; when plotting functions with vectorized BarPlot, LinePlot, AreaPlot, or PointPlot; when customizing axes, scales, legends, or foregroundStyle grouping; or when creating specialized visualizations like heat maps, Gantt charts, stacked/grouped bars, sparklines, or threshold lines.
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。
Implement, review, or improve photo picking, camera capture, and media handling in iOS apps using PhotoKit and AVFoundation. Use when working with PhotosPicker, PHPickerViewController, camera capture sessions (AVCaptureSession), photo library access, image loading and display, video recording, or media permissions. Also use when selecting photos from the library, taking pictures, recording video, processing images, or handling photo/camera privacy permissions in Swift apps.
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。
Display and manipulate PDF documents using PDFKit. Use when embedding PDFView to show PDF files, creating or modifying PDFDocument instances, adding annotations (highlights, notes, signatures), extracting text with PDFSelection, navigating pages, generating thumbnails, filling PDF forms, or wrapping PDFView in SwiftUI.
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。
Benchmark Xcode clean and incremental builds with repeatable inputs, timing summaries, and timestamped `.build-benchmark/` artifacts. Use when a developer wants a baseline, wants to compare before and after changes, asks to measure build performance, mentions build times, build duration, how long builds take, or wants to know if builds got faster or slower.
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。
Translate Figma designs into production-ready SwiftUI code with 1:1 visual fidelity using the Figma MCP workflow. Trigger when the user provides Figma URLs or node IDs and wants iOS/SwiftUI implementation, asks to implement a design or component from Figma for an iOS app, or references Figma selections in the context of an Xcode/SwiftUI project. Also trigger when user asks to inspect Figma designs for iOS planning, fetch design tokens for SwiftUI, or convert Figma assets for Xcode. Requires a working Figma MCP server connection. Do NOT trigger for web/React implementations.
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。
Devil's-advocate attack on AI workflow designs — threat model, assumption challenges, code critiques, and hypothetical redesigns with no file edits. Use for "attack this design", devil's advocate, or hostile challenge on agents/tools/summarization/tokens. Not for PR peer review (code-review) or self-review that applies fixes (ai-systems-review). Prefer: this skill → decide → ai-systems-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。
Structured 3-phase peer review of a diff or PR — intent, issues by severity, then pointed merge-readiness questions and a verdict. Use for general code review. Not for AI workflow self-fix-and-edit (ai-systems-review) or no-edit devil's-advocate threat models (adversarial-challenge). Phase 3 asks questions only; it is not the adversarial-challenge 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。
Generate a polished frontend reference screenshot through a configurable GPT-image-2-compatible generations endpoint, save and show versioned previews inside the project, revise selected previews through a configurable /images/edits endpoint, and reproduce only the user-approved design as functional frontend code with high visual fidelity. Use when Codex is asked to design, build, restyle, or recreate a web page, application screen, dashboard, landing page, or UI component through an image-first workflow, design approval loop, screenshot-driven implementation, pixel matching, or a 1:1 frontend recreation.
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。
Discuss a community-edition product requirement with the user, draft a bilingual (Chinese + English) PRD for review, then — after explicit user approval — create the English-only issue on GitHub (<OWNER/REPO>). Use whenever the user wants to turn a requirement (from a Feishu doc, a meeting note, a customer ask, or a rough idea) into a GitHub issue. Triggers on phrases like "create requirement doc", "create a requirement", "put this requirement on GitHub", "create new feature issue", "draft an issue for...", or anytime the user describes a product feature/improvement they want tracked. The format is opinionated (Background / Goal / Spec / Verification / Related, NO implementation details, draft shown bilingually for human review, issue itself written in English only).
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。