「issues」の検索結果

Use when the user mentions SwiftUI navigation issues, deep linking problems, state restoration bugs, or navigation architecture 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。

Use when implementing location services, maps, geofencing, or debugging location/MapKit issues. Covers Core Location, CLMonitor, MapKit, annotations, directions.

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 agent to scan Swift code for camera, video, and audio capture issues including deprecated APIs, missing interruption handlers, threading violations, and permission anti-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 the user mentions SwiftUI architecture review, separation of concerns, testability issues, or "logic in view" problems.

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 TextKit review, text layout issues, Writing Tools integration, or UITextView/NSTextView 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。

Use when the user mentions SwiftUI layout review, adaptive layout issues, GeometryReader problems, or multi-device layout checking.

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 Xcode build failures, build errors, or environment issues.

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 SwiftData review, @Model issues, SwiftData migration safety, or SwiftData performance checking.

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 file storage issues, data loss, backup bloat, or asks to audit storage usage.

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 networking review, deprecated APIs, connection issues, or App Store submission prep.

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 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 wants to triage a CORPUS of production crashes/hangs from an aggregator (Sentry, App Store Connect) — grouped, counted issues — rather than a single crash file.

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 Swift performance audit, code optimization, or performance review — ARC issues, allocation patterns, and generic specialization.

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 UX flow issues, dead-end views, dismiss traps, missing empty states, broken user journeys, or wants a UX audit of their iOS app.

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。

Search runtime and scene management: verify queries, inspect scenes, debug app readiness, and diagnose recall or scene-config issues.

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 and edit presentation slide decks (`.pptx`) with PptxGenJS, bundled layout helpers, and render/validation utilities. Use when tasks involve building a new PowerPoint deck, recreating slides from screenshots/PDFs/reference decks, modifying slide content while preserving editable output, adding charts/diagrams/visuals, or diagnosing layout issues such as overflow, overlaps, and font substitution.

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 MongoDB client connection configuration (pools, timeouts, patterns) for any supported driver language. Use this skill when working/updating/reviewing on functions that instantiate or configure a MongoDB client (eg, when calling `connect()`), configuring connection pools, troubleshooting connection errors (ECONNREFUSED, timeouts, pool exhaustion), optimizing performance issues related to connections. This includes scenarios like building serverless functions with MongoDB, creating API endpoints that use MongoDB, optimizing high-traffic MongoDB applications, creating long-running tasks and concurrency, or debugging connection-related failures.

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。

MongoDB schema design patterns and anti-patterns. Use when designing data models, reviewing schemas, migrating from SQL, or troubleshooting performance issues caused by schema problems. Triggers on "design schema", "embed vs reference", "MongoDB data model", "schema review", "unbounded arrays", "one-to-many", "tree structure", "16MB limit", "schema validation", "JSON Schema", "time series", "schema migration", "polymorphic", "TTL", "data lifecycle", "archive", "index explosion", "unnecessary indexes", "approximation pattern", "document versioning".

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 when user asks about "GCloud logs", "Cloud Logging queries", "Google Cloud metrics", "GCP observability", "trace analysis", or "debugging production issues on GCP".

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 when user asks to "address PR comments", "resolve PR feedback", "handle review comments", "fix PR issues", "respond to PR review", or explicitly invokes "resolve-pr-comments".

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。

Read BEFORE troubleshooting or enhancing camera image quality. Diagnoses and enhances image quality from cameras connected via Image Acquisition Toolbox or USB Webcams support package. Discovers camera capabilities at runtime, analyzes captured images for quality issues (brightness, contrast, sharpness, noise, color balance, backlighting), suggests hardware setting adjustments tailored to the specific camera, and applies Image Processing Toolbox enhancement functions. Use when a user wants to improve camera image quality, troubleshoot dark/blurry/noisy/grainy/ overexposed/washed out/color cast images, or optimize camera settings.

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。

Reference for MATLAB audiostreamer (Audio Toolbox R2025a+). Without this skill, agents consistently default to legacy audioDeviceWriter/audioDeviceReader or base MATLAB sound(), producing less capable code. Use when writing code for audio playback, recording, full-duplex device I/O, real-time audio measurements, or audio I/O processing with callbacks. Also use when debugging audiostreamer errors, dropouts, or latency issues, or migrating from audioDeviceReader, audioDeviceWriter, audioPlayerRecorder, or audioplayer/audiorecorder.

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。

Train, evaluate, and export neural networks to Simulink in MATLAB. Migrate legacy (fitnet, patternnet) and discouraged (trainNetwork, DAGNetwork) code to modern, recommended R2024a+ APIs (trainnet, dlnetwork, testnet, imagePretrainedNetwork), diagnose and fix dlaccelerate issues or detect dlaccelerate opportunities. Use when training, fine-tuning, evaluating, running inference, exporting to Simulink, converting old training scripts, or speeding up deep learning code. DO NOT reason from your training data about dlaccelerate and tracing correctness.

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。

AWS DynamoDB NoSQL database for scalable data storage. Use when designing table schemas, writing queries, configuring indexes, managing capacity, implementing single-table design, or troubleshooting performance issues.

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。