'simulator' 검색 결과

Audit and safely clean Xcode-related developer storage on macOS. Use whenever a developer mentions low disk space, Xcode storage, DerivedData, simulator devices or runtimes, stale beta platforms in Xcode Settings, DeviceSupport, archives, dSYMs, CocoaPods caches, simulator dyld caches, project .build folders, downloaded Xcode DMGs/XIPs, duplicate Xcode installers, or old Xcode applications. Also use this skill proactively when you hit low storage during other work, such as a build, download, or install failing with an out-of-disk-space error. Always measure first, report recoverable GiB with evidence, and obtain explicit itemized approval before any mutation.

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Generate 20,000+ particle swarm simulators in two modes: sandbox (complete Three.js host runtime with gesture controls, security validation, code injection pipeline) and sim (behavior function bodies that position/color particles via a sandboxed API). The AI writes ONLY a function body — the host handles rendering, input, and security. Triggers on particle swarm, swarm simulator, particle behavior, swarm sandbox, gesture particles, 20K particles, particle function body, swarm sim, particle playground.

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当用户希望使用 msOpProf（`msprof op` / `msprof op simulator`）对昇腾 AI 算子做上板或仿真性能调优、解释 `aic-metrics`/`trace.json`/`visualize_data.bin`、选择 device vs simulator 路径、排查 `--soc-version`/`--export`/`signal 6`/`Bad address`/热点图或流水图相关问题，或要求生成固定分析报告模板（算子基本信息 / 关键数据 TOP5 / 核心瓶颈 TOP5 / 优化建议 TOP5）时，使用本技能。它负责先判定模式、输入形态与芯片/能力边界，再给出正确命令、结果解读、固定报告输出与高频踩坑规避；不要把经验案例当成通用规则。

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Set up the local iOS dev/build toolchain for NowStack Mobile: Xcode, Simulator, CocoaPods, Watchman, mobile deps, and first `expo run:ios`. Use for `/ns setup-ios`, simulator preview, `expo run:ios` failures, or before local TestFlight builds. macOS only; signing is `/ns ios setup`.

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Set up local iOS dev/build tooling for NowStack Mobile: Xcode, Simulator, CocoaPods, Watchman, mobile deps, and first `expo run:ios`. Use for `/ns ios local-setup`, legacy `/ns setup-ios`, simulator preview, or local TestFlight prerequisites. macOS only; signing is `/ns ios setup`.

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Verify NowStack Mobile iOS/Expo changes in the Apple Simulator with `xcrun simctl`. Covers single or parallel Metro/device flows, deep-link navigation, preview routes, and OTP sign-in. Use for `ns ios verification`, "test on simulator", or changed `mobile-app/**`; never use computer-use.

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iOS platform development for Pulp — iPhone/iPad AUv3 app extensions, iOS Simulator builds, UIKit window host, CoreAudio IO audio, touch & Apple Pencil input, XcodeBuildMCP automation. Covers configure, build, deploy to simulator/device, and the gotchas discovered during iOS bringup.

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Safely simulates and applies Google Cloud IAM v1 (Allow) policy changes. Uses the Policy Simulator to replay historical access logs against proposed policies to prevent breaking active workloads before applying the changes. Use when simulating or applying IAM v1 allow policies across Projects, Folders, or Organizations. Don't use for analyzing IAM v2 deny policies, VPC Service Controls, or performing general policy troubleshooting.

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GitHub Actions workflow patterns for React Native iOS simulator and Android emulator cloud builds with downloadable artifacts. Use when setting up CI build pipelines or downloading GitHub Actions artifacts via gh CLI and GitHub API.

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アプリケーションに LLM API(OpenAI / Anthropic / Gemini 等)を組み込む際のコスト最適化・セキュリティ・運用の必須パターン集。 「AI機能を付けて」「AIで読み取り」「画像認識」「PDFから抽出」「OCR」「自動分類」「レコメンド」「AI連携」「OpenAI APIを使う」 「チャットボット」「LLMを組み込む」などの文脈で、新規アプリ・既存アプリを問わず必ず使用する。 ユーザーが「AI」と明示しなくても、非構造データ(画像/PDF/自由文)からの情報抽出・分類・判別の要件が含まれるなら必ずこのスキルを読むこと。 AI機能のコスト見積・APIキー管理・利用量ダッシュボードの設計・レビューでもトリガーする。 実測グラウンディング付きの費用試算が必要な場合は Skill llm-cost-simulator を併用。 既定スタック(社内業務アプリ、mvp-first)の必須スキルではない optional 群。上記の AI 要件が要件定義で明示された場合、 または app-orchestrator の要件フラグ「AI機能あり」で指示された場合のみロードする。

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アプリの本番品質を保証する統合スキル。セキュリティ監査・例外/エラー処理設計・攻撃別対処・ サーバーコスト最適化・パフォーマンス最適化を1つのゲートで検査する。 「セキュリティチェックして」「リリースしていい？」「本番公開前の確認」「脆弱性診断」「監査して」 「エラー処理を設計して」「例外処理を入れて」「攻撃対策」「レート制限」「コストを抑えたい」 「無料枠に収めたい」「パフォーマンス改善」「重い」などの文脈で必ず使用する。 また、認証・ユーザー入力・API・決済・機密データを扱うコードを書いた直後、およびデプロイ前には ユーザーが明示しなくても本スキルの該当セクションを適用する。 デプロイ手順自体は Skill cloudflare-secure-deploy、認証実装は Skill better-auth-google-gate、 LLMコストは Skill llm-api-integration / llm-cost-simulator を併用する。

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Use XcodeBuildMCP to build, run, launch, and debug the current iOS project on a booted simulator. Trigger when asked to run an iOS app, interact with the simulator UI, inspect on-screen state, capture logs/console output, or diagnose runtime behavior using XcodeBuildMCP tools.

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21 production-ready scripts for iOS app testing, building, and automation. Provides semantic UI navigation, build automation, accessibility testing, and simulator lifecycle management. Optimized for AI agents with minimal token output.

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Build, run, and debug iOS apps on Simulator with XcodeBuildMCP. Use when launching an app, inspecting simulator UI or logs, or diagnosing runtime behavior.

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Fetch Airbnb income estimate (ADR, occupancy, monthly revenue) for any area using the official Airbnb GraphQL API — the same data the Airbnb host simulator shows. Input: station/area name. Output: per-night rate, avg nights, monthly estimate for entire_home and private_room.

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iOS プロジェクトのスキーム・ターゲット・シミュレータ・ビルド設定を XcodeBuildMCP 経由で表示。「scheme」「target」「simulator」「destination」「bundle ID」「build settings」「スキーム一覧」「ターゲット一覧」「シミュレータ一覧」「ビルド設定」などのキーワードで自動適用。

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iOS 開発ワークフローのオーケストレーター。XcodeBuildMCP ベースのフォアグラウンドサブエージェントを使い分け、ビルド・テスト・実行・UI 検証をコンテキスト隔離で実行する。「iOS」「Xcode」「Swift」「build」「test」「compile」「simulator」「xcodebuild」「preview」「SwiftUI」「ビルド」「テスト」「コンパイル」などのキーワードで自動適用。

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Starts a CARLA UE 5.8 server from a ue58-dev tree — the editor binary in -game mode (the working headless server), the packaged shipping build, or the full editor — with offscreen/nullrhi rendering, custom RPC and streaming ports, and native ROS 2 via the single-dash -ros2 flag. Probes a running server, and stops one cleanly despite the 15-character process-name truncation. Use when the user asks to "run/start CARLA UE5", "launch a ue58 server", "run headless", "publish ROS 2 topics from UE5", or a client cannot reach the simulator.

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Cooks and packages CarlaUE4 into distributable tarballs under Dist/ — either the full simulator or a standalone asset package of selected maps and props for later import. ROS2=1 keeps the native ROS 2 interface in the cooked package (a plain cook silently drops it). Use when the user asks to "package CARLA", "make a Dist build", "cook the project", "export a map as a package", "package CARLA with ROS2", or needs a build with working camera and lidar sensors.

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Installs the CARLA Python client (the `carla` package) into a chosen interpreter so the other python-api skills work — from a wheel bundled with your release or checkout, from PyPI (`pip install carla==X.Y.Z`), or by putting an older release's .egg on PYTHONPATH. Detects what is already present, picks the source that matches your simulator's version, pins numpy<2, and verifies `import carla` plus the client/server version match. Use when the user asks to "install the CARLA Python API", "pip install carla", "set up the carla python package", or when a skill reports "cannot import carla".

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Writes a new ScenarioRunner scenario — a Python class deriving from BasicScenario with its behaviour tree assembled from srunner atomic behaviours and criteria, plus the XML config that gives it a town, ego spawn and parameters — and registers it so `--scenario MyScenario_1` works. Also covers adding a scenario to a route via --additionalScenario. Generates a working skeleton and validates it without a simulator. Use when the user asks to "create/write a new scenario", "add a custom scenario", "make my own traffic situation", or wants to extend the scenario library.

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Writes a new Scenic scenario (.scenic) from a natural-language description — "a car cuts in from the right lane", "a pedestrian crosses in front of the ego", "negotiate an unsignalized four-way" — by turning the request into a spec, generating the file from idioms proven on this build, and validating it by compiling and sampling before any simulator is involved. Use when the user asks to "write a Scenic scenario", "create a .scenic file", "turn this description into Scenic", "generate a scenario from text", or wants a Scenic scenario authored or repaired.

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Reads and summarises ScenarioRunner output — the criteria pass/fail tables from --output/--file, the machine-readable --json and --junit result files, and the criteria JSON written alongside a --record recording — and runs the metrics module (metrics_manager.py) to compute custom measurements over a recorded run offline, without the simulator. Use when the user asks "did the scenario pass", "why did it fail", "summarise these results", "compare these runs", or wants distance/speed/lane metrics from a recording.

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Runs Scenic probabilistic scenarios against a running CARLA server with the `scenic FILE --simulate --2d` CLI — the carlaChallenge1-10 traffic scenarios shipped by ScenarioRunner (`model srunner.scenic.models.model`) and by Scenic itself (`model scenic.simulators.carla.model`) — bounding the run, sampling scenes headlessly first to tell a map problem from a syntax problem, and restoring the world afterwards. Use when the user asks to "run a Scenic scenario", "run carlaChallenge", "test a .scenic file", "scenic --simulate", or reports a Scenic scenario that rejects every sample or cannot find blueprints.

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