「apa」の検索結果

Assemble the FREE steps of the product-hypermotion + kinetic-typography video format — dice ONE Seedance 2.0 hypermotion clip into 5-6 segments and intercut them with PIL kinetic-typography spec/CTA cards (italic skew, 1.08x outline echo, 3D extrusion, slam-with-shake, inversion flash) plus a real-logo PIL end card (base64-decoded from the brand SVG), center-crop 1:1 to 9:16, and explicit-map mux a music bed. Deterministic, FREE (PIL + FFmpeg), no paid calls, the real logo and spec typography stay pixel-crisp. The paid steps (the ONE Seedance i2v, the music) are separate capabilities; the recipe orchestrates them. Use for the product-hypermotion format.

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。

Assemble an Apple Notes list video ad from a note + end-card JSON — a frame-accurate fake iPhone screen recording of a short list being typed into Apple Notes (character by character, key pops, blinking caret, the note scrolling up as it fills) crossfaded into a checklist end card (the note's picks as ticked rows, real product photos, logo, CTA, in the brand's colours and fonts), with an optional music bed. FREE assembly (Playwright + ffmpeg); the recipe supplies the per-brand note + end card and gates the paid music call to its own capability. The Apple Notes sibling of render-imessage-chat and render-chatgpt-chat. Use for the apple-notes format.

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 the deterministic PIL pill overlays for a 'perfect-score + proof-points' UGC video ad (white 10/10 score header with a medal + orange sub with a finger-down + 3-4 green-check proof pills) and composite them onto a base clip in a diagonal L->R->L->R cascade, then mux the music bed into master-final.mp4. Config-driven (config.json), 1080x1920 9:16, FREE and deterministic (no paid calls, text stays pixel-crisp). Use for the overlay-proof-points format; the base clip + music come from separate paid capabilities.

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。

Assemble an absurdist animated-explainer video ad (~38s, 9:16) from per-scene i2v clips + their measured VO windows — retime each clip to its VO, re-encode every segment to identical 30fps/libx264/yuv420p so the concat demuxer never drops frames, concat, build a REAL-product PIL end card (never AI) held static, mix VO (loudnorm I=-14) under music (loudnorm I=-26, volume 0.62, amix normalize=0), and burn libass captions last. FREE deterministic assembly (bash-free, Python + ffmpeg + PIL); the recipe supplies the clips, VO, music, product photo, palette, and caption table and gates the paid keyframe/clip/VO/music calls to their own capabilities. Use for the absurdist-explainer format.

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。

Shared helper that routes ALL paid media generation (FAL image/video, ElevenLabs music) through the GooseWorks proxies so every call bills the Ads agent — never a provider SDK's default host. Host-swaps the FAL queue URLs, loads the agent token from the sandbox env (GW_MEDIA_PROXY_TOKEN) or ~/.gooseworks/credentials.json, and returns the result CDN URL. Every video-ad media capability imports this; templates never call a provider directly.

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。

Render a configurable iMessage conversation inside a properly framed phone, then a brand end card. Uses the original send/receive sounds and a shared frame timeline for text, typing, scrolling and sound. Free local Playwright + ffmpeg assembly; optional image/music generation belongs to separate gated capabilities.

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。

Governs Microsoft Fabric OneLake catalog health, protection, and trust through Fabric Admin, Core, and Power BI REST APIs. Use for tenant or owner-scoped audits and guarded remediation of domains, workspace assignment, capacity, labels, tags, descriptions, refresh, and item identity. Catalog item discovery belongs to search-consumption-cli.

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Renders Hi-C contact matrices honestly and reproducibly with matplotlib, cooltools, HiCExplorer, pyGenomeTracks, FAN-C, CoolBox, and plotgardener. Covers the raw/ICE-balanced/observed-over-expected transform choice, LogNorm vs symmetric-diverging colormaps with vmax/percentile clipping, resolution-to-feature matching (compartments 100-500kb, TADs 10-40kb, loops 5-10kb), square vs rotated-triangle track-stacking, NaN/white-stripe handling, virtual 4C, APA/saddle/on-diagonal pileups, two-condition side-by-side and log2-ratio maps, and interactive (HiGlass) vs scripted-static publication figures. Use when plotting a contact matrix, choosing a normalization or color scale, building a multi-track Hi-C figure, making a virtual 4C profile, piling up loops/boundaries, or comparing two conditions.

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。

Analyzes single-cell pooled CRISPR screens (Perturb-seq, CROP-seq, Perturb-CITE-seq, ECCITE-seq, multiome) where each cell carries an sgRNA and a scRNA-seq / surface-protein / chromatin readout. Covers experimental design (direct-capture Perturb-seq Dixit 2016 vs CROP-seq 3'UTR-barcoded Datlinger 2017 vs ECCITE-seq vs Multiome), MOI for sgRNA assignment, escaper-cell filtering (Mixscape, Papalexi 2021), SCEPTRE NB GLM + permutation for low-MOI (Barry 2024 Genome Biol 25:124), the Pertpy framework, factor decomposition, genome-scale Perturb-seq (Replogle 2022 Cell, 2.5M cells), and per-perturbation single-cell DE. Use when running a single-cell CRISPR screen, choosing direct-capture vs CROP-seq architecture, filtering escaper cells, performing single-cell DE, integrating Perturb-seq with pathway analysis, scaling to GW CRISPRi via Replogle protocol, or analyzing multi-omics screens.

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。

Installs 425 bioinformatics skills covering sequence analysis, RNA-seq, single-cell, variant calling, metagenomics, structural biology, and 56 more categories. Use when setting up bioinformatics capabilities or when a bioinformatics task requires specialized skills not yet installed.

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。

Support automatic audio switching for paired third-party Bluetooth headphones or earbuds with AudioAccessoryKit. Use when a companion app registers an audio accessory, an app extension reports worn/removed placement or connected source-device changes, or AccessoryControlDevice capabilities and errors need handling. Do not use for general AVAudioSession routing, Bluetooth transport, or initial accessory pairing.

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。

Integrate Apple Pay payments and Wallet passes using PassKit. Use when adding Apple Pay buttons, creating payment requests, handling payment authorization, adding passes to Wallet, configuring merchant capabilities, managing shipping/contact fields, or working with PKPaymentRequest, PKPaymentAuthorizationController, PKPaymentButton, AddPassToWalletButton, PKPass, PKAddPassesViewController, PKPassLibrary, Wallet pass distribution, or Apple Pay checkout flows for physical goods, real-world services, donations, and eligible recurring payments.

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 iOS App Clips with invocation URLs, App Clip Codes, NFC, QR codes, Safari banners, Maps, Messages, target setup, App Store Connect experiences, size/capability constraints, NSUserActivity routing, SKOverlay promotion, App Group/keychain handoff, ephemeral notifications, location confirmation, and full-app migration. Use when creating App Clips or wiring App Clip invocation, experience configuration, or full-app 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。

Build alternative browser engines using BrowserEngineKit. Use when developing a non-WebKit browser engine for iOS/iPadOS in supported regions, managing web content/rendering/networking extension processes, configuring GPU and networking process capabilities, checking alternative-engine device eligibility, or reviewing BrowserEngineKit entitlements and Info.plist setup.

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 when the user asks what information a Stripe Connect connected account must provide for verification, onboarding, KYC, or account requirements; when they need to compare requirements between connected-account setups; or when they ask which verification fields, documents, or business details are required for a particular platform country, account country, business type, dashboard, service agreement, or capability.

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 wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this 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。

构建、调试与发布 Tauri v2 应用的工程化工作流。覆盖项目初始化（create-tauri-app）、前端与 Rust 命令通信（`#[tauri::command]` + `invoke`）、状态管理、Capabilities 权限建模、插件接入、跨平台构建与问题排查。当用户需求涉及“创建 Tauri 项目”“把 Web 前端接到 Rust 后端”“最小权限配置（fs/http/shell）”“接入 Tauri 官方插件”“执行 tauri dev/build”“排查 Tauri 构建或运行错误”时使用此 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。

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。

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。

Model, simulate, and optimize Serializer/Deserializer (SerDes) systems — serial and parallel links — using MATLAB SerDes Toolbox. Design NRZ and PAM-N links (PAM3 through PAM16) — explore equalization architectures (FFE, CTLE, DFE), sweep or optimize parameters with genetic algorithms, and characterize channels from loss models, S-parameter files, or crosstalk scenarios. Process captured waveforms through equalization chains, build eye diagrams, and decompose jitter. Deliver IBIS-AMI models for Tx, Rx, Redriver, or Retimer by exporting to Simulink and compiling .ami/.ibs/.dll/.so files. Covers the full arc from initial design exploration and parameter optimization to compliance testing and compiled model validation, including custom datapath blocks for nonstandard equalization.

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。

Extract battery features for degradation analysis and health monitoring in MATLAB. Covers cycling test features, differential curves (IC/DV/DT), and measurement statistics. Use when working with battery cycling data, SOH estimation, RUL prediction, or any battery test data analysis in MATLAB. Triggers on battery* functions such as batteryTestDataParser, batteryTestFeatureExtractor, batteryMeasurementFeatures, batteryDifferentialCurves.

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。

Handle security incidents with IR playbooks and procedures. Implement detection, containment, eradication, and recovery processes. Use when responding to security events or building incident response capabilities.

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。

Automate security workflows and remediation. Build security pipelines, automate compliance checks, and implement SOAR capabilities. Use when scaling security operations or implementing DevSecOps.

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。