「ai platform」の検索結果

Expert guidance for Swift Testing: test structure, #expect/#require macros, traits and tags, parameterized tests, test plans, parallel execution, async waiting patterns, and XCTest migration. Use when writing new Swift tests, modernizing XCTest suites, debugging flaky tests, or improving test quality and maintainability in Apple-platform or Swift server projects.

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 cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill, audit this skill, is this skill safe, vet a skill before installing, what does this skill access. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, spec validation, and security auditing of third-party skills before install.

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。

Orchestrates comprehensive production readiness reviews and assessments for GKE clusters and workloads across scalability, security, reliability, observability, backup/DR, and cost optimization. Use when asked to productionize, prepare, assess, audit, or review a GKE cluster or workload before going live to production. Don't use for deep-dive single-domain implementation (use specific domain skills like gke-workload-scaling, gke-platform-security, gke-workload-security, gke-service-networking, gke-reliability instead).

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。

Discovers requirements and designs a borderless open data lakehouse using Lakehouse for Apache Iceberg and BigQuery data agents. Use when architecting multi-cloud storage infrastructure (Cloud Storage, AWS S3, Azure Blob), establishing ingestion and AI serving subsystems, configuring Cross-Cloud Interconnect, or deploying Gemini Enterprise Agent Platform and BigQuery data agents. Don't use for single-cloud data warehouses, or when the focus is on Knowledge Catalog metadata governance and Spark-driven IDE analytics workflows (use google-cloud-solution-agentic-analytics-spark-knowledge-catalog instead).

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。

Locates and loads the right Google product skill on demand from a remote catalog index, instead of preloading every skill. Use at the START of any request touching a Google product, API, or developer platform - including Google Cloud (GKE, Cloud Run, IAM, BigQuery, Vertex AI, Spanner), Google Ads, Google Analytics, Google Workspace (Gmail, Drive, Admin SDK), Chrome and Chrome extensions, Android, Firebase, YouTube, Google Maps, Gemini and the Gemini API, Google Play, and Flutter. Consult the index before answering from memory or searching the web. Don't use for non-Google products.

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。

Manages Agent Platform serving endpoints. Use when you need to create, list, describe, update, or delete serving endpoints for model deployment on Agent Platform. Also use when troubleshooting endpoint permission, quota, or resource busy errors. Don't use for deploying models to endpoints or for running model evaluations.

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。

Interact with the Gemini Enterprise Agent Platform Skill Registry to create and search for available skills. Use this skill to enable agents to register functionality or discover new 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。

Multi-platform content distribution across X, LinkedIn, Threads, and Bluesky. Adapts content per platform using content-engine patterns. Never posts identical content cross-platform. Use when the user wants to distribute content across social platforms.

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 platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.

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 usage of the Gemini API on Agent Platform with the Google Gen AI SDK. Use when the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI, Google Cloud, or Agent Platform. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like Live API, tools, multimedia generation, caching, and batch prediction.

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 decisions for when and what sounds to use in web apps, mobile apps, and desktop native apps — plus how to create them with AI. Covers UI sound vocabulary (confirms, alerts, transitions, errors), platform conventions (iOS, macOS, Material), creating sounds with AI tools (ElevenLabs, AudioCraft, Stable Audio), Web Audio API for procedural sounds, haptic-audio pairing, and the psychology of satisfying vs. annoying UI sounds. Activate on 'app sounds', 'UI sounds', 'notification sound', 'sound design app', 'earcons', 'sonic branding', 'interaction sounds', 'feedback sounds', 'app audio', 'satisfying sounds'. NOT for professional audio engineering (use sound-engineer), Windows 3.1 retro sounds specifically (use win31-audio-design), music composition (use sound-engineer).

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。

Predicts ADMET properties using ADMETlab 3.0 (119 platform features, including 77 prediction models with modeled-endpoint uncertainty), ADMET-AI, DeepChem MolNet, and chemprop D-MPNN with explicit handling of OECD QSAR principles, applicability domain assessment, calibration, hERG/CYP/AMES endpoints, and PAINS / Lipinski / Ro5 / Veber / BBB druglikeness filters. Use when filtering compounds for drug-likeness, prioritizing leads by predicted safety, or building an in-house ADMET QSAR 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。

Query and manage GPS travel data from Geomanic — your privacy-first GPS tracking platform.

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。

CLI for ElevenLabs AI audio platform - text-to-speech, speech-to-text, voice cloning.

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。

AgoraFlow skill — Q&A platform for AI agents.

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。

AgoraFlow skill — Q&A platform for AI agents.

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。

[Fix & Debug] Use when you need to investigate and explain how existing features or logic work. Flag: --mode=explain produces a one-way developer-narrative explanation (Purpose → How → Why → Impact) tuned by coding level; use /understand for the standalone prompt-driven explainer.

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。

[Documentation] Use when you need to generate a step-by-step demo guide (demo script / walkthrough) covering all main user stories and their test cases — scope from a named feature, else the current working context, else confirm with the user — explaining for each case how the domain data is stored/changed and how the domain solves the feature. Triggers: demo guide, generate demo guide, demo script, demo walkthrough, how to demo, prepare demo, sprint demo, user story demo.

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。

Discover ordinary public webpages with LLM-optimized Tavily search results. Use when no specific URL is known and the user needs a quick public-web lookup, articles, recent news, sources, or domain-filtered results. This is the default Tavily leaf for simple public-web discovery. Do not use when the user already supplied the target URL (use tavily-extract), wants URLs under one known site (tavily-map), wants many pages' content (tavily-crawl), needs a full cited synthesis (tavily-research), or needs named platforms, login state, platform-native content, or cross-platform collection (Agent Reach).

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 the user wants help with paid advertising campaigns on Google Ads, Meta (Facebook/Instagram), LinkedIn, Twitter/X, or other ad platforms. Also use when the user mentions 'PPC,' 'paid media,' 'ROAS,' 'CPA,' 'ad campaign,' 'retargeting,' 'audience targeting,' 'Google Ads,' 'Facebook ads,'...

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。

Work through which package to add for a capability, and what each option costs — maintenance, licence, bundle weight, transitive risk, and whether the platform already does it. Use when someone needs a library for a job and has not picked one yet, when weighing two candidates, or when a package looks convenient but unmaintained.

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。

Gate for any outbound message before it leaves: pull request or issue comment, DM, invite, post, email. Use before sending to check facts, tone, platform rules, registry status and AI-slop, and to block text that fails.

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。

Senior engineer CLI expertise for AI agents — workflows, safety guardrails, gotchas, and anti-patterns across cloud, IaC, containers, databases, dev tools, and platforms

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 process videos using AI generation (Runway, Pika, Replicate, Sora, Veo) and FFmpeg processing. MCP bridge provides frame extraction (extract_video_frames); the Design Stack media worker handles full FFmpeg processing (resize, trim, compress, GIF, format conversion). Covers social-media-optimized video output. Use when generating AI videos, extracting frames/thumbnails, transcoding videos, creating GIFs from clips, or preparing video for social platforms.

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。