114 件 ・ 関連度順
概要と使いどころ
Discover Atlas Cloud image and video models, inspect their live schemas, and submit one confirmed media generation request with bounded GET polling. Use when integrating Atlas Cloud media APIs or generating images and videos without hard-coding stale model parameters.
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 asks to "monitor brand mentions", "set up social listening", "did anything spike about us this week", or "watch these accounts for buying triggers"; runs always-on keyless listening — a versioned listening-query architecture (brand variants incl. misspellings and 中文 names, exclusion terms, per-source syntax for HN Algolia / Bluesky / GDELT / Tavily), a mention sweep with six-class triage (crisis / bug / lead / praise / question / spam) each routed with an SLA, a 7-day rolling baseline with spike flags (the crisis trigger input), a B2B trigger watchlist (funding / hiring / launch signals), and an explicit coverage disclosure where X/IG/TikTok/LinkedIn/小红书 numbers are proxy-labeled, never Measured. Not for launch-window telemetry (T-0→T+30 rank and review polling) — use launch-monitor. 舆情监听/品牌提及监测/基线突刺/触发信号
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 asks to "monitor my launch", "track our Product Hunt / Hacker News ranking", or "watch the launch window"; runs the T-0 to T+30 window watch — pre-launch instrumentation verification (UTM/event checks, the upstream of RAMP P1), HN rank/points/comments polling with a comments-over-points flamewar early-warning (Estimated heuristic), PH votes/featured status, store charts and reviews, news echo, D0/W1/M1 KPI snapshots vs targets, spike-vs-sustain and owned-capture reads, and alert thresholds against the launch-tier KPI targets. Not for launch-day go/rollback calls — use launch-day-conductor; not for metric deep-dives — use performance-analyzer; not for SEO rank tracking — use rank-tracker. 发布监控/排名轮询/火焰战比/spike-sustain
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。
Analyze and tune AssemblyAI model choice, audio delivery, polling, Streaming v3 turns, concurrency, and downstream work. Use when pursuing measured latency or throughput goals. Trigger with "tune AssemblyAI" or "AssemblyAI latency".
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。
Analyze and design a typed AssemblyAI adapter that isolates SDK drift, regional routing, polling, and streaming lifecycles. Use when integrating an official SDK. Trigger with "AssemblyAI SDK pattern", "AssemblyAI adapter", or "wrap AssemblyAI".
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。
Analyze and design idempotency, bounded polling, per-service circuits, durable queues, DLQ/replay, degradation, and reconciliation for Adobe workloads. Use when the task requires adobe async reliability controls. Trigger with "Adobe reliability", "Firefly retry design", or "PDF job recovery".
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 narrow, version-pinned Adobe SDK and REST adapters with typed contracts, redaction, bounded polling, and compatibility evidence. Use when writing or upgrading integration code. Trigger with "Adobe SDK patterns", "wrap Adobe API", or "review Adobe client".
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。
Run a current Adobe Firefly image generation job with prompt approval, response-led polling, artifact custody, and cancellation. Use for approved creative automation. Use when the task requires firefly controlled async generation. Trigger with "generate with Firefly", "Firefly async job", or "Adobe image generation".
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。
Wire player input in Unity 6.3 LTS with the Input System package: Input Actions, action maps, the PlayerInput component, and reading values via callbacks or polling. Use when the project has a .inputactions asset or com.unity.inputsystem, or when the user mentions the Unity Input System, InputAction, action maps, PlayerInput, control schemes, or rebinding.
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。
Runway developer API: text-to-video, image-to-video, task polling, video upscale, lip-sync. Trigger phrases: runway, runway video, gen-4 video, runway upscale, runway lip sync.
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。
Kling AI video generation with client-side JWT auth: text-to-video, image-to-video, status polling, clip extend, lip-sync. Trigger phrases: kling, kling video, klingai, kling text to video.
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。
HeyGen avatar and talking-head video: prompt-to-video agent, multi-scene avatar video, status polling, avatar and voice lists. Trigger phrases: heygen, avatar video, talking head video, video agent.
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。
Luma Dream Machine video generation: text-to-video and image-to-video, status polling, cancel, image upload. Trigger phrases: luma, dream machine, luma video, ray video.
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。
Black Forest Labs FLUX image generation: flux-2-pro and flux-2-flex text-to-image with async polling. Trigger phrases: black forest labs, BFL, flux image, flux-2-pro, flux 2 generate.
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 before expensive VidSeeds MCP workflows - seeds, daily MCP call quotas, async jobId polling, when to call vidseeds_get_seed_balance, and avoiding retry loops on MCP_QUOTA_EXCEEDED or insufficient seeds.
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 Fabric deployment pipelines for ALM promotion across dev, test, and prod stages, including stage creation, workspace assignment, selective forward or backward deploys, operation polling, stage role assignments, and the pipeline and workspace permissions each action requires. For Git sync use git-integration-operations-cli.
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 battery drain, energy optimization, power consumption audit, or pre-release energy check — timer abuse, polling patterns, continuous location, animation leaks, and background mode misuse.
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。
Audit and prioritize performance work through bounded-work and forward-progress checks. Use when asked to find performance issues, investigate freezes/500s/OOMs, review retries or polling for no-progress loops, rank a performance backlog, or implement the next simple performance fixes.
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。
Replace arbitrary timeouts with condition polling for reliable async tests
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 and download images through APIMart's asynchronous GPT-Image-2 API. Use when Codex needs APIMart image generation, GPT-Image-2 text-to-image, image-to-image with reference URLs or local image files, 1k/2k/4k output, aspect-ratio control, task polling, or saving APIMart image results locally.
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 BullMQ job workflows in NestJS. Use when building queue processors, redis-throttler, Upstash limits, idle polling, stalled jobs, and retention policies.
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 tests have race conditions, timing dependencies, or inconsistent pass/fail behavior - replaces arbitrary timeouts with condition polling to wait for actual state changes, eliminating flaky tests from timing guesses
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 real-time features using Convex reactive queries that automatically update when data changes, enabling live collaboration, instant updates, and reactive UIs without manual polling. Use when building live dashboards, implementing collaborative editing, creating chat applications, showing real-time notifications, building activity feeds, implementing presence indicators, creating reactive search, or any feature requiring instant data synchronization across clients.
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 delays that must survive process restarts (e.g., 24-hour cart abandonment, scheduled follow-ups), waiting for human approval or external events with timeouts (review gates, webhook callbacks, async API completion), polling external services without losing state on crashes, calling other functions and awaiting their results, memoizing expensive operations so they don't re-run on retry, or running async work in parallel inside a workflow. Covers Inngest step methods: step.run, step.sleep, step.waitForEvent, step.waitForSignal, step.sendEvent, step.invoke, step.ai, plus patterns for loops and parallel execution.
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。