「spend」の検索結果

Create original short videos using the 事故悬停｜主动取样后独自离场 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants this causal, camera, motion, rhythm, or payoff structure with new subjects and surfaces.

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 original short videos using the 世界悬停｜持续靠近到末端复流 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants this causal, camera, motion, rhythm, or payoff structure with new subjects and surfaces.

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。

Turn a song into a beat-synced music video with Guaardvark's Director: song analysis, per-cut shot prompts, storyboard keyframes, image-to-video renders, cuts on the beat. Use when the user says "music video", "video for this track", or wants visuals timed to a song. Has an approval gate before GPU spend.

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 privacy-aware observability for AI agents using traces, spans, structured events, metrics, cost attribution, dashboards, alerts, and investigation workflows. Use when instrumenting an agent, debugging intermittent tool or model failures, defining service-level objectives, analyzing latency or spend, auditing agent decisions, or preparing production monitoring.

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。

Weekly clinical-trial status diff — the 11-category change report over the stored weekly snapshots (spec 055 FR-B03). Surfaces exactly what changed on the trial registry for your coverage: New / Suspended / Withdrawn / Terminated / Recruiting / Recruitment-Complete / Completed / Ahead / Delayed / Upsized / Downsized, every row carrying previous and new values, with risk flags on Terminated and Downsized and re-timing flags on Ahead and Delayed. The stored-previous-value discipline makes each week's diff reproducible.

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。

Select, integrate, and operate multi-model video-generation gateways — hosted inference aggregators such as fal.ai, Replicate, and WaveSpeed that expose many third-party video (and video-adjacent audio) models behind one account, one API surface, and one bill. Use when deciding whether to route video generation through a gateway versus a direct model-provider API; when comparing gateways on catalog, async/queue job design, webhooks, pricing, schema discovery, and version pinning; and when operating gateway workloads in production — spend controls, retries, cross-gateway failover, content- safety differences, data retention, and commercial-rights passthrough of the underlying model. Not for direct model-provider APIs, local/self-hosted inference, model training/fine-tuning, or image-only gateway use.

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。

Select, integrate, and operate multi-model image-generation gateways with model-specific schema discovery, version policy, asynchronous jobs, webhooks, spend approval, safe inputs and artifacts, data-governance review, and billing observability. Use for comparing or building against fal.ai, Replicate, or Together AI image APIs, including controlled failover; do not use for direct model-provider APIs, local inference, training, dedicated endpoint provisioning, video generation, or general image editing.

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。

Designs adaptive clinical trials including group-sequential (O'Brien-Fleming, Pocock, Lan-DeMets spending), sample-size re-estimation (blinded Friede-Kieser, unblinded Cui-Hung-Wang, Mehta-Pocock promising zone), seamless Phase 2/3 with treatment-arm selection, population enrichment, and response-adaptive randomisation. Covers FDA 2019 Final Adaptive Designs Guidance, FDA 2022 Master Protocols, and ICH E20 Step 2b/3 draft (June 2025, NOT final). Use when planning interim analyses, sample-size re-estimation, or master/platform-trial designs.

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 asks for an HTML-first visual design deliverable or design judgment: interactive prototype, slide deck, motion demo, infographic, dashboard, landing page, whitepaper, changelog, business card, social cover, brand system, design critique, multi-variant exploration, or export to MP4, GIF, PPTX, PDF, or SVG. It is optimized to make AI agents do the routing, template selection, verification, and export prep so humans spend less time prompt-engineering. Do not use for production web apps, SEO sites, backend systems, or pure copy edits.

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。

Redpanda's Agentic Data Plane: governance infrastructure for building, running, and governing AI agents and MCP servers, plus a proxying AI Gateway for LLM providers, operated via `rpk ai` and the ADP API. Use when creating or managing AI agents (managed or self-managed) via `rpk ai agent` or `AgentRegistryService`; configuring MCP servers (remote or managed catalog, code mode, auth); setting up LLM providers or querying models via `rpk ai llm`/`rpk ai model` or the AI Gateway proxy; or configuring budgets, guardrails, or Cedar access-control policies through the governance APIs. Also covers reading agent transcripts and spending insights, and wiring OAuth clients or providers to the aigw Authorization Server. For the separate rpk cloud mcp control-plane MCP server, see `/redpanda:rpk-cloud`.

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。

Organize, categorize, and summarize business expenses for reimbursement and tax preparation. Use when a user asks to create an expense report, organize receipts, categorize expenses, summarize spending, prepare expenses for reimbursement, or compile business expenses for tax filing. Handles receipts, CSV data, and manual entries.

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。

Finds orphaned, idle, and underutilized cloud resources across AWS, GCP, or Azure accounts. Use when someone needs to audit cloud spending, find unused EBS volumes, stale snapshots, unattached IPs, idle load balancers, or oversized RDS instances. Trigger words: cloud waste, orphaned resources, unused volumes, cloud audit, infrastructure cleanup, cloud bill analysis.

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 and trace AI agents in Python with AgentScope, an open-source agent framework with a ReAct loop, tools, middleware, team pipelines and OpenTelemetry tracing. Use when building production agents that need observability, debugging an agent's model and tool calls, capping token spend per reply, or coordinating a leader with specialist 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。

The systematic discipline of reviewing AI-generated and human-written marketing content for quality, accuracy, consistency, and effectiveness. This isn't proofreading—it's strategic quality control that catches issues before they damage brand, waste spend, or miss opportunities. In an era where AI can generate content at scale, QA becomes the bottleneck— and the moat. Speed without quality is just fast failure. Every piece of content is a brand promise, and QA ensures that promise is kept. Content QA operates at multiple levels: tactical (spelling, grammar), strategic (message alignment), technical (platform compliance), and brand (voice, tone). The best QA catches what the creator couldn't see because they were too close. Use when "review content, QA, quality check, proofread, check copy, content review, brand compliance, verify content, fact check, review before publish, content approval, final review, qa, content-review, quality-assurance, brand-compliance, proofreading, content-quality, review" mentioned.

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。

UTM parameter strategy, campaign tracking, and marketing attribution modeling. Build consistent UTM taxonomies, configure attribution models, measure cross-channel performance, and connect marketing spend to revenue. Use when the user asks about UTM parameters, campaign tracking, attribution models, marketing measurement, or cross-channel analytics.

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 a local agent needs to dispatch work to CommonGround, inspect turn or agent state, wait for a turn to close, or resume a suspended turn through the `cg` CLI instead of calling the CG HTTP API 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。

Use when deterministic runtime code needs to execute CommonGround worker lifecycle steps through the local `cg worker` command namespace, including claim acquisition, renewal, progress append, terminal finish, child dispatch, and suspend flows.

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。

End-to-end test of the heygen CLI against the live API. Builds the binary, then exercises auth, list, get, --human, schema, error handling, and the full create-poll-download-delete write path. Spends a small number of API credits per run. Use before cutting a stable release.

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。

Join and operate on tiny.place (the agent-to-agent social network): create a self-custodied wallet, fund it via MoonPay, buy/renew/transfer a @handle 'domain', publish a discovery card, discover and resolve other agents, manage your profile and social graph (follow/feed/reputation), send Signal end-to-end encrypted messages, earn and spend through the jobs/escrow economy and marketplace, audit the settlement ledger, and poll the platform for updates — all through the `tinyplace-agent` 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。

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,' 'LinkedIn ads,' 'ad budget,' 'cost per click,' 'ad spend,' or 'should I run ads.' Use this for campaign strategy, audience targeting, bidding, and optimization. For bulk ad creative generation and iteration, see ad-creative. For landing page optimization, see cro.

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。

Decide when AutoCode acts on its own and when it must stop and ask the user. Runs before any consequential action — deleting files, spending money, buying a server, deploying to production, force-pushing, binding a domain, sending or publishing anything. Ordinary reversible work proceeds silently; only costly or hard-to-undo actions pause for the user. Powered by I-Lang v5.0 vector judgment.

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 paid motion-graphics videos in Kunpeng with MiniMax H3, Omni, or Seedance Mini. Use for MG animation, app showcase MG, talking-head graphic overlays, text-to-video MG explainers, and editor/canvas workflows that may spend credits.

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。

Audits SaaS, cloud, payment, and AI spend. Use when analyzing bills, right-sizing plans, sizing Savings Plans or CUDs, cutting payment-processing fees, or LLM self-host breakeven.

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。

PID/MPC/Kalman/anti-windup control primitives for feedback loops. Use when an autoscaler flaps, a controller overshoots after saturation, or budget pacing overspends at peak.

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。