「chat」の検索結果

Adopt Prisma Next into a new project, onto an existing database, or as the first move after a bootstrap tool dropped you into a scaffold. Use for "what can I do with Prisma Next", "what can I do next with Prisma", "where do I start", "what should I do first", "just ran createprisma", "createprisma", "npx createprisma", "npx create-prisma", "first steps", "first query", "I have a scaffolded Prisma Next project what now"; for `pnpm dlx prisma-next init` greenfield setup; and for `prisma-next contract infer` + `db sign` against an existing database. Also covers the connect-write-read first-arc orientation, the day-to-day commands (`contract emit`, `db init`, `db update`, `migration plan`, `migrate`, `db schema`, `db verify`), and routing to `prisma-next-contract` / `prisma-next-queries` / `prisma-next-runtime` for the next move. Flags: --target, --authoring, --schema-path, --probe-db, --output.

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Wire the Prisma Next runtime — `db.ts` setup using `postgres<Contract>(...)` from `@prisma-next/postgres/runtime`, `sqlite<Contract>(...)` from `@prisma-next/sqlite/runtime`, or `mongo<Contract>(...)` from `@prisma-next/mongo/runtime`; middleware composition (telemetry from `@prisma-next/middleware-telemetry`; lints and budgets), `DATABASE_URL` config, per-environment branching, switching between Postgres, SQLite, and Mongo façades. Use for db.ts, postgres(), sqlite(), mongo(), middleware, telemetry, lints, budgets, DATABASE_URL, .env, connection pool, poolOptions, dev vs prod config, transactions, db.transaction, read replicas, multi-database, script won't exit, hangs, close connection, db.end, db.close, pool.end, [Symbol.asyncDispose], await using.

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Clones a STATIC IMAGE ad into finished ads for your own product, into a reusable prompt TEMPLATE, or both — the template is what makes the ads and the ads are what prove the template. Round-trips the frame through gpt-image-2, nano-banana-pro or reve-2.1 until it reproduces, replaces every brand-specific with a {placeholder}, then fills it with your product pinned to a real photo. Use for "clone this ad for my product", "rebuild this competitor's ad for us", "make me ads like this", "reverse engineer this ad", "make this ad reusable", "add this to my prompt library", or "clone my competitors' ads" with NO file attached — it sources one via spy-competitor-ads rather than asking which. **Among cloners the source's medium decides**: a still, or nothing attached, lands here; "clone this ad" plus a VIDEO is clone-video-ad. NOT for generating an ad from a brief (chatgpt-image-ad, nano-banana-image-ad), nor animating a still as-is (image-to-motion). Refuses to render your product without a real photo of it.

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 resumption of any multi-day LLM batch-scoring campaign that calls an unpinned model alias (deepseek-chat, gpt-*-latest, gemini-*-preview, any provider alias without a pinned version). Use when: (1) resuming a paused or credit-exhausted scoring run days after its last chunk, (2) topping up credits to finish a campaign, (3) extending a cached scoring pipeline with new items. Prevents silently splicing two model versions or serving revisions into one measure. Verified 2026-07-16: for $0.30 caught a serving-revision drift WITHIN DeepSeek v4-flash (same alias, same family, litigation scores systematically shifted across a 2-day gap) before an $83 resume 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。

OpenUI generative UI with OpenAI SDK backend. Streaming chat completions with gpt-5.5 (or any current OpenAI-compatible 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。

Build UIs with @nuxt/ui v4 — 125+ accessible Vue components with Tailwind CSS theming. Use when creating interfaces, customizing themes to match a brand, building forms, or composing layouts like dashboards, docs sites, and chat interfaces.

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。

Marketing analytics and data-driven optimization for B2B SaaS campaigns. Use this skill when analyzing marketing performance, optimizing conversion rates, running A/B tests, conducting customer research, creating marketing dashboards, building attribution models, analyzing funnel metrics, or storytelling with data. Also triggers on: marketing ops, performance analytics, CRO, A/B testing, data storytelling, customer insights, tracking plan, event taxonomy, UTM taxonomy, GA4 audit, consent mode, instrumentation contract, sample size calculation, minimum detectable effect, test duration, not enough traffic to A/B test, statistical significance, Bayesian vs frequentist, sample ratio mismatch, experiment feasibility, martech stack, marketing tech stack audit, tool consolidation, build vs buy, vendor evaluation, shadow IT tools, ESP/CRM/platform migration, switching cost, cutover plan, suppression list migration, data portability, customer interviews, survey design, sampling frame, non-response bias, how many people should I interview, thematic saturation, voice of customer, jobs-to-be-done, buyer persona research, is this finding real, data enrichment, which enrichment provider should we buy, waterfall enrichment, contact data quality, match rate, our list data is bad, email verification, catch-all domain, accept-all, bounce rate from bad data, B2B data decay, how often should we re-verify contacts, ZoomInfo vs Apollo vs Clearbit evaluation, cost per usable record, where did this list come from, GDPR Article 14 notice, purchased list compliance, suppression screening, TAM list building, demand planning, marketing plan, how many leads do we need, what pipeline target should marketing carry, funnel model, top-down vs bottom-up plan, plan of record, annual marketing planning, quarterly planning, pipeline coverage we have to create, sales cycle lag, our leads cannot close this quarter, carry-in pipeline, scenario planning, conservative moderate aggressive forecast, stretch target, reforecast, re-forecast triggers, assumption register, capacity ceiling, addressable audience ceiling, marginal cost per lead, blended CPL is wrong, we missed plan and nobody knows why, AI policy for the marketing team, AI governance, AI acceptable use policy, which AI tools are we allowed to use, can I paste customer data into ChatGPT, shadow AI, AI use register, human review of AI output, when can we stop reviewing every AI draft, can the agent send on its own, the AI made a mistake now what, pull back AI autonomy, AI evals, our AI vendor changed the model, AI output went out wrong, prompt injection, can our AI read prospect replies safely, lethal trifecta, the AI leaked internal notes, turn off auto-generated ad assets, auto-applied recommendations, AI literacy training, EU AI Act Article 4, duplicate records in the CRM, dedupe before import, which value wins in a merge, CRM cleanup.

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。

Transform vague inputs into precision-optimized AI prompts for Claude, ChatGPT, Gemini, or other LLMs. Use when user mentions "optimize prompt", "improve prompt", "lyra", "prompt engineering", or needs help crafting effective AI prompts.

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Monitor brand visibility in AI search and traditional search. Use when user says "brand radar", "brand monitoring", "AI search visibility", "brand mentions", "share of voice", "who mentions my brand in AI", "brand in ChatGPT", "brand in Perplexity", "how visible is my brand", "brand awareness tracking", "AI brand presence", "is my brand cited in AI responses".

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。

为他山学科交叉公众号撰写微信文章，包括选择文章类型、套用排版模板、生成配图、转换HTML、添加底部模板。当用户说"写一篇公众号文章""帮我写他山文章""写公众号推文""帮我把这篇写完""补全这篇文章""继续写这篇"时使用。写完后自动触发 article-proofreading 审稿。

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。

根据当前科研数字分身状态，生成结构化提示词，供用户提交给 ChatGPT 等带记忆功能的 AI，从中提取与画像构建相关的信息。不询问用户使用哪个 AI 工具，提示词对所有平台通用。

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。

解析用户从 ChatGPT 等 AI 获取的记忆回复（支持多个 AI 依次粘贴），与现有画像对比后，有据可查的条目内部整合直接写入并标注置信度；模糊/冲突/当前需求条目以选择题形式逐条确认；❌记忆不足条目不丢弃，转入步骤五追问队列；写入后执行字段级完整度扫描，列出缺口清单并逐批追问，达到必填门槛后才进入量表阶段。

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。

撰写通用长文（技术分析/产品思考/对外分享/个人随笔），区别于微信公众号文章（公众号请用 wechat-article-writer）。读取写作习惯手册后起草，支持大纲确认、正文撰写、挑战者自检、审稿闭环。当用户说「写一篇技术文章」「写一篇对外分享」「写一篇产品分析/产品思考」「帮我写一篇通用文章/长文」「写一篇个人随笔」时使用。

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。

Language-specific guidelines for producing high-quality Traditional Chinese (zh-TW) content: script, full-width punctuation, spacing, forms of address, grammar constraints, and Taiwan terminology. Includes the no-calque rule against literal translations of English phrasal verbs such as 折入 for fold in. Use when writing any kind of Chinese content. Including blog posts, notes, technical articles, technical writing, chitchat, social media posts, etc., even when you are just sending a text message. Also use when reviewing or editing existing Chinese content for language and terminology compliance. Always apply `writing-style-guideline` alongside this skill for structure, tone, rhetorical constraints, and banned phrases.

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。

Language-agnostic writing style guidelines covering structure, tone, rhetorical constraints, banned phrases, and review checks. Use when writing any kind of content in any language. Including blog posts, notes, technical articles, technical writing, chitchat, social media posts, etc., even when you are just sending a text message. Also use when reviewing or editing existing content for tone and style compliance. For Traditional Chinese (zh-TW) content, apply `chinese-content-writing-guideline` alongside 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。

Build a morning briefing ritual with Muse: overnight priorities, today's calendar, weather-aware planning, and top 3 focus items as a concise chat summary.

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 conversational multi-agent systems with AutoGen — agent types, group chats, and orchestration patterns.

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 streaming AI user interfaces with AI SDK patterns — message rendering, tool-call displays, loading states, and optimistic updates. Use when creating chat UIs that stream model output and show agent activity.

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。

Proven prompts behind viral AI-made videos across 4 models — Claude, Muse AI, ChatGPT, Gemini. Browse by model, category, or tech tag, copy a creator's prompt, adapt it to your own model and renderer. Use when you need a motion-graphic, explainer visual, 3D scene, interactive animation, or AI video-gen prompt that already worked in the wild.

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 spoken audio from text, single or multi-speaker, including voice notes or messages for chat, audio for artifacts, and audio from cron jobs. For podcasts, briefings, or narrated summaries, use podcast.

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Review Zoom meetings, calls, recordings, and transcripts. Use to catch up on missed calls, summarize decisions, and extract action items and owners; also work with Team Chat, Canvas, Tasks, Whiteboard, Hub, and Revenue Accelerator through Zoom's official MCP servers.

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Generate a 2026-grade content brief for a target query — combines classic SERP analysis with AI Overview / Perplexity / ChatGPT citation analysis, entity recommendations (target ≥15 recognized entities), topical authority gap map, intent-mapped heading structure, internal linking targets.

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Autonomous SEO + AI-search optimization agent for 2026. Audits and fixes technical SEO, on-page metadata, structured data, Core Web Vitals (LCP/INP/CLS), llms.txt, Generative Engine Optimization (GEO) for ChatGPT/Perplexity/AI Overviews, E-E-A-T author signals.

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Multi-pass editor that removes AI-writing tells from drafted content — eliminates filler phrases, balances sentence length, restores opinion and voice, and strips em-dash overuse so posts sound human and opinionated rather than ChatGPT-generic..

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。