「gpt」の検索結果

用前端渲染生成图片 —— 不依赖模型的多模态能力，任何能写 HTML/CSS 的模型 (DeepSeek / Claude / Kimi / GPT 等) 都能用。 当用户要「生成/做/画一张图」且属于以下任意一种时使用：头像、图标、公众号封面、 OG 分享图、Banner/横幅、小红书封面、知识卡片、金句卡、代码片段图、数据卡、 功能发布图、对比图、步骤图、视频封面/缩略图、幻灯片单页、活动海报、名片、 二维码卡、配图、题图、缩略图、poster、cover、thumbnail、banner、avatar。 也用于：批量出多个尺寸/多平台的同一张图；把一段文字/数据/代码变成图； 给文章配图；做一套风格统一的系列图。 支持指定视觉风格，共 32 套：手绘/涂鸦/白板、黑板、水彩、拼贴/剪贴、博物图鉴、 瑞士国际主义、杂志编辑部、报纸、工程蓝图、档案手稿/打字机、包豪斯、装饰艺术 Art Deco、 双色印刷 Riso、粗野主义、孟菲斯、美漫波普、像素 8-bit、千禧 Y2K、蒸汽波、霓虹赛博朋克、 街头海报/喷漆、日式侘寂、中式水墨、国潮/新中式、终端 CLI、极光渐变、玻璃拟态、 奢侈品黑金、极简产品、电影海报、复古未来 70s、极简线条。 用户没指定时主动报 3~4 个候选让他选；说了库里没有的风格就按四步法拆成 token。 产出一个可预览的画板工作台页面，多种画幅并排展示，点按钮即可导出 PNG (页内零依赖导出 + 本机 Chrome 精确出图两条通道)。 不适用：需要照片级真实内容的图（人像、风景、材质渲染）—— 那需要真正的图像模型。

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Import a memory export from another AI assistant (ChatGPT, Gemini, Claude, etc.) into this agent's memory — conversationally, additively, and with the pasted content treated as data. Use when the user wants to bring over what another assistant knows about them.

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Delegate implementation (or, when explicitly requested, research) to GPT-6.1 Sol (high reasoning; xhigh on request) via Codex CLI. Claude plans, orchestrates, and reviews; Sol writes the code.

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A 15-minute guided setup that teaches Cowork who you are, how you work, and what tools you use — so every result feels tailored instead of generic. Use when setting up Cowork for the first time, for personalizing your workspace preferences, during onboarding after your first session, when configuring your tools and context, or when the user says "set up cowork", "configure cowork", "why is cowork giving me generic results", "cowork setup", "personalize cowork", "make cowork know me", "cowork feels like chatgpt", or "how do I get better results from cowork".

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Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains.

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。

Generative Engine Optimization for AI search engines (ChatGPT, Claude, Perplexity).

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Comprehensive framework for effective gptme agent onboarding that builds user trust, communicates capabilities clearly, and establishes productive working relationships from the first interaction.

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Use Codex (CLI + AppServer) as the full agent provider — planning, tool orchestration, native compaction, MCP tools, session resume — in place of the Claude Agent SDK. ChatGPT subscription or OPENAI_API_KEY. Per-group via agent_provider. Distinct from using OpenAI as an MCP tool (where Claude remains the planner).

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AI and LLM red-teaming skill for evaluating prompt injection, jailbreak, data exfiltration, tool abuse, agent hijack, RAG poisoning, model denial of service, and unsafe tool-use chains in Gemini, Claude, GPT, and open-weight models. Use to build evaluation harnesses, attack corpora, defensive guardrails, and red-team reports for AI systems you own or are authorized to test.

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Review computational protein or gene function predictions and fill PredictionReview YAML files using the COR/CNN/LSP/UNC/PLI/NPI/REP biological-validity taxonomy. Use for ProtNLM, DeepECTF, BioReason/GO-GPT, InterPro2GO, PANTHER/IBA, CLEAN, GloEC, MAPred, ProteinInfer, or other predicted EC/GO annotations, including audits of the evidence and reasoning in existing prediction reviews.

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Work with BioReason-Pro predictions and reasoning traces for protein function. Use when: comparing BioReason outputs against curated reviews, converting web exports to YAML, reviewing reasoning trace quality, or running the SFT/RL comparison. Triggers: "bioreason", "GO-GPT predictions", "reasoning trace review", "bioreason comparison", "SFT vs RL".

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End-to-end AI website generation pipeline. Claude Opus 4.8 emits Bolt-style <boltArtifact> envelopes (multi-file, plan-first) that customize Vite+React+Tailwind templates from pre-researched business data. Pre-research via APIs, media acquisition, brand extraction, visual inspection via GPT Image 2 vision, R2 upload (per-file content-type by extension), D1 status updates. Supports all business types: SaaS, portfolio, non-profit, restaurant, salon, medical, legal, retail, tech.

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Section-by-section media planning and generation. Image generation (GPT Image 2 primary, built-in fallback), logo/icon generation (Ideogram v3 → favicon set), video generation (Veo 3.1), social preview images (OG 1200x630 + AI search optimization), stock photo curation (Pexels, Pixabay), critique/remix loops (max 3 rounds), asset compression pipeline, and media performance budgets.

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Detect and rewrite AI writing patterns to make content sound authentically human. Supports voice calibration from the author's own writing samples. Use when asked to humanize text, remove AI patterns, calibrate voice, audit content for AI detectability, or check if writing sounds like ChatGPT. Triggers: /humanize, /voice-calibrate, /audit-ai

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Gaia Skill Tree image-generation and deterministic export harness for Ascension Overdrive v3. Use when generating, iterating, refining, cropping, color-grading, making transparent cutouts, compressing, upscaling, or validating production image assets. Always use image gen 2 / gpt-image-2 and never nano-banana.

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Design or revise Interpreter UI for non-developers with an ultra-minimal, utilitarian style inspired by the OpenAI website and ChatGPT, not the developer platform. Use when simplifying settings, onboarding, chat, forms, empty states, or helper copy; when removing extra containers, labels, or visual noise; when replacing technical wording with plain language; when clarifying hierarchy and making the main user action obvious; when making every visible label and status understandable to an average HR admin or other non-technical user; when hiding implementation details such as logs, IDs, endpoints, paths, or protocol names; or when a screen must respect the app's existing CSS variables and light/dark theme behavior.

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Generate AI video ads and image ads through the Novoads REST API (api.novoads.ai). Use when the user wants a UGC video, a product video, a talking-head ad, an AI actor holding a product, a TikTok or Reels or Shorts ad, a static image ad, or asks to "make me an ad", "generate a video", or names a model (Seedance, Seedance 2.5, Seedance Mini, Omni Flash, Veo 3.1, Sora 2, GPT Image 2, Nano Banana Pro, Reve). Handles upload, dialogue approval, cost confirmation, generation, polling, QA, and download. A product photo lands here when it SEEDS a new scene; when the picture itself should move, unchanged, that is image-to-motion. Not for editing an existing video file and not for publishing to an ad platform.

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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.

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Elite UX/UI & Advanced GSAP Motion Engineer. Enforces Python-driven true randomization for layout variance, strict AIDA page structure, wide editorial typography (bans 6-line wraps), gapless bento grids, strict GSAP ScrollTriggers (pinning, stacking, scrubbing), inline micro-images, and massive section spacing.

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

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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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Audit robots.txt for AI crawler access policies. Checks GPTBot, ClaudeBot, PerplexityBot, Google-Extended, and other AI crawlers. Use when user says "robots AI", "AI crawlers", "block AI", "allow AI bots", "AI crawl policy".

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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。