「minimax」の検索結果

Design a Seedance 2.0 two-player co-op game menu or opening animation with stable character bindings, approved visual direction, readable UI copy, coordinated palette, explicit interaction events, and a clean final menu state. Use for game concepts and character-led social intros; not for playable game development or copying commercial game branding.

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 Seedance 2.0 brand, product, website, app, shop, or personal-project promo from verified assets and claims. Use when the user needs a truthful 4–15 second reel with a clear hook, product proof, controlled typography, camera, sound, CTA, and provenance-aware asset roles; not for inventing claims or imitating unavailable brand marks.

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 real product images and a verified brief into a clean Seedance 2.0 minimalist product film. Use for 4–15 second e-commerce or launch ads that require faithful product color/material/geometry, independent anchor-image roles, product-specific actions, restrained camera, readable integrated copy, sound, and a stable closing frame; not for talking-head ads or invented product features.

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 a Seedance 2.0 prompt for a rough hand-drawn luminous entity that physically contacts a live-action space, continuously transforms while remaining traceable, escapes through adjacent geography, and is followed by a slightly delayed handheld camera. Use for playful 4–15 second mixed-media clips; not for horror, polished CG, unrelated cuts, or simple visual filters.

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 when reasoning about generative AI, adversarial machine learning, neural network security, algorithmic fairness, or deep learning fundamentals. This skill channels the thinking of Ian Goodfellow, inventor of Generative Adversarial Networks (GANs). Trigger this skill when the user asks about model robustness, mitigating bias, evaluating AI guardrails, designing generative models, or defending against adversarial attacks. Apply his frameworks of minimax games, adversarial feature learning, and worst-case robustness analysis to shift the user's perspective from average-case optimization to adversarial resilience.

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 video clips on the user's own GPU through Guaardvark: text-to-video, image-to-video, first+last frame animation, clips with their own soundtrack and dialogue (MiniMax H3), short looping animations, and batch runs. Use when the user asks to make, render, animate, or batch-generate video 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。

Fan out a one-shot or flat parallel batch of cc-fleet PROVIDER subagents (headless `cc-fleet subagent`) that return a result — DeepSeek / GLM / Kimi / Qwen / MiniMax, or a Codex/Claude subscription. Trigger ONLY to delegate a task to a cc-fleet provider worker (parallel research, bulk per-file work, a specialized model). Do NOT trigger for a multi-phase pipeline (that is /cc-fleet:workflow), for ordinary local shell/coding, or for editing or researching cc-fleet's own code.

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 one-shot or flat parallel batch of provider LLM subagents (headless `cc-fleet subagent`) that return a result. Use when fanning out N independent tasks, doing bulk per-file work, or calling a specialized provider model (DeepSeek / GLM / Kimi / Qwen / MiniMax). NOT a long-lived collaborator you message back and forth (that is /cc-fleet:team); NOT a multi-phase pipeline with dependencies or resume (that is /cc-fleet:workflow); NOT trivial work the main session should just do.

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。

Think and work like an expert Mathematical Statistician. Use when a task calls for Mathematical Statistician judgment. Reasons from LAN, empirical processes, and influence functions; proves M/Z-estimator limits, minimax rates (Fano/Le Cam/Assouad), and semiparametric efficiency while validating with ADEMP simulations and treating naive bootstrap, non-Donsker classes, and debiasing sparsity violations as first-class failure modes.

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。

Produce video (and its supporting stills) through Higgsfield (higgsfield.ai), a multi-model creative platform that fronts third-party video models (Kling, Veo, Seedance, Wan, MiniMax, and, until retirement, Sora) plus Higgsfield's own control layer — Soul / Soul ID image generation, the DoP camera-preset engine, and the Cinema Studio filmmaking suite. Use this skill when a request routes generation through Higgsfield specifically, when the user wants aggregator-level model switching and cinematic camera/effect presets in one workspace, when planning character consistency via Soul ID, or when deciding whether to go through Higgsfield versus direct to an underlying model provider. Covers model selection, per-model prompt strategy, credit economics, the (partial) API surface, capability limits, and rights/consent policy for generated and uploaded real-person footage.

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miora 视频生成的可靠性与规格层——补内置技能未覆盖的部分：四必填参数闸门（模式/分辨率/时长/画幅缺一不可提交）、时长区间闸门、完成信号的判定与轮询等待、官方规格口径与本通道实测差异（时长/分辨率/参考图上限）、文生/首尾帧/参考生三种模式的参数事实、提示词的自动修正边界、生成状态向用户的同步。当用户要生成视频、动效、短视频，或提到参考生视频/首尾帧/图生视频、miora 视频、minimax h3、视频生成进度、视频怎么还没出来时使用。

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。

Generate a single image from a text prompt using the MiniMax image generation API. Use when the user asks to create, generate, or render an image from a prompt and explicit width/height.

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。

AIGC 创作工作流 (AIGC 创作工作流 / AIGC Creative Workflow — 以「生成式 AI 视觉创作（图像 + 视频）的工程化创作流水线」为对象的认知操作系统：从「需求/概念（要做什么画面/镜头/风格）→ 模型与工具选型（Midjourney / Stable Diffusion·SDXL·Flux / ComfyUI / 可灵 Kling / 即梦 Jimeng / Runway / Vidu / Sora）→ Prompt 与参数设计（提示词工程、风格描述、负向、种子、CFG/步数/采样器、参考图）→ 可控生成（ControlNet / LoRA / IPAdapter / inpainting / 图生图 / 局部重绘 / 区域控制）→ 批量出图与筛选 → 精修与合成（放大/超分、修手修脸、PS/AE 后期、抠图合成）→ 图生视频/文生视频（首尾帧、运镜、时长、一致性、对口型）→ 商业交付与迭代复现（参数留存、工作流文件复用、版权与可商用判断）」的完整创作-工程-交付决策链。覆盖 (a) 第一性张力 — **可控性/工程化复现（ControlNet/LoRA/ComfyUI 节点工作流/固定种子与参数/可复现可迭代）⇄ 随机性/抽卡玄学（出图随机、prompt 玄学、抽卡刷图、靠运气）**；**审美/创意/艺术指导主导（人的审美判断、概念设计、构图、镜头语言、艺术总监能力——'模型是地板，审美是天花板'）⇄ 工具/模型/参数主导（堆模型能力、堆参数、堆 LoRA、以为换个大模型就行）**；**开源生态/本地可控（Stable Diffusion / ComfyUI / Flux / civitai / liblib 本地部署可定制可控可商用、显卡门槛）⇄ 闭源商业/易用黑盒（Midjourney / 可灵 / 即梦 / Runway 开箱即用但不可精控、按量付费、黑盒）**；**图像生成（T2I/I2I：Midjourney / SDXL / Flux）⇄ 视频生成（T2V/I2V：可灵 / Runway Gen-3 / Vidu / 即梦 / Sora，2024-2025 前沿从图迁移到视频）**；**生产力/商业量产（替代或增强传统设计/插画/电商/广告/影视分镜流程、降本提效、批量）⇄ 纯艺术创作/作者表达（个人风格、实验性、作品集）**；**效率/批量（一次出几十张筛选、商单走量、自动化 pipeline）⇄ 质量/精控（单张精修、商业可用级细节、修手修脸修穿帮）**。(b) 核心工作流 / pipeline（最标准、最易蒸高质量 + CLI 化）— 单图创作链：概念/参考收集（moodboard/风格定位/竞品）→ 模型工具选型（按可控性/风格/成本/可商用判断 MJ vs SD/Flux vs 国产）→ Prompt 与参数设计（主体/风格/光影/镜头/负向词/CFG/采样器/分辨率/种子）→ 首轮出图与方向筛选 → 可控迭代（ControlNet 控构图/姿态/线稿、LoRA 控风格/角色一致性、图生图重绘、inpainting 局部修）→ 放大超分与精修（高清放大/修手修脸/后期调色合成）→ 交付与参数留存（工作流文件/种子/参数复现）。视频创作链：分镜/脚本→首帧出图（图像链产出关键帧）→图生视频（运镜/时长/首尾帧/动态强度）→多镜头一致性（角色/场景/风格统一）→对口型/配音/配乐→剪辑合成→交付。ComfyUI 工程链：节点工作流搭建（加载器/采样/ControlNet/放大/面部修复节点）→ 参数化与复用→批量队列→工作流分享（civitai/openart workflow json）。(c) 工具栈 — 闭源图像（Midjourney v6/v7、DALL·E 3、Adobe Firefly、Ideogram、Recraft）、开源图像与底座（Stable Diffusion 1.5/SDXL/SD3、Flux.1 dev/schnell（Black Forest Labs）、ComfyUI（节点式）、Automatic1111/Forge WebUI、Fooocus）、可控生成插件（ControlNet、LoRA、IPAdapter、AnimateDiff、inpainting/outpainting、ReActor 换脸、面部修复 CodeFormer/GFPGAN、放大 ESRGAN/SUPIR/Topaz）、模型/资源社区（Hugging Face、Civitai、liblib 哩布、吐司 Tusi、openart）、视频生成（可灵 Kling、即梦 Dreamina/Jimeng、Runway Gen-3/Gen-4、Luma Dream Machine、Pika、Vidu、海螺 Hailuo、Sora、Wan 通义万相、MiniMax）、辅助（Magnific 放大、Krea、Photoshop/After Effects 后期、ChatGPT/Claude 写 prompt、reverse prompt 反推）。(d) 知识正典 — AIGC 创作 canon 横跨论文/工程/社区教程：奠基论文（DDPM、Latent Diffusion/Stable Diffusion（Rombach et al）、DiT、ControlNet（Zhang et al）、LoRA、DreamBooth、Textual Inversion、SDEdit、IP-Adapter、视频扩散 SVD/Sora 技术报告）、官方文档与模型卡（Stability AI、Black Forest Labs Flux、ComfyUI 文档、Midjourney docs、可灵/即梦官方教程、Hugging Face diffusers）、社区教程与工作流（ComfyUI 官方示例、civitai 文章、B站/YouTube 创作者长教程、openart workflow）、prompt 工程资源（Midjourney 风格库、提示词指南）。(e) figures/流派 — 模型/工具创造者（Midjourney David Holz、Stability AI Emad/Robin Rombach、Black Forest Labs（Flux，原 SD 团队）、ComfyUI comfyanonymous、ControlNet 张吕敏 Lvmin Zhang、AUTOMATIC1111、可灵/即梦/快手字节团队）、创作者 KOL 与教育者（Midjourney/SD 头部创作者、ComfyUI 工作流大神、AI 视频创作者、国内 B站/抖音 AIGC 教程作者、独立 AI 艺术家）、行业分析与评测（AI 工具评测、生成式 AI 创作生态观察者）。流派分歧：开源可控派（SD/ComfyUI/Flux 本地精控）vs 闭源易用派（MJ/可灵开箱即用）、工程化派（节点工作流/可复现/参数化）vs 玄学抽卡派（prompt 玄学/堆词/抽卡）、审美主导派（'模型是地板审美是天花板'）vs 工具主导派（堆模型堆参数）、图像派 vs 视频派、艺术创作派 vs 商业生产力派、国产工具派（可灵/即梦/liblib）vs 海外工具派（MJ/Flux/Runway）。(f) 行业话术/黑话 — 出图 / 抽卡 / 刷图 / 炼丹（训练 LoRA）/ 喂图 / 垫图（参考图/图生图）/ 控图 / 锁种子 seed / CFG / 采样器 sampler / 步数 steps / 重绘幅度 denoise / 提示词 prompt / 咒语 / 负向 negative / 权重 / tag / 大模型 checkpoint / 底模 / LoRA / ControlNet / 控线稿/openpose/depth / IPAdapter / inpainting 局部重绘 / outpainting 扩图 / 高清放大 / 超分 / 修手 / 崩手 / AI 味 / 风格 / 角色一致性 / 工作流 workflow / 节点 / 跑图 / 队列 / 文生图 T2I / 图生图 I2I / 文生视频 T2V / 图生视频 I2V / 首帧/尾帧 / 运镜 / 动态强度 / 时长 / 对口型 / 一致性 / 可商用 / 训练集 / 过拟合 / 翻车 / 穿帮。(g) 争议/批判 — 「版权与训练数据」（模型训练用未授权作品、生成图版权归属、可商用风险、洗图/伪原创）、「AI 替代创作者就业」（替代画师/插画师/设计师/摄影、行业冲击与转型）、「AI 味与审美趋同」（生成图同质化、套模板、缺乏原创审美）、「玄学 prompt 神话与割韭菜」（'咒语'神秘化、'7天 AIGC 变现/月入过万'付费课割韭菜、抽卡当能力）、「工具快速迭代与淘汰焦虑」（模型月月换、工作流频繁失效、追新疲劳）、「开源 vs 闭源之争」（可控可商用 vs 易用黑盒）、「质量天花板」（修手修脸穿帮、长视频一致性、可控性仍有限）。(h) 大量隐性创作手艺 + 审美 + 工程 + 沟通软技能（prompt 的描述功底与审美词汇、参数与采样的手感、ControlNet/LoRA 的组合控制经验、节点工作流的搭建与调试、批量筛选的审美眼力、修图合成的后期功底、镜头语言与运镜设计、角色/风格一致性的控制、商业需求的翻译与交付、版权与可商用的判断）是高 tacit、靠大量实操跑图 + 审美积累 + 工程调试经验的核心。水分极高（大量'咒语速成/一键变现/AI 绘画割韭菜'营销

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 when reasoning about generative AI, adversarial machine learning, neural network security, algorithmic fairness, or deep learning fundamentals. This skill channels the thinking of Ian Goodfellow, inventor of Generative Adversarial Networks (GANs). Trigger this skill when the user asks about model robustness, mitigating bias, evaluating AI guardrails, designing generative models, or defending against adversarial attacks. Apply his frameworks of minimax games, adversarial feature learning, and worst-case robustness analysis to shift the user's perspective from average-case optimization to adversarial resilience.

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。

Open, create, read, analyze, edit, or validate Excel/spreadsheet files (.xlsx, .xlsm, .csv, .tsv). Use when the user asks to create, build, modify, analyze, read, validate, or format any Excel spreadsheet, financial model, pivot table, or tabular data file. Covers: creating new xlsx from scratch, reading and analyzing existing files, editing existing xlsx with zero format loss, formula recalculation and validation, and applying professional financial formatting standards. Triggers on 'spreadsheet', 'Excel', '.xlsx', '.csv', 'pivot table', 'financial model', 'formula', or any request to produce tabular data in Excel format.

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 when visual quality and design identity matter for a PDF. CREATE (generate from scratch): "make a PDF", "generate a report", "write a proposal", "create a resume", "beautiful PDF", "professional document", "cover page", "polished PDF", "client-ready document". FILL (complete form fields): "fill in the form", "fill out this PDF", "complete the form fields", "write values into PDF", "what fields does this PDF have". REFORMAT (apply design to an existing doc): "reformat this document", "apply our style", "convert this Markdown/text to PDF", "make this doc look good", "re-style this PDF". This skill uses a token-based design system: color, typography, and spacing are derived from the document type and flow through every page. The output is print-ready. Prefer this skill when appearance matters, not just when any PDF output is needed.

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。

Professional DOCX document creation, editing, and formatting using OpenXML SDK (.NET). Three pipelines: (A) create new documents from scratch, (B) fill/edit content in existing documents, (C) apply template formatting with XSD validation gate-check. MUST use this skill whenever the user wants to produce, modify, or format a Word document — including when they say "write a report", "draft a proposal", "make a contract", "fill in this form", "reformat to match this template", or any task whose final output is a .docx file. Even if the user doesn't mention "docx" explicitly, if the task implies a printable/formal document, use 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。

把自媒体口播文案变成配音音频。自动做章节/分段拆分，用 MiniMax TTS（含用户本人的复刻音色）逐句合成，按采样帧精确拼接，停顿节奏可控。默认只出音频，需要字幕时可加出 SRT。触发场景：(1) 用户给一段文案要求"生成配音"、"做成音频"、"配个音"、"转成语音"；(2) 口播稿/自媒体文案转成品音频；(3) 用户要"出个口播"、"用我的声音读一遍"；(4) 需要复刻声音做 TTS；(5) 用户要文案的 SRT 字幕；(6) 使用 /voice-clone-tts 命令。

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 to create, generate, or produce video content using AI tools or programmatic frameworks. Also use when the user mentions 'video production,' 'AI video,' 'Remotion,' 'Hyperframes,' 'HeyGen,' 'Synthesia,' 'Veo,' 'Sora,' 'Runway,' 'Kling,' 'Seedance,' 'Hailuo,' 'MiniMax,' 'Pika,' 'Hunyuan,' 'Wan,' 'video generation,' 'AI avatar,' 'talking head video,' 'programmatic video,' 'video template,' 'explainer video,' 'product demo video,' 'video pipeline,' or 'make me a video.' Use this for video creation, generation, and production workflows. For video content strategy and what to post, see social. For paid video ad creative, see ad-creative.

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 generating video clips with Chinese video models — text-to-video (文生视频), image-to-video (图生视频), first/last-frame and reference-to-video across 4 platforms: Bailian (Wan/PixVerse/Kling/Vidu/HappyHorse), Jimeng (doubao-seedance), MiniMax (Hailuo), Hunyuan (hy-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。

Multi-platform Chinese & multilingual TTS text-to-speech via Edge/Doubao/CosyVoice/Qwen3/StepFun/GLM-TTS/Azure/Tencent/Baidu/MiniMax/Xunfei plus ElevenLabs/OpenAI/Google/Atlas Cloud — 15 backends, word-level timestamps, [PAUSE:x] pause markers, pinyin pronunciation overrides

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。

将文案与用户自己的参考录音合成为配音、SRT 和可交接时间轴。默认使用 MiniMax 与用户自己的音色；可显式选择免费本地 Qwen3-TTS（Apple Silicon 用 MLX）或 Nano CPU。适用于口播配音、声音复刻，以及为网页视频演示准备最终音频和字幕。

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 pipeline for producing Vox-style explainer videos from a single topic prompt. One topic in, finished film out — script, keyframes (Seedream 5.0 Pro), animation (Gemini Omni Flash), voiceover (xAI TTS), music (MiniMax Music 2.6), all assembled locally with ffmpeg via the Atlas Cloud API. Use this skill whenever the user asks for an explainer video, a Vox-style video, a documentary short, an educational video essay, a "one prompt to video" pipeline, or wants to turn a topic/article/report into a narrated video with subtitles and music. Also trigger when the user mentions Atlas Cloud video pipelines, keyframe-to-animation workflows, or automated video essays — even if they don't say "Vox."

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。