“search scene”的搜索结果

Search runtime and scene management: verify queries, inspect scenes, debug app readiness, and diagnose recall or scene-config issues.

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Turn a math or science video idea into a detailed scene plan. Research the topic, clarify the audience, and outline visuals, narration, transitions, and implementation notes for Manim, an animation tool.

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• Turn a rough explainer idea into a scene plan
• Plan intuitive math and science visuals
• Adapt video depth to the audience

Viking Search tuning for specified policy directions. Use this when the user provides specific queries, a type of query, or a business policy direction, and asks to boost, suppress, or fix a class of search results through request-parameter passthrough. You must only perform read-only baseline evaluation and request-level candidate testing; do not modify search scenes, app config, dictionaries, recommend scenes, or primary recall parameters.

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Trigger when: (1) the user mentions "manim", "scene", "video", "EN/KO render", "GEODE_HERO_LANG", "1080p60", or (2) editing files under `scripts/visualizations/` ending in `.py`, or (3) the user asks to render, re-render, or extend any of the four validated scenes (`geode_hero.py`, `autoresearch_filewalk.py`, `autoresearch_compare.py`, `critical_floor.py`). GEODE Manim Scene authoring standard. Locks the patterns the four validated scenes already share — Anthropic-style palette, Helvetica Neue + Pretendard font pairing with weight=NORMAL, EN/KO multilingual lang via `GEODE_HERO_LANG` env, `_dashed_arrow_with_head` stage-coupled tinting, `verify_hero_layout.py` ratchet — so the next scene does not re-discover the kerning / padding / transition regressions catalogued in [[viz-frame-audit]].

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Recommend runtime and V2 scene management: run recommendation requests, manage recommend scenes and rules, and verify the deployed recommendation path.

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Use when the user provides 1-50 concrete bad-case search queries for one Viking Search app and wants local deterministic fixes. This skill only verifies request-level fine-operation interventions against a read-only baseline scene and delivers a console-ready configuration sheet, validated payloads, and a replay script. It must not mutate scenes, apps, dictionaries, datasets, recall core parameters, or online defaults.

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Manages Volcano Engine ContextSearch control-plane and application-console operations. Use for ContextSearch scene, AgenticSearch, data source, indexer, search-config, model, deployment, network, specification, and API-key administration. Do not use for generic web search or runtime RAG, image, or video retrieval and chat.

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将视频和音频导入VideoDB，按语音或画面搜索场景并制作片段，还可添加字幕和音轨、调整画面比例、设置直播事件通知，以及记录和总结桌面操作。

• 按语音或画面查找并截取场景
• 添加字幕、背景音乐或配音
• 调整视频分辨率和画面比例

Trigger when: (1) User wants to create an educational/explainer video, (2) User has a vague concept they want visualized, (3) User mentions "3b1b style" or "explain like 3Blue1Brown", (4) User wants to plan a Manim video or animation sequence, (5) User asks to "compose" or "plan" a math/science visualization. Transforms vague video ideas into detailed scene-by-scene plans (scenes.md). Conducts research, asks clarifying questions about audience/scope/focus, and outputs comprehensive scene specifications ready for implementation with ManimCE or ManimGL. Use this BEFORE writing any Manim code. This skill plans the video; use manimce-best-practices or manimgl-best-practices for implementation.

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Trigger when: (1) User wants to create an educational/explainer video, (2) User has a vague concept they want visualized, (3) User mentions "3b1b style" or "explain like 3Blue1Brown", (4) User wants to plan a Manim video or animation sequence, (5) User asks to "compose" or "plan" a math/science visualization. Transforms vague video ideas into detailed scene-by-scene plans (scenes.md). Conducts research, asks clarifying questions about audience/scope/focus, and outputs comprehensive scene specifications ready for implementation with ManimCE or ManimGL. Use this BEFORE writing any Manim code. This skill plans the video; use manimce-best-practices or manimgl-best-practices for implementation.

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Trigger when: (1) User wants to create an educational/explainer video, (2) User has a vague concept they want visualized, (3) User mentions "3b1b style" or "explain like 3Blue1Brown", (4) User wants to plan a Manim video or animation sequence, (5) User asks to "compose" or "plan" a math/science visualization. Transforms vague video ideas into detailed scene-by-scene plans (scenes.md). Conducts research, asks clarifying questions about audience/scope/focus, and outputs comprehensive scene specifications ready for implementation with ManimCE or ManimGL. Use this BEFORE writing any Manim code. This skill plans the video; use manimce-best-practices or manimgl-best-practices for implementation.

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操作Unreal Engine编辑器，放置场景物体，调整灯光、材质和相机构图。检查场景状态与视觉效果，并输出截图或渲染图。

• 搭建三维关卡并布置物体
• 调整符合场景氛围的灯光
• 设置相机构图并输出渲染图

将目标图片与已实现的3D场景截图进行比较，逐步改善构图、照明和材质。记录视觉还原度评分与修改建议，并检查渲染速度，在需要时进行优化。

• 制作接近目标图片的3D场景
• 打磨浏览器游戏的照明与材质
• 改善现有3D作品的视觉效果

Build an immersive scroll-scrubbed "fly through the world" landing page for any industry or brand using Higgsfield. As the visitor scrolls, a pre-rendered camera flies from outside each scene into its interior, then flows on to the next scene with NO cuts — one continuous connected flight (Emons-style isometric diorama world, or any art direction you pick). The skill interviews the user for the topic, the story beats/sections, and brand kit, then generates cohesive scenes + seamless camera clips with Higgsfield and wires a portable, framework-agnostic scroll-scrub engine. The video chain renders through Monid by default (Seedance 2.0, pay-per-clip USD — capability re-checked each build, see Step 4) with Higgsfield credits as the fallback biller. Use when the user wants a "3D world" / "browse-through-the-industry" hero, a scroll cinematic, a diorama landing, or to turn a business into a scrollable world.

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Think and work like an expert Computer Graphics Researcher. Use when a task calls for Computer Graphics Researcher judgment. Reasons from the rendering equation, Monte Carlo bias/variance, sampling theory, and BSDF energy conservation through pbrt-v4/Mitsuba 3 references, MIS/ReSTIR/path guiding, DXR 1.2 real-time stacks, 3DGS and NerfBaselines protocols, FLIP/ColorVideoVDP evaluation, OpenUSD/MaterialX/OpenPBR interchange, and ACES 2/OCIO color while treating unconverged references, unequal-time comparisons, denoiser and temporal-reuse bias, scene- vs display-referred color errors, and white-furnace energy failures as first-class failure modes.

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Use when adding a plugin to the marketplace, or when authoring, editing, or re-rendering a scene under scripts/animations/scenes/ — including when a scene fails the render contract, the contrast gate, or the grid baseline.

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Search and preview Irasutoya illustrations with the installed `irasutoya` command-line tool. Use this skill whenever the user wants to find, recommend, preview, randomly pull up, or get the page/image URL of an Irasutoya (いらすとや) image — from a topic, scene, Korean/Japanese/English phrase, visual description, emotion, character, object, or action — even if they don't say "Irasutoya" by name but clearly want a free, cute illustration for a slide, 발표자료, blog, doc, or chat. Also use it to optimize vague requests into fast Japanese keyword candidates and to return page/image URLs. Do NOT use it to generate brand-new AI art (e.g. DALL·E, Midjourney), draw charts or diagrams, design logos or icons, cut out/edit existing images, or recommend other stock-image sites — it only searches Irasutoya's existing catalog.

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运用公开信息调查方法，将照片、视频和公开记录中的零散线索串联起来，核实地点、时间及组织关系，区分证据与假设，并整理反证和未确认事项。

• 核实公共场所照片的拍摄位置
• 从公开记录重建事件时间线
• 调查企业与域名的关系

通过OpenHue CLI和Hue Bridge控制Philips Hue照明，支持单个灯泡或整个房间的开关、亮度与颜色调节，以及已保存场景的应用。

• 观影前调暗灯光
• 将卧室调为柔和暖光
• 调亮工作室照明

将数学概念、公式推导和算法执行过程制作成动画解说视频。使用Manim Community Edition，从内容规划、场景绘制到视频拼接，以图形辅助理解。

• 用图形解释数学概念
• 逐步展示公式推导
• 可视化算法执行过程

Find reusable visual effects, charts, titles, and other video elements, then install and integrate them into HyperFrames compositions. It explains how to place standalone scenes on a timeline and merge smaller effect snippets into existing HTML.

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• Find and add a title effect or transition
• Integrate charts, maps, or terminal visuals into a video
• Install multiple video blocks sharing a tag

Create pixel art illustrations as SVG files, a scalable image format, for READMEs, documentation, and slides. Build character portraits, conversations, or group scenes, then refine colors, speech bubbles, arrows, and spacing to fit the requested layout.

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• Create a pixel art hero image for a README
• Illustrate a conversation with characters and speech bubbles
• Make a character illustration in project colors

Build continuous-shot motion-driven HTML stories from a subject or narrative, including research, story structure, consistent AI stills, Seedance scene and connector clips, interface styling, media normalization, and browser QA. Use for immersive journeys, timelines, product stories, fictional worlds, or other scene-based visual narratives whose camera should flow from beginning to end; not for ordinary autoplay video pages or general web apps.

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Detect and humanize AI-generated Chinese text. 20+ rule detection categories plus statistical features (sentence-length CV, short-sentence fraction, comma density, perplexity, GLTR, DivEye) plus scene-aware LR fusion (rule × 0.2 + LR × 0.8) trained on three scenes: general / academic / longform 长文本 (≥1500 字)。Unified CLI: ./humanize {detect,rewrite,academic,style,compare}. 8 style transforms (casual/zhihu/xiaohongshu/wechat/academic/literary/weibo/novel)。 Multi-paragraph rewriting (paragraph length CV、跨段 trigram 重复) plus best-of-N humanize (默认 N=10 取最低 LR)。165 replacement patterns + CiLin 同义词词林 38873 with collision blacklist。 Academic paper AIGC reduction for CNKI/VIP/Wanfang (知网/维普/万方 AIGC 检测降重)。 Pure Python, no dependencies, offline。v5.0.0 — HC3 fused 准确率 95%、学术 hero 100→35 (-65)、 工作汇报 96→13 (-83)、长篇博客 96→41 (-55)。 Use when user says: "去AI味", "降AIGC", "人性化文本", "humanize chinese", "AI检测", "AIGC降重", "去除AI痕迹", "文本改写", "论文降重", "知网检测", "维普检测", "AI写作检测", "让文字更自然", "detect AI text", "humanize text", "reduce AIGC score", "make text human-like", "去ai化", "改成人话", "去机器味", "降低AI率", "过AIGC检测", "长文本改写", "小说改写"

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