「video」の検索結果

Summarize or extract text/transcripts from URLs, podcasts, and local files (great fallback for “transcribe this YouTube/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。

Free web search via DuckDuckGo — text, news, images, videos. No API key needed. Prefer the `ddgs` CLI when installed; use the Python DDGS library only after verifying that `ddgs` is available in the current runtime.

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。

GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, NSFW detection. Scales across GPUs with RAPIDS. Use for preparing high-quality training datasets, cleaning web data, or deduplicating large corpora.

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。

Best practices for Remotion - Video creation in React

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。

Systematically explore and test a web application to find bugs, UX issues, and other problems. Use when asked to "dogfood", "QA", "exploratory test", "find issues", "bug hunt", "test this app/site/platform", or review the quality of a web application. Produces a structured report with full reproduction evidence -- step-by-step screenshots, repro videos, and detailed repro steps for every issue -- so findings can be handed directly to the responsible teams.

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。

Posts content and articles to X (Twitter). Supports regular posts with images/videos and X Articles (long-form Markdown). Uses real Chrome with CDP to bypass anti-automation. Use when user asks to "post to X", "tweet", "publish to Twitter", or "share on X".

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。

视频生成 - AI视频生成与后期剪辑制作 职责：调用Vidu生成视频、模型选择、Prompt调优、视频拼接、质量检测

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。

Maxim action choreography video — engineered for emotional arousal and sales lift through Arousal-Based Persuasion. Uses Mirror Neurons + Arousal-Misattribution + Kinetic Energy Perception to drive emotional peak that transfers to brand preference and purchase intent.

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。

Maxim 2D cartoon explainer video — engineered for learning retention and friendly brand affinity. Uses Dual Coding Theory + Cognitive Load Reduction + Ekman Universal Emotion to make complex ideas memorable and brands feel trustworthy-approachable.

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。

Maxim fashion editorial video — engineered for aspirational desire and status signaling via Aesthetic Resonance + Aspirational Self + Social Comparison Theory. Fashion films that trigger status-driven purchase behavior.

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。

Maxim product turntable video — engineered for pre-ownership feeling via Endowment Effect + Visual Completion Bias. The structured rotation format that makes viewers mentally "hold" the product → purchase intent lift.

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。

Maxim social-hook video — engineered for lead gen and top-of-funnel acquisition via 2-Second Hook Science + Zeigarnik + Variable Reward. Platform-optimized short-form that turns scrollers into followers, subscribers, and leads.

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。

Maxim anime-action video — engineered for tribe identity and brand loyalty in youth markets. Uses Social Identity Theory + Pattern Interruption + Emotional Amplification to create brand-tribe belonging that translates to loyalty and advocacy.

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。

Maxim e-commerce direct-response video — engineered for PURCHASE. The primary sales style. Uses AIDA + JTBD + Loss Aversion + Scarcity + Anchoring stacked for maximum conversion. Every second is behavioral leverage.

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。

Maxim motion-design + kinetic typography video — engineered for comprehension-to-conversion via AIDA + Hick's Law. Explainer-ad hybrid that makes complex value props land in under 15 seconds and converts via behavioral-architected CTA.

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。

Repurpose one piece of content across platforms — "repurpose this for all platforms", "turn this into a thread and a LinkedIn post", "make platform versions of this". Each output is written for its platform, not reformatted.

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。

Research synthesis from sources — "summarize these URLs or papers", "research this topic with these sources", "create a podcast about", "audio overview", "mind map", "quiz from these sources", "flashcards", "deep research on". Wraps Google NotebookLM via notebooklm-py.

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。

Analyze a screen recording of a manual process and produce targeted, working automation scripts. Extracts frames and audio narration from video files, reconstructs the step-by-step workflow, and proposes automation at multiple complexity levels using tools already installed on the user machine.

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。

GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, NSFW detection. Scales across GPUs with RAPIDS. Use for preparing high-quality training datasets, cleaning web data, or deduplicating large corpora.

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。

Pixel art w/ era palettes (NES, Game Boy, PICO-8).

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。

Free web search via DuckDuckGo — text, news, images, videos. No API key needed. Prefer the `ddgs` CLI when installed; use the Python DDGS library only after verifying that `ddgs` is available in the current runtime.

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 images, video, and audio with ComfyUI — install, launch, manage nodes/models, run workflows with parameter injection. Uses the official comfy-cli for lifecycle and direct REST/WebSocket API for execution.

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 for any question about a codebase, its architecture, file relationships, or project content — especially when graphify-out/ exists, where the question should be treated as a graphify query first. Turns any input (code, docs, papers, images, videos) into a persistent knowledge graph with god nodes, community detection, and query/path/explain tools.

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。

E2E artifact handling routing. Use when traces, videos, screenshots, reports, or failure bundles need controlled repository-local placement; do not use for simple unit tests or production-mutating E2E 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。