MediaKit 是面向音视频与图像处理的专业工具集,覆盖视频剪辑与合成、音频处理、视频理解与增强、图像处理与内容理解等工作流。用户明确提出剪辑、拼接、裁剪、转场、滤镜、运镜、混音、提取字幕、语音转字幕、音视频处理、图片处理、视频分析或画质增强目标时,先加载本 Skill,再按对象和目标选择 audio、editing、image 或 video。不承担具体能力参数说明。
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。
動画編集、サムネイル、マンガ、音声(3,150 件)
概要と使いどころ
MediaKit 是面向音视频与图像处理的专业工具集,覆盖视频剪辑与合成、音频处理、视频理解与增强、图像处理与内容理解等工作流。用户明确提出剪辑、拼接、裁剪、转场、滤镜、运镜、混音、提取字幕、语音转字幕、音视频处理、图片处理、视频分析或画质增强目标时,先加载本 Skill,再按对象和目标选择 audio、editing、image 或 video。不承担具体能力参数说明。
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。
面向视频文件的智能处理、媒资理解、画质治理与画质检测、抽帧、隐私保护、语音转字幕、字幕提取、字幕擦除、水印处理、精彩片段与高光拆条分析生成、剧情结构化与剧本整理、场景与语义分段、画面文字识别、视频转码转封装及抠像换脸等目标。若对象和目标族已明确属于视频增强、视频分析理解、视频内容结构化、从视频提取字幕、语音转字幕、视频字幕识别或擦除、视频隐私脱敏、视频媒资探测或分发适配,但具体能力不确定,可先加载本 Skill 探索。
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。
Standardize a 2D animation baseline image with `/img2mo-std xxx.png/pos`. Use when preparing a character, creature, prop, or weapon baseline before motion generation, especially if the source image is too large, tightly cropped, lacks transparent action margin, has a white background, or later walk/attack/idle frames show clipping, overlap, scale popping, or inconsistent character size.
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 one line ("a turbofan jet engine", "a mechanical watch", "an LVAD heart pump") into a photoreal, physics based, interactive 3D simulation of that machine in a single HTML file, plus a 20 to 30 second film to post it. Real proportions in metres, real materials (PBR metals, paints, polymers, glass), studio lighting with soft shadows, moving parts driven by a small solver that computes real numbers (thrust, torque, rpm, flow, pressure, efficiency), and modes to explode it, cut it open with clean section caps, x-ray it, slow it down, label it and break it. Use this whenever someone asks to build, simulate, visualise, explain or "show how X works" for any machine, engine, mechanism, device, instrument or piece of hardware, wants an interactive 3D model or a cutaway, or wants a video of a machine for a post, even if they never say "simulation" or "three.js".
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 user asks to analyze an image, describe image contents, or answer questions about a picture. iFlytek Image Understanding (图片理解) — analyze and answer questions about images using Spark Vision model. WebSocket API, pure Python stdlib, no pip dependencies.
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。
Ultra-fast speech transcription using iFLYTEK Speed Transcription API. Transcribe audio files (WAV/PCM/MP3) up to 5 hours in ~20 seconds per hour. Supports Chinese, English, and 202+ Chinese dialects with automatic language detection. Use when user asks to transcribe audio files, convert speech to text, or mentions "speed transcription" or "极速转写".
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 user asks to synthesize speech, convert text to audio, or read text aloud. 讯飞超拟人语音合成 - 支持文本转语音、语音合成(发音人/语速/语调/音量/输出格式)。大模型语音合成技能。语音合成, 文字转语音, 超拟人, TTS.
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 user asks to clone a voice, train a custom voice model, or synthesize speech with a cloned voice. iFlytek Voice Clone tts(声音复刻) — train a custom voice model from audio samples and synthesize speech with the cloned voice. Supports the full workflow: get training text → create task → upload audio → submit training → poll results → synthesize with cloned voice. Pure Python stdlib, no pip dependencies.
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。
ifly-pdf-image-ocr skill supporting both image OCR (AI-powered LLM OCR) and PDF document recognition. Use when user asks to OCR images, extract text from images/PDFs, convert PDF to Word/Markdown, or perform any OCR tasks on images or PDFs. Supports multi-language text extraction, document layout understanding, and various output formats.
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 user asks to translate videos, dub video content, or localize videos into other languages. Translate videos with AI-powered dubbing using iFlytek (Xfei) Video Translation API. Supports video language translation, voice dubbing, multilingual video localization, 视频翻译, 视频配音, 视频本地化. Features task creation, task list, task details retrieval. Ideal for content creators and localization 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。
Think and work like an expert Glycobiologist. Use when a task calls for Glycobiologist judgment. Reasons from N-/O-glycan biosynthesis, O-GlcNAc cycling (OGT/OGA), LC-MS glycomics, exoglycosidase sequencing, and lectin microarrays; uses GlyTouCan/SNFG/MIRAGE, pGlyco/GlycoWorkbench, and treats PNGase F limits, isomer collapse, and ER-stress high-mannose 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。
Think and work like an expert Gerontologist. Use when a task calls for Gerontologist judgment. Reasons from senescence hallmarks, frailty, multi-morbidity, and life-course exposures through validated instruments (Fried phenotype, Rockwood CFS, SPPB/gait speed), epigenetic clocks (Horvath, PhenoAge, GrimAge), competing-risk survival (Fine-Gray), and NIA cohorts (HRS, NHATS, ITP) while treating survivor bias, differential attrition, healthy-volunteer bias, and frail-subset toxicity 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。
Think and work like an expert Audiologist. Use when a task calls for Audiologist judgment. Reasons from auditory transduction, site-of-lesion localization, audibility, and noise dose-response through calibrated pure-tone/masking audiometry, immittance, OAE and ABR/ASSR, and real-ear verification against NAL-NL2/DSL targets while treating unmasked cross-hearing, collapsed ear canals, transducer miscalibration, and non-organic loss 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。
Generate Xiaohongshu (XHS / RedNote) cover images using GPT Image 2 / Codex image generation first, with the legacy Gemini CLI as fallback. Triggers for cover generation: "生成封面", "小红书封面", "xhs封面", "制作封面", "帮我做张图", "XHS cover", "RedNote cover". Triggers for cover editing: "修改封面", "改一下封面", "上一张图基础上", "基于这张图调整", "不要重新做", "edit this cover". Triggers for style learning: "学习这个风格", "提取风格", "我想自定义风格", "这张图的风格", "learn this style", "extract style". Always trigger this skill when user mentions 小红书/XHS/RedNote together with 封面/cover/图片, OR when user uploads a reference image and asks about creating a similar style.
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。
Plan and scope production work with Odyssey's real-time interactive video world models (odyssey.ml — Odyssey-1/Odyssey-2/Starchild-1/Agora-1). Use when a request involves generating video that a user steers live with keyboard, text, speech, or controller input (streamed frames that respond in the moment), or when someone must decide between Odyssey-style interactive generation and offline clip generators (Sora/Veo/Kling) or downloadable 3D / game engines. Covers what is verified versus announced, current access routes, latency and coherence limits, feasible-now versus speculative use cases, pricing/access terms, and content/rights considerations. This is a fast-moving research-stage product; the skill teaches honest scoping, not a promise of production reliability.
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 persistent, explorable 3D worlds/environments with Marble by World Labs — from text, a single image, multiple images, video, or a 360 panorama, plus coarse-structure blocking with Chisel. Use this skill when a task needs a navigable 3D scene, VR/immersive backdrop, virtual-production environment, previz set, game-blockout, or web/engine-ready Gaussian splat or mesh, and you must choose an input mode, a Marble model, an export format, and a plan/API route, then review world quality. Covers the Marble web app and the World API, editing/expansion, output formats and what each supports downstream, import into Unity/Unreal/Blender/Houdini/web, pricing/credits, capability limits, and rights/licensing. Not for flat text-to-image, text-to-video clips, or real-time on-the-fly world models (Marble outputs are downloadable, static 3D environments).
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。
Local and self-hosted text-to-speech with Kokoro, the ~82M-parameter open-weight (Apache 2.0) model by hexgrad. Use when synthesizing speech offline, on-device, in the browser, or on your own server without per-character API cost — for high-volume narration, audiobooks, privacy-constrained pipelines, and prototyping. Covers running Kokoro via the Python `kokoro` package, ONNX / kokoro-js in the browser, and the OpenAI-compatible Kokoro-FastAPI wrapper; picking voices and language codes; blending voices; chunking long text; controlling pronunciation via misaki/espeak-ng; and judging when Kokoro is the right tool versus when its lack of voice cloning, narrow emotional range, and weaker non-English quality mean you should reach for a hosted or larger model instead. Not for voice cloning, expressive/emotional character performance, or high-fidelity multilingual work — say so and route elsewhere.
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。
Select, integrate, and operate multi-model video-generation gateways — hosted inference aggregators such as fal.ai, Replicate, and WaveSpeed that expose many third-party video (and video-adjacent audio) models behind one account, one API surface, and one bill. Use when deciding whether to route video generation through a gateway versus a direct model-provider API; when comparing gateways on catalog, async/queue job design, webhooks, pricing, schema discovery, and version pinning; and when operating gateway workloads in production — spend controls, retries, cross-gateway failover, content- safety differences, data retention, and commercial-rights passthrough of the underlying model. Not for direct model-provider APIs, local/self-hosted inference, model training/fine-tuning, or image-only gateway use.
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。
Plan and integrate ShengShu Vidu Open Platform video generation with current model/mode selection, reference consistency, pricing, exact approval, async task handling, and safe artifact custody. Use for Vidu API text-to-video, image-to-video, start/end-frame, multi-subject reference, media-reference, or Q2 multi-frame work; do not conflate the API with vidu.com consumer plans or Vidu-S1 streaming digital humans.
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。
Plan, prompt, generate, reference, edit, motion-control, and quality-review videos with Kuaishou's direct Kling AI video platform and API, especially Kling VIDEO 3.0, 3.0 Omni, 3.0 Turbo, native audio, multi-shot, elements, start/end frames, and image/video references. Use for first-party Kling video production or API integration, not Kolors image generation, avatars, standalone audio, consumer-only membership advice, or third-party Kling gateways.
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, reference, and conversationally edit short videos with Google's Gemini Omni Flash through the Gemini Developer API or Gemini Enterprise Agent Platform. Use when a task specifically needs Gemini Omni video, multimodal reference roles, time-directed prompting, audio-aware generation, Interactions API state, or a precise comparison with Veo, Nano Banana, consumer Gemini, or gateway routes.
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 speech and clone voices with Fish Audio — its hosted TTS API (S2.1-Pro / S2-Pro / S1 model lineup, REST + WebSocket streaming, instant and persistent voice cloning) and its open-weight OpenAudio S1-mini / Fish-Speech models for self-hosting. Use this skill when an agent must generate narration or dialogue through Fish Audio, choose between Fish Audio's hosted models and open weights, clone a voice from reference audio, author emotion/tone/special markers for expressive delivery, estimate cost from UTF-8 bytes, wire real-time streaming for a voice agent, decide whether self-hosting beats the API, or review Fish Audio TTS output for production. Do not use it to pick a different provider — it covers Fish Audio specifically.
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, edit, extend, and govern short videos with xAI's direct Grok Imagine Video API. Use for text-to-video, image-to-video, multi-reference video, natural-language video edits, video continuation, exact media-cost approval, asynchronous request recovery, Files/Batch integration, moderation review, and API privacy or residency decisions. Covers `grok-imagine-video` and image-only `grok-imagine-video-1.5`; excludes Grok consumer subscriptions, Grok on X, still-image generation, voice APIs, and third-party gateways.
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.
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。