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Found 307 Skills
Video understanding for any model — native passthrough for small files, frame extraction + audio transcription fallback for large files. Use when the user asks to analyze, describe, or understand a video file (e.g. "what's in this video", "summarize this clip", "transcribe this recording").
Use when generating or editing video on Scenario via MCP: text-to-video, a music video from a song, image-to-video (still animation, frame anchors), motion prompting, lipsync and talking avatars, dubbing a clip, video upscale to 4K, prompt-based editing, trim, split, concat, extend, reframe, resize, background removal, frame or audio extraction, long video jobs, or a clip over a duration limit. Keywords: txt2video, img2video, video2video, audio2video, I2V, T2V, V2V, localization.
Use when generating or editing video with Kling models on Scenario via MCP: text-to-video, image-to-video with first and last frames, multi-shot sequences with per-shot prompts, consistent characters via elements and reference images, prompt-based video editing, motion transfer from a driving video (motion control, mocap), lipsync to audio or text, talking avatars, native audio and dialogue, or picking 720p, 1080p, or 4K tiers. Keywords: Kling V3, O1, 2.6, Omni, Kuaishou, T2V, I2V, V2V.
Use when generating or extending video with Google Veo models on Scenario via MCP: text-to-video, image-to-video from a first frame, first and last frame transitions, reference-to-video (R2V) with asset or style reference images, native audio with dialogue, sound effects, and ambience, negative prompts, seeded reruns, extending a 16:9 clip, or choosing a quality, fast, or lite tier. Keywords: Veo 3.1, Veo 3.1 Fast, Veo 3.1 Lite, Extend Video, Google, T2V, I2V, V2V, 720p, 1080p.
Remove, replace, or modify video backgrounds using each::sense AI. Create transparent backgrounds, virtual offices, green screen effects without green screens, blur effects, and professional video compositing.
Change ANYTHING inside a video — background, scene, lighting, outfit, weather, mood — from a free-form prompt, while keeping the EXACT original facial identity, motion, speech, audio AND closest supported output ratio. Edits the first frame with gpt-image-2, then propagates that look across the clip with Kling reference-video using the original clip as the identity anchor. Triggers: "change anything in my video", "edit my video with a prompt", "change the background of this video", "change my outfit in this clip", "restyle this video without changing the person", "put me on a beach", "make this video at night", "/fix-my-look".
Use when the user asks for stagefight or a task matching the examples below. Generate a viral "fan-filmed staged fight" clip — POV phone footage of two costumed performers having a choreographed cosplay battle on an elaborate themed stage at a live outdoor event, with a believable live-stage effect (smoke / colored fire / water geyser) and a crowd in the foreground filming. A gpt-image-2 stage still → image-to-video (Seedance, ~10s, 16:9). The advertiser-safe "theatrical performance" framing is what gets fight content past moderation. Triggers: "/stagefight", "make a staged fight video", "fan-filmed cosplay fight", "ninja/samurai stage battle", "that staged fight trend". Requires the pika MCP.
Create ecommerce product demo videos, SaaS demo videos, app promo clips, and tool walkthrough-style videos with GPT Image 2 and Seedance 2 on EvoLink. Use this skill when the user needs to show what a product is, how it works, or why it matters.
【Viral Remake】Viral Content Remake — Break down benchmark viral videos into structure and transferable formulas (with evidence grading, no speculation), then swap in your product's real selling points to produce a remake script or AI video-generation prompts; until actionable selling points are provided, only deliver structural analysis—never invent selling points or fabricate product appearance. Triggers when users say: "Help me break down this viral video", "How do I copy this video structure?", "Make one for my product based on this video", "Remake with a different product", "Write video-generation prompts for me".｜Produced by Xiaoye
Use when one look must hold across Scenario generations: one character across scenes, a turnaround, or a video animated from its references, one product across angles, one style across icon sets, a character from an uploaded drawing, a variant off an approved baseline, or deciding when references stop scaling and a trained model is due. Triggers: make this match, same character, on-model, reference to video, style reference. Keywords: consistency, identity, control map, seed, LoRA.
Use when generating or editing video with Seedance models on Scenario via MCP: text-to-video, image-to-video from a first frame, first and last frame anchors, reference-to-video with identity, product, or world references, prompt-based editing, extending a clip, audio-conditioned motion, shot sound without music, or deciding between first-frame and reference conditioning. Keywords: Seedance 2.5 and 2.0, ByteDance, T2V, I2V, V2V, multimodal references, native audio, video extension.
Generate a 15-second cinematic awards-ceremony video — a host announces a winner from the stage, a spotlight finds them in the crowd, they walk up to the podium, receive the award, and the LED display reveals their name and "THE BEST ACTOR".