End-to-end motion-design / animated-ad creation flow on Higgsfield via the MCP connector. Use when the user wants to create motion design, animate a logo, make a video from an image, build an animated ad or brand promo, turn a product into motion, or says 'make a motion', 'motion design', 'animate this', 'make a video from my logo', 'animated brand', 'motion graphics', 'brand motion', 'kinetic graphics', 'promo video', or 'ad video'. Drives a storyboard-first pipeline: brief → storyboard sheet (GPT Image 2) → video (Seedance 2.0) — an AI-generated pixel video clip. Distinct from higgsfield-motion (the named camera/motion preset library) and from higgsfield-vibe-motion (deterministic Remotion code with crisp text); use vibe-motion instead when the text/logo must stay perfectly crisp, editable, and deployable as code.
npx skills add https://github.com/OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield-motion-design
A full motion-design creation flow run through the Higgsfield MCP connector. Follow the steps in order, be concise and direct, and reply in the user's language. This skill is the guided *ad/brand-motion* pipeline — for the named camera/motion preset library (Explosion, Werewolf, Air Bending, etc.) use higgsfield-motion instead.
> Not a spec sheet. Model parameter enums (resolutions, modes, durations) come from the specs layer / models_explore — verify there (HARD RULE #3), don't hardcode them here.
seedance_2_0); confirm the model id with models_explore if unsure →Identify which workflow applies before anything else:
If the request makes the flow obvious, proceed silently. If ambiguous, ask once:
> "Which style fits your project better — Classic Motion (smooth, elegant, cinematic) or Hyper / Kinetic (fast cuts, extreme dynamics, CGI energy)?"
Ask all of these in a single message (never split into rounds). Save every answer before proceeding:
If the user HAS assets: when the client is an Apps UI-capable surface, call media_upload_widget immediately so they can attach the local file (remote MCP cannot read chat attachments). For a web media URL, call media_import_url first and pass the returned media_id. Then proceed to Step 3.
If the user has NO assets: generate a base visual with GPT Image 2 (generate_image, model gpt_image_2) — construct the prompt from brand name, mood, style, palette, aspect ratio. Display the result with job_display, ask "Does this work or want changes?", regenerate if needed, then proceed once approved.
The core creative step. Generate one storyboard sheet — a single image with all N panels in a grid (N = the count from Step 1: 6, 8, or 9). Do not generate N separate images.
Call generate_image once with GPT Image 2, passing the approved asset / base visual as a reference. Each panel must: stay visually consistent with the approved asset · represent a distinct moment (opening → build → climax → resolution → logo lock) · show camera position, subject state, motion blur/freeze where relevant · carry a 2–4 word burned-in caption (scene label, not subtitle).
Prompt skeleton:
Storyboard sheet, [N] sequential panels in a grid, each labeled "Frame 1"…"Frame N".
Panel 1: [scene]. Panel 2: [scene]. … Panel N: [logo lock / brand name].
Each panel: [camera angle], [motion state], [mood/lighting]. Style: [cinematic / kinetic].
Consistent color palette throughout. Clean storyboard design, thin borders between panels.
Display with job_display, then present a short storyboard summary (Frame 1…N one-liners + Mood + Motion + Ending) and ask: Approve ✅ or Changes needed (regenerate the sheet, repeat approval).
Once the storyboard is approved, generate the final video with Seedance 2.0 (generate_video, model seedance_2_0 — confirm the id via models_explore if unsure). Build the prompt from: the approved scene sequence, the flow type, duration + aspect ratio (Step 1), mood/style, and the brand name/slogan for the logo lock.
smooth motion design, [scene flow], elegant transitions, [mood] atmosphere, cinematic camera movement, [duration]s, brand reveal at end: [brand], [aspect ratio]high-intensity kinetic motion, [scene flow], extreme camera speed, aggressive match-cuts, peak-action freeze frames, [mood] CGI aesthetic, neon contrast, [duration]s, hard-stop logo lock: [brand], [aspect ratio]For highMD, the final seconds must be a static hold on the brand/logo — build it into the prompt explicitly, scaled to clip length (~1s for 5s, ~2s for 10s, ~2–3s for 15s).
Pass as the start frame: the original uploaded asset if the user had one, otherwise the first approved storyboard frame's job id. Seedance 2.0 carries native audio by default and a genre hint — set genre to match the mood when useful (action/horror/comedy/noir/drama/epic). Display with job_display.
> Resolution note: Seedance 2.0 reaches 4K only in mode=std; mode=fast caps at 720p. See higgsfield-seedance / the specs layer.
Present the render and ask: Love it ✅ (done) · Different edit (regenerate, same storyboard) · Different style (back to Step 1) · Another version (a second variation with a slight prompt change).
gpt_image_2). Video model: Seedance 2.0 (seedance_2_0).generate_image, generate_video, job_display, media_upload_widget, media_import_url, media_upload / media_confirm, models_explore, balance — confirm exact ids with tool search if unsure. Check credits with balance if the user seems concerned about usage.higgsfield-motion — the named camera/motion preset library (different skill)higgsfield-vibe-motion — deterministic Remotion code motion graphics (crisp text, exact colors, deployable). Use it instead of this skill when the text/logo must stay perfectly crisp and editable rather than be a rendered video clip.higgsfield-gpt-image-2 — GPT Image 2 prompt craft for the storyboard sheethiggsfield-seedance — Seedance 2.0 prompt formula, modes, and preflight linterhiggsfield-marketing-studio — one-click product-ad surface (alternative to this manual flow)higgsfield-apps — MCP connector tooling (media upload, job display, balance)Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
Improves the quality of images, especially screenshots, by enhancing resolution, sharpness, and clarity. Perfect for preparing images for presentations, documentation, or social media posts.
Downloads videos from YouTube and other platforms for offline viewing, editing, or archival. Handles various formats and quality options.
Lightweight WSI tile extraction and preprocessing. Use for basic slide processing tissue detection, tile extraction, stain normalization for H&E images. Best for simple pipelines, dataset preparation, quick tile-based analysis. For advanced spatial proteomics, multiplexed imaging, or deep learning pipelines use pathml.
Microscopy data management platform. Access images via Python, retrieve datasets, analyze pixels, manage ROIs/annotations, batch processing, for high-content screening and microscopy workflows.
Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.
This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.
Take osidemedia/higgsfield-motion-design from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.