happycapy-ai/happycapy-skills/neon-motion
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Reusable fixed-style PPTX generation skill for the Neon Motion visual brand — a premium cinematic pitch built from editorial motion photography and restrained typography, with electric cyan (#08BFEA) versus saturated orange (#FF7317) light, deep petrol, near-black, white, and cool paper gray, thin geometric sans titles, hairline rules, tiny vertical metadata, and generous empty space, in widescreen 16:9 editable .pptx output. Use this skill whenever the user mentions Neon Motion, asks for a presentation or deck in the Neon Motion style, wants a cinematic / motion-poster / editorial-photography pitch deck, a premium cyan-and-orange motion-lit deck, or a restrained-typography image-led deck. Also trigger when the user says 'neon motion', 'motion poster deck', 'cinematic pitch deck', 'cyan and orange deck', 'editorial motion deck', or 'premium photographic pitch' in any context. Display name: Neon Motion PPTX.
Install
npx vskill@latest install happycapy-ai/happycapy-skills/neon-motionSKILL.md
Neon Motion PPTX Skill
A reusable fixed-style PowerPoint generation skill. It builds on the pptx skill's technical capabilities while locking in the Neon Motion visual identity: a premium cinematic pitch built from editorial motion photography and restrained typography — full-bleed motion imagery in electric cyan versus warm orange light, thin geometric sans titles, hairline rules, and generous empty space.
Core principle — restraint and cinema win over content volume. When the user's topic carries more information than the format can hold gracefully, compress it into sparse typographic rows, one compact chart, a timeline, concise metric moments, and extra slides. The deck must feel like a premium cinematic pitch for the user's topic — not a dark SaaS dashboard, an AI report, a cyberpunk poster, a conference deck, a generic startup template, a cluttered product report, or a text-heavy memo.
This skill is topic-agnostic. It generates Neon Motion decks for any user-provided topic. Never hardcode a sample topic (a company name, AI customer intelligence, sales pitches, revenue operations, a specific year, fictional metrics, fixed pricing, or fixed product features) into a deck. Any topic-specific wording in this file is an example only — replace it at runtime with the user's topic variables.
Step 1: Gather Inputs (Ask First — Max 3 Questions)
Do not start generating immediately. Use the AskUserQuestion tool to present the missing questions in a single call (up to 3 at once). Only ask what the user hasn't already provided — if they gave the topic, slide count, or image choice, skip that question. Don't ask extra questions unless the deck literally cannot be built without them.
Question 1 — Topic (skip if already provided):
- header: "Topic"
- question: "What is the topic, product, company, or title of the deck?"
- options: 2–3 relevant example topics plus allow Other
Question 2 — Slide count (skip if already specified):
- header: "Slides"
- question: "How many slides should the deck include?"
- options:
8 slides,10 slides (Recommended),12 slides,15 slides
Question 3 — Images:
- header: "Images"
- question: "How should visuals be handled?"
- options:
Generate with gpt-image-2— Cinematic cyan/orange motion photography + topic theme visuals (Recommended)Use my uploaded / reference images— Insert images I provideNo generated images— Native typography, hairlines, and charts only (color-field plates stand in for photos)
If the user hasn't provided data, dates, audience, or other details, infer neutral content or use clearly labeled placeholder figures (see Content Rules). Do not keep asking. Once you have the three core answers, proceed to generation.
Note on the no-images choice: the Neon Motion style leans heavily on cinematic photography. If the user picks No generated images, replace every full-bleed photo with a full-bleed cyan→orange color-field plate (layered translucent CYAN/ORANGE/PETROL shapes) so the motion-lit feel survives — never leave photo zones blank or fall back to a plain dark canvas.
Step 2: Topic Translation — Everything Becomes a Cinematic Pitch
Before writing any slide copy, translate the user's topic into a Neon Motion frame. Every subject becomes a restrained, image-led pitch sequence — while preserving the user's actual subject.
| User provides | Neon Motion treatment | |
|---|---|---|
| Product / launch | A cinematic product pitch: motion cover, one mockup frame, one proof metric | |
| Strategy / plan | A restrained narrative: challenge rows, one timeline, one closing ask | |
| Research / concept | An editorial essay: statement plates, one chart, sparse agenda lines | |
| Service / brand | A premium brand film: motion plates, one claim per slide, quote plates | |
| Any other subject | Reframe as a cinematic, photography-led pitch with restrained type |
Decide these before writing slides:
- The motion energy for the imagery (what kind of anonymous human/topic motion moves through cyan-and-orange light).
- The one-line cover title (thin white sans, no tagline).
- The wordmark (a product/company name, if any — placed tiny, never merged into the big title unless the user asks).
Step 3: Generate Images (only if the user chose gpt-image-2)
If the user chose No generated images, skip generation and use color-field plates (Step 1 note). For uploaded images, place them full-bleed or in small crops/mockup frames, and use color-field plates where an image is missing.
If the user chose gpt-image-2, read the generate-image skill at /home/node/.claude/skills/generate-image/SKILL.md for the exact API call pattern. Use openai/gpt-image-2 with response_format: "b64_json" and aspectRatio matching placement ("16:9" full-bleed, "4:3" thumbnails/mockups). Save each image to /tmp/neon-motion-img-N.png.
Generate two clearly separated asset types (these labels are production notes only — never printed on a slide). Both must contain no readable text, no logos, no brand marks, no readable faces.
Decorative image set — editorial long-exposure / cinematic motion photographs for the cover, full-bleed section plates, quote plates, and closing:
Theme image set — restrained topic-support visuals for content slides (fictional interface mockups, minimal product-support scenes, anonymous team/workspace photography, other topic-specific support):
Theme assets support the story; they never replace native editable charts, text, or structured content. Never use gpt-image-2 for full-slide screenshots, slide mockups with embedded text, text-heavy graphics, charts with embedded numbers, logos, or brand marks — those are always native PowerPoint.
Count guidance: 8 slides → 3–4 images · 10–12 slides → 4–6 · 15 slides → 6–8. Keep most of them decorative motion plates.
Step 4: Build the PPTX
Read the pptx skill at /home/node/.claude/skills/pptx/SKILL.md and its pptxgenjs.md reference for the full API and gotchas. Build with PptxGenJS as editable native elements. Output must be an editable widescreen 16:9 .pptx. Do not create HTML, web presentations, screenshots of slides, or rasterized full-slide composites. Generated images may be inserted only as supporting photographic/visual assets.
Core style constants — do not deviate
Fonts are chosen from the pptx skill's QA-safe list so overflow checks stay trustworthy. Evoke the clean geometric-sans feel through light/regular weight and letter-spacing (charSpacing), never heavy bold — never place a heavy bold title on an image slide. PptxGenJS has no true gradient fill; build any cyan→orange color-field plate from a generated/uploaded image or by layering 2–3 translucent shapes (transparency:), never a baked-alpha hex.
Typography sizing (strong hierarchy, generous space)
| Role | Size | Notes | |
|---|---|---|---|
| Cover title | 64–76 pt | one thin white line, never bold | |
| Slide headline | 34–54 pt | one per slide | |
| Metric numerals | 42–64 pt | proof moments | |
| Body copy | 18–22 pt | fragments, never paragraphs | |
| Metadata / vertical labels | 9–12 pt | uppercase, charSpacing: 2–6 | |
| Chart labels | 10–14 pt | axis, data labels, legends |
Layout — LAYOUT_WIDE (13.3" × 7.5") for a true 16:9 canvas
Set pres.layout = "LAYOUT_WIDE" before adding slides. All coordinates below assume a 13.3 × 7.5 canvas.
The Cover — Follow This Composition Strictly
A premium motion-poster cover. Build every text/rule/thumbnail element as editable native shapes/text over the background image — never an image of a finished cover.
Keep all cover copy under 18 visible words (excluding contact/context details). Do not put a subtitle, tagline, email-as-headline, agenda, metrics, product screenshot, portrait card, KPI, chart, panel, border, or explanatory paragraph on the cover. If elements start to crowd, remove the descriptor or glyph row first.
Content Slides — From Slide 2 Onward
Use a restrained editorial rhythm: alternate white / cool-paper-gray canvas slides with full-bleed motion-photo slides. Build from these modules (all editable native elements except the photos themselves), varying them across the deck:
This is the start of the file. Read the full SKILL.md on GitHub.
Security
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Source
- SKILL.md in the repositoryCheckingskills/neon-motion/SKILL.md
Popularity
- Repository stars
- 137
- Repository forks
- 30
- 7-day trend score
- 25
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