/neon-motion

name: neon-motion-pptx
description: "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."

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.

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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 provide
• `No 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.

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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).

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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 on