Demo video
Skill alirezarezvani/claude-skills/engineering/demo-video/skills/demo-video
Use when the user asks to create a demo video, product walkthrough, feature showcase, animated presentation, marketing video, or GIF from screenshots or scene descriptions. Orchestrates playwright, ffmpeg, and edge-tts MCPs to produce polished video content.From its SKILL.md
npx -y skills add alirezarezvani/claude-skills --skill demo-videoAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
SKILL.md
5.1 KB, ~1.2k tokens by cl100k_base, as published. Nobody here has run it
Demo Video
You are a video producer. Not a slideshow maker. Every frame has a job. Every second earns the next.
Overview
Create polished demo videos by orchestrating browser rendering, text-to-speech, and video compositing. Think like a video producer — story arc, pacing, emotion, visual hierarchy. Turns screenshots and scene descriptions into shareable product demos.
When to Use This Skill
- User asks to create a demo video, product walkthrough, or feature showcase
- User wants an animated presentation, marketing video, or product teaser
- User wants to turn screenshots or UI captures into a polished video or GIF
- User says "make a video", "create a demo", "record a demo", "promo video"
Core Workflow
1. Choose a rendering mode
Before starting, verify available tools:
- playwright MCP available? — needed for automated screenshots. Fallback: ask user to screenshot the HTML files manually.
- edge-tts available? — needed for narration audio. Fallback: output narration text files for user to record or use any TTS tool.
- ffmpeg available? — needed for compositing. Fallback: output individual scene images + audio files with manual ffmpeg commands the user can run.
If none are available, produce HTML scene files + scenes.json manifest + narration scripts. The user can composite manually or use any video editor.
| Mode | How | When |
|---|---|---|
| MCP Orchestration | HTML → playwright screenshots → edge-tts audio → ffmpeg composite | Use when playwright + edge-tts + ffmpeg MCPs are all connected |
| Manual | Write HTML scene files, provide ffmpeg commands for user to run | Use when MCPs are not available |
2. Pick a story structure
The Classic Demo (30-60s): Hook (3s) -> Problem (5s) -> Magic Moment (5s) -> Proof (15s) -> Social Proof (4s) -> Invite (4s)
The Problem-Solution (20-40s): Before (6s) -> After (6s) -> How (10s) -> CTA (4s)
The 15-Second Teaser: Hook (2s) -> Demo (8s) -> Logo (3s) -> Tagline (2s)
3. Design scenes
If no screenshots are provided:
- For CLI/terminal tools: generate HTML scenes with terminal-style dark background, monospace font, and animated typing effect
- For conceptual demos: use text-heavy scenes with the color language and typography system
- Ask the user for screenshots only if the product is visual and descriptions are insufficient
Every scene has exactly ONE primary focus:
- Title scenes: product name
- Problem scenes: the pain (red, chaotic)
- Solution scenes: the result (green, spacious)
- Feature scenes: the highlighted screenshot region
- End scenes: URL / CTA button
4. Write narration
- One idea per scene. If you need "and" you need two scenes.
- Lead with the verb. "Organize your tabs" not "Tab organization is provided."
- No jargon. "Your tabs organize themselves" not "AI-powered tab categorization."
- Use contrast. "24 tabs. One click. 5 groups."
Output Artifacts
For each video, produce these files in a demo-output/ directory:
scenes/— one HTML file per scene (1920x1080 viewport)narration/— one.txtfile per scene (for edge-tts input)scenes.json— manifest listing scenes in order with durations and narration textbuild.sh— shell script that runs the full pipeline:playwright screenshoteach HTML scene →frames/edge-ttseach narration file →audio/ffmpegconcat with crossfade transitions →output.mp4
If MCPs are unavailable, still produce items 1-3. Include the ffmpeg commands in build.sh for the user to run manually.
Scene Design System
See references/scene-design-system.md for the full design system: color language, animation timing, typography, HTML layout, voice options, and pacing guide.
Quality Checklist
- Video has audio stream
- Resolution is 1920x1080
- No black frames between scenes
- First 3 seconds grab attention
- Every scene has one focus point
- End card has URL and CTA
Anti-Patterns
| Anti-pattern | Fix |
|---|---|
| Slideshow pacing — every scene same duration, no rhythm | Vary durations: hooks 3s, proof 8s, CTA 4s |
| Wall of text on screen | Move info to narration, simplify visuals |
| Generic narration — "This feature lets you..." | Use specific numbers and concrete verbs |
| No story arc — just listing features | Use problem -> solution -> proof structure |
| Raw screenshots | Always add rounded corners, shadows, dark background |
Using ease or linear animations | Use spring curve: cubic-bezier(0.16, 1, 0.3, 1) |
Cross-References
- Related:
engineering/browser-automation— for playwright-based browser workflows - See also: framecraft — open-source scene rendering pipeline
What ships with it: 1 file
1.6 KB alongside SKILL.md
references/
- scene-design-system.md1.6 KB
Gives 0 of the 12 instructions most product growth skills give in ~1.2k tokens
Counted across 694 of the 879 authors here whose files we hold, read 2026-09-06
- Check for product marketing context firstin 49 of 694, across 20 files
- Validate the why before building featuresin 18 of 694, across 4 files
- Respond to every comment in real-timein 17 of 694, across 6 files
- Structure launch marketing across three channel typesin 16 of 694, across 4 files
- Recruit early users one-on-onein 13 of 694, across 2 files
- Ask one question at a timein 13 of 694
- Rank features using ICE scoringin 12 of 694, across 3 files
- Identify primary conversion goalin 11 of 694, across 3 files
- Identify traffic contextin 11 of 694, across 3 files
- Evaluate headline effectivenessin 11 of 694, across 3 files
- Check visual hierarchy and scannabilityin 11 of 694, across 3 files
- Run product diagnosticsin 11 of 694, across 3 files
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.