Suede Video

Suede Video Production

Suede Video turns an approved message and rights-cleared source material into scripts, storyboards, generation plans, edit systems, and reusable production pipelines. It keeps likeness, licensing, brand assets, render cost, and publishing as explicit gates rather than assumptions.

Before Starting

Check for product marketing context first: If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.

Gather this context (ask if not provided):

1. Video Goal

• What type of video? (Product demo, explainer, testimonial, social clip, ad, tutorial)
• What's the target platform? (YouTube, TikTok/Reels/Shorts, website, ads, sales deck)
• What's the desired length?

2. Production Approach

• Do you need a human presenter? (AI avatar vs. voiceover vs. screen recording)
• Do you have existing footage or assets? (Screenshots, logos, product UI)
• Do you need generated footage? (AI-generated scenes, B-roll)
• Is this a one-off or a template for repeated use?

3. Technical Context

• What's your tech stack? (Node.js, Python, etc.)
• Do you have API keys for any video tools?
• Budget constraints? (Some tools charge per minute of video)

Choosing Your Approach

Choose the production method from the job, available evidence, rights, and currently callable tools:

Programmatic Video

Programmatic video is a candidate for repeatable, templated, or data-driven work; verify fit against the current stack, edit needs, cost, and review burden.

HTML/CSS renderer candidate

Hyperframes may fit an HTML/CSS workflow. First check whether it is installed. If it is, read the installed version's documentation, inspect its license, and confirm the renderer and export path. If it is not installed, use a renderer-neutral handoff or request explicit installation authorization after showing the current package source, version, lockfile impact, and cost. The following command must not run without that authorization:

npm install hyperframes

Key concept: Each frame is an HTML document. Compose frames into a timeline, render to MP4.

import { render } from "hyperframes";

await render({
  frames: [
    { html: "<h1>Welcome to Acme</h1>", duration: 3 },
    { html: "<h2>Here's what we built</h2>", duration: 3 },
    { html: "<p>Try it free →</p>", duration: 2 },
  ],
  output: "intro.mp4",
  width: 1080,
  height: 1920, // 9:16 for vertical
});

Candidate fit: Product announcements, changelogs, data-driven reports, and approved personalized outreach videos. Verify determinism with a repeat-render test instead of assuming it.

React renderer candidate

Remotion may fit a React-based workflow. Verify the installed or callable version, current documentation, license, rendering path, and hosting cost. The scaffold command may install packages or create files; run it only with explicit authorization for that change, otherwise provide a renderer-neutral plan:

npx create-video@latest

Key concept to verify: React components express timed visuals and props drive content. Confirm whether rendering is local or uses an authorized hosted renderer.

Read references/programmatic-renderers.md when the repo already uses React, or when the choice between the HTML/CSS and React paths has to be justified: it carries the React component sample and the renderer selection table.

AI Video Generation

Generate original footage from text or image prompts. Use for B-roll, hero visuals, and scenes you can't practically film.

Model comparison

Discover currently callable and authorized models before recommending one. Read current official documentation and run a bounded test on the actual account. Compare:

If no model is callable and authorized, return a shot list, prompt set, reference-frame brief, and manual vendor-evaluation checklist.

Prompting for Video Models

Good video prompts specify: subject + action + camera + style + mood

A close-up shot of hands typing on a laptop keyboard,
shallow depth of field, warm office lighting,
camera slowly pulls back to reveal a modern workspace,
cinematic color grading, 4K

Common mistakes:

• Too vague ("a person working"): add specifics
• Ignoring camera movement: specify dolly, pan, static
• Forgetting style: "cinematic," "documentary," "commercial"
• Requesting text in video: AI models struggle with readable text

For detailed prompting guides: See references/ai-video-prompting.md

AI Generation vs. Stock Evaluation

AI Avatars

Create talking-head videos without filming. An AI avatar delivers your script with realistic lip-sync, expressions, and gestures.

Avatar tool evaluation

HeyGen is one possible avatar platform, not a guaranteed or preferred integration. Before naming it or another vendor, verify current official documentation, authenticated access, callable API or connector availability, plan limits, price, output rights, body-motion and script-ingestion controls, localization and export requirements, and the consent requirements for every voice or likeness involved.

If no avatar tool is currently callable and authorized, provide a manual vendor-neutral workflow: approved script, consent record, user-operated upload, export checklist, and a real-camera or voiceover fallback.

Possible fit to test: product explainers, feature announcements, multilingual versions, and approved personalized outreach.

Avatar vs. Other-Approach Test