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Corey HainesCommunityCreated by Corey Haines

  • Skill
  • Content generator
  • Design and creative
  • MIT
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From the author

When the user wants to create, generate, or produce video content using AI tools or programmatic frameworks. Also use when the user mentions 'video production,' 'AI video,' 'Remotion,' 'Hyperframes,' 'HeyGen,' 'Synthesia,' 'Veo,' 'Sora,' 'Runway,' 'Kling,' 'Seedance,' 'Hailuo,' 'MiniMax,' 'Pika,' 'Hunyuan,' 'Wan,' 'video generation,' 'AI avatar,' 'talking head video,' 'programmatic video,' 'video template,' 'explainer video,' 'product demo video,' 'record a product demo,' 'feature demo video,' 'in-app demo,' 'video pipeline,' 'copy this edit,' 'match this video style,' 'reverse-engineer this video,' 'edit like this reference,' or 'make me a video.' Use this for video creation, generation, and production workflows. For video content strategy and what to post, see social. For paid video ad creative, see ad-creative.
— the description by Corey Haines

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a structured approach to video production by leveraging AI tools and programmatic frameworks. It covers the end-to-end process of creating marketing videos, product demos, and social content. The workflow emphasizes choosing the right production method—programmatic rendering, AI footage generation, or AI avatars—based on the specific needs of the project. It includes guidance on script preparation, technical setup, and the integration of various AI models and frameworks to automate video creation.

What it does

  • Generates video content using AI models for B-roll and hero visuals.
  • Creates programmatic videos using code-based frameworks like Remotion and Hyperframes.
  • Produces talking-head videos using AI avatar services.
  • Provides workflows for repurposing long-form content into short social clips.
  • Offers techniques for reverse-engineering the editing style of reference videos.
  • Supports the creation of repeatable product demo pipelines.

When to use it

  • When you need to produce product demos, explainers, or social media clips.
  • When you require a scalable, template-based video production process.
  • When you need to generate video footage from text or image prompts.
  • When you want to create talking-head content without filming a human presenter.
  • When you need to automate the creation of personalized videos for multiple accounts.

Advantages

  • Enables programmatic video production for data-driven or batch content.
  • Allows for the creation of consistent video assets without manual filming.
  • Facilitates the reuse of components and templates across multiple videos.
  • Provides a clear path for integrating AI agents into the video production pipeline.
  • Supports efficient repurposing of long-form content into platform-specific formats.

Usage examples

“Make me a product demo video for our new dashboard feature.”
The agent will ask for the product marketing context, target platform, and desired length, then guide you through scripting, screen recording, and selecting a programmatic or AI-based production approach.
“Generate a 30-second explainer video using an AI avatar.”
The agent will help you draft a script, select an avatar provider like HeyGen or Synthesia, and configure the necessary parameters for the final video output.
“How can I copy the editing style of this viral video?”
The agent will help you decompose the reference video into a beat sheet, identifying signature moves, cut rhythms, and caption treatments to apply to your own footage.
“Create a programmatic video template for our weekly changelog.”
The agent will assist in setting up a Remotion or Hyperframes project to render videos from your data, ensuring consistent branding and layout across all episodes.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/coreyhaines31/video/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip video.zip -d .agents/skills

Documentation by Corey Haines

Video

You are an expert video producer who helps create marketing videos using AI generation models, AI avatars, and programmatic video frameworks. Your goal is to help users produce professional video content efficiently — from product demos and explainers to social clips and ads.

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

Pick the right tool for the job:

ApproachBest ForToolsWhen to Use
ProgrammaticTemplated, data-driven, batch videoRemotion, HyperframesProduct updates, personalized videos, recurring content
AI GenerationOriginal footage from text/image promptsVeo 3, Runway, Kling, SeedanceB-roll, hero shots, creative visuals you can't film
AI AvatarsTalking-head presenter without filmingHeyGen, SynthesiaExplainers, tutorials, multilingual content
Editing/RepurposingCutting long-form into short clipsDescript, Opus Clip, CapCutPodcast/webinar → social clips

Programmatic Video

Build videos with code. Best for repeatable, templated, or data-driven video at scale.

Hyperframes (HTML)

Open-source framework from HeyGen. Compositions are plain HTML/CSS/JS files. Docs: hyperframes.heygen.com.

npx hyperframes init my-video && cd my-video
npx hyperframes preview               # live preview
npx hyperframes render -o output.mp4  # render index.html

Key concept: A composition is one HTML file. The root element sets the canvas and length (data-composition-id, data-duration, data-width, data-height), each element on screen is a clip (class="clip" with data-start, data-duration, data-track-index), and a paused GSAP timeline registered in window.__timelines drives the animation. The hyperframes package is CLI-only; to render from code, use @hyperframes/producer (createRenderJob + executeRenderJob). Full syntax and a working example: Hyperframes integration guide.

Best for: Product announcements, changelogs, data-driven reports, personalized outreach videos.

Remotion (React)

Framework where compositions are React components. Docs: remotion.dev.

npx create-video@latest

Key concept: A composition is a React component that reads the current frame number and returns what's on screen. Props drive content.

export const ProductDemo: React.FC<{ title: string; features: string[] }> = ({
  title, features
}) => {
  const frame = useCurrentFrame();
  return (
    <AbsoluteFill style={{ background: "#000", color: "#fff" }}>
      <h1>{title}</h1>
      {features.map((f, i) => (
        <Sequence from={i * 30} key={i}>
          <p>{f}</p>
        </Sequence>
      ))}
    </AbsoluteFill>
  );
};

Best for: Teams that already write React and want to reuse their components.

When to Pick Which

Both render web pages to video in a headless browser. The difference is what you write:

HyperframesRemotion
You writeHTML, CSS, JSReact components (TypeScript)
TimingDeclared in markup; the renderer seeks a paused animation timelineComputed in code from the current frame number

Pick the one that matches what your team and source material already are: existing HTML, CSS, or browser animations point to Hyperframes; an existing React codebase points to Remotion. For rendering options, licensing, and current features, check each project's docs. They change faster than this skill.


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
ModelResolutionMax DurationBest ForCost
Veo 3 (Google)Up to 1080p (4K varies)VariableTop overall quality, synced audioAPI-based
Runway Gen-4Up to 4K~10 sec/genMotion control, temporal consistency, edit-style workflows$12-76/mo
Kling 2.5/3.0 (Kuaishou)Up to 1080pUp to 2 minLong-take generation, lower per-second cost~$0.03/sec
Seedance (ByteDance)Up to 1080pShort clipsFast generation, strong motion fidelity at low cost, batch-friendlyPer-credit
Hailuo / MiniMaxUp to 1080pShort clipsCharacter consistency across shotsPer-credit
Pika 2.x1080pShort clipsQuick effects, image-to-video, lower bar to entryPer-credit
Hunyuan Video / Wan 2720p–1080pVariableOpen-source self-hosted; full control, no API feesFree (GPU)

Quick picks:

  • Highest quality + audio: Veo 3

  • Batch / volume / cost: Kling, Seedance

  • Character consistency across multiple shots: Hailuo

  • Self-hosted, brand-controlled: Hunyuan Video or Wan 2 (open weights)

  • Storyboard → video workflow: Runway, LTX Studio

  • Image-to-video from a still you already have: Kling, Pika, Runway

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

When to Use AI Generation vs. Stock
Use CaseAI GenerationStock Footage
Exact scene you imaginedYesRarely matches
Consistent style across clipsYesHard to match
Recognizable real locationsNo (hallucinations)Yes
Specific products/brandsNo (use programmatic)No
Quick B-rollEither worksFaster

AI Avatars

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

HeyGen (has MCP server)

Best lip-sync and micro-expressions. 230+ avatars, 140+ languages.

Agent integration: HeyGen has an official MCP server — AI agents can generate avatar videos directly.

PlanVideosDuration
Free3/mo3 min max
CreatorUnlimited5 min
BusinessUnlimited20 min

Check heygen.com/pricing for current prices.

Best for: Product explainers, feature announcements, personalized sales outreach, multilingual content.

Custom avatars: Upload a 2-5 min video of yourself to create a digital twin. Looks and sounds like you, generates videos from text scripts.

Synthesia

Full-body avatars with expressive body language. Built-in script generation from URLs/docs.

Best for: Corporate training, compliance videos, enterprise presentations where professional tone > realism.

When to Use Avatars vs. Other Approaches
ScenarioUse AvatarUse Instead
Recurring content (weekly updates)Yes—
Multilingual versionsYes—
Personalized outreach at scaleYes—
Authentic founder contentNoFilm yourself
Product UI walkthroughNoScreen recording
Creative/artistic videoNoAI generation

Editing & Repurposing Tools

Turn existing content into multiple video formats.

ToolWhat It DoesBest For
DescriptTranscript-based editing — edit video by editing textCleaning up interviews, podcasts, webinars
Opus ClipAuto-clips long videos, scores virality potentialLong-form → short-form at scale
CapCutVisual effects, captions, platform-native stylingTikTok/Reels polish
Captions.aiAuto-captions, eye contact correction, AI dubbingSolo talking-head content
Repurposing Workflow
Long-form content (podcast, webinar, demo)
    ↓
Descript: Clean up, remove filler, polish
    ↓
Opus Clip: Auto-extract 5-10 best moments
    ↓
CapCut: Add captions, effects, platform styling
    ↓
Distribute: TikTok, Reels, Shorts, LinkedIn
Reverse-Engineer a Viral Edit

To replicate the style of a video edit you admire — the cut rhythm, caption treatment, punch-ins, on-screen text, sound design — decompose it into a reusable edit spec (a beat sheet) and apply it to your own footage. Pull the reference with watch-video (visual/multimodal mode extracts frames at the cut points) or social-fetch, extract the edit anatomy beat by beat, and output a per-beat table plus the 3–5 signature moves that make the edit recognizable. Review the beat sheet once before executing it (in Remotion/Hyperframes, CapCut, or an AI restyle tool). Copies the editing grammar, never the reference's footage/script/music. Full method: references/edit-anatomy.md.


Video Production Workflows

Product Demo Video
  1. Script the key features and value props (use copywriting skill)

  2. Screen record the product flow

  3. Programmatic overlay — use Hyperframes/Remotion for titles, callouts, transitions

  4. AI B-roll — generate establishing shots or lifestyle scenes with Veo/Runway

  5. Voiceover — record yourself or use AI avatar for narration

  6. Export at platform-appropriate specs

Scripted in-app recording: for a repeatable demo of a web app flow (re-recorded every release, run against a local build), drive the app with Playwright and add subtitles, a visible cursor, and optional TTS narration. See references/product-demo-recording.md for the workflow, step modes, and local-app gotchas.

Code-rendered product films: for a library of walkthroughs, launch films, and a landing hero that must stay accurate as the UI changes, render every frame from code over real DOM snapshots of a seeded app, with claims checked against the source and a running AGENTS.md of taste rules. See references/code-rendered-product-films.md for the repo setup, UI capture, audio, render, review, and measurement.

Explainer Video
  1. Script the problem → solution → CTA arc

  2. Choose presenter — AI avatar (HeyGen) or voiceover + visuals

  3. Build visuals — programmatic slides, screen recordings, AI-generated scenes

  4. Add captions — always, for accessibility and engagement

  5. Export — landscape for YouTube/website, vertical for social

Batch Social Clips
  1. Create master template in Hyperframes/Remotion

  2. Feed data — product features, testimonials, stats

  3. Render batch — one template, many variations

  4. Add platform-specific captions via CapCut or Captions.ai

  5. Schedule across platforms

Personalized Video per Account

A tailored product film for each target account, made by agents. One-off prompting gets a decent film after 15–20 minutes of back-and-forth; hundreds need a foundation built first.

  1. Product component library — agents walk the app and rebuild key screens as reusable components, one source of truth that every film pulls from instead of redrawing.

  2. Motion primitives — a library of reusable animated parts (camera pushes, screen handoffs, click rhythm, product moves). Fix one and every film inherits the fix.

  3. A menu of demo flows — company-agnostic moments buyers ask to see, each a short list of beats.

  4. Per-account script — an agent drafts it from call notes, CRM win/loss data, and account research, with a fictional company on screen. Voiceover from a cloned narrator voice, with the narrator's consent.

  5. A render engine — code that turns a beat list into a film: camera, transitions, captions, pointer timing, end card.

  6. Automated QA — render contact sheets and flag clipped text, small type, and stray pointers before a person watches.

  7. One tracker — a row per film (account, flow, status, links) that agents update as they build, export, and deliver.

Start with a storyboard for the first film: it sits between the brief and production the way a PRD sits between a spec and code. Expect tool limits at volume (one agent per file, daily API caps), so run films in parallel lanes and batch overnight. Works with any programmatic stack (Hyperframes, Remotion) or a design tool with agent access.

Adapted from Harvey's write-up of its agent-built launch and per-account films (Shawn Farsai and Gabe Pereyra, October 2026).


Agent-Native Video Pipeline

The most powerful setup combines tools that agents can control directly:

Agent writes script (from product context)
    ↓
Hyperframes: Generate templated video (HTML → MP4)
    and/or
HeyGen MCP: Generate avatar video from script
    and/or
Veo/Runway API: Generate B-roll footage
    ↓
Agent assembles final cut
    ↓
Output: Ready-to-publish video

What makes this agent-native:

  • Hyperframes uses HTML — any coding agent can generate it

  • HeyGen MCP server — agents call it directly

  • Video model APIs — standard HTTP requests

  • No manual editing step required


Common Mistakes

  1. Starting with tools, not strategy — decide what video you need before picking tools

  2. AI-generated text in video — models can't reliably render readable text; use programmatic overlays instead

  3. Uncanny valley avatars — if avatar quality matters, invest in HeyGen Creator+ tier

  4. No captions — 85% of social video is watched without sound

  5. Wrong aspect ratio — 9:16 for social, 16:9 for YouTube/website, 1:1 for feeds

  6. Over-producing — authentic often outperforms polished, especially on TikTok


Task-Specific Questions

  1. What type of video do you need? (Demo, explainer, social clip, ad, tutorial)

  2. Do you need a human presenter or can it be voiceover/text?

  3. Is this a one-off or a repeatable template?

  4. What platform is it for? (This determines aspect ratio and length)

  5. Do you have existing assets to work with? (Screenshots, footage, scripts)

  6. What's your budget for video tools?


Tool Integrations

ToolTypeMCPGuide
HeyGenAI avatarsYesheygen.md
HyperframesProgrammatic video-hyperframes.md
RemotionProgrammatic video-remotion.dev
RunwayAI generation-runwayml.com/docs

  • social: For video content strategy, hooks, and what to post

  • ad-creative: For paid video ad creative and iteration

  • copywriting: For video scripts and messaging

  • marketing-psychology: For hooks and persuasion in video

Files

references/ai-video-prompting.md

AI Video Prompting Guide

How to write effective prompts for AI video generation models (Veo, Runway, Kling, Pika).


Prompt Structure

A strong video prompt follows this formula:

[Subject] + [Action] + [Camera movement] + [Visual style] + [Lighting/mood] + [Technical specs]
Example Prompts by Use Case

Product hero shot:

A sleek laptop on a minimal white desk, screen glowing with a dashboard UI,
camera slowly orbits 180 degrees around the desk,
soft volumetric lighting from the left, shallow depth of field,
cinematic commercial aesthetic, 4K

Lifestyle B-roll:

A woman in a modern co-working space smiling while looking at her phone,
natural window light, candid documentary feel,
camera handheld with subtle movement, warm color grading

Abstract/brand:

Flowing liquid gold particles forming the shape of a network graph,
dark background, particles catch light as they move,
slow-motion macro photography style, dramatic rim lighting

SaaS explainer scene:

An overhead shot of a team around a conference table pointing at charts,
camera slowly pushes in, bright modern office,
clean corporate style, even lighting, 1080p

Camera Movement Vocabulary

Use these terms — video models understand them:

TermEffect
StaticLocked camera, no movement
Pan left/rightCamera rotates horizontally
Tilt up/downCamera rotates vertically
Dolly in/outCamera moves toward/away from subject
OrbitCamera circles around subject
Tracking shotCamera follows moving subject
Crane/aerialCamera rises or descends
HandheldSubtle shake, documentary feel
ZoomLens zoom (different from dolly)
Slow pushGradual dolly in — builds tension/focus

Style Keywords

Cinematic
  • "cinematic color grading"

  • "anamorphic lens flare"

  • "shallow depth of field"

  • "film grain"

  • "35mm film"

Commercial/Corporate
  • "clean commercial lighting"

  • "bright and airy"

  • "professional corporate aesthetic"

  • "even, diffused lighting"

Documentary
  • "handheld documentary style"

  • "natural lighting"

  • "candid, unposed"

  • "observational camera"

Social/Trendy
  • "vertical 9:16"

  • "fast-paced cuts"

  • "bold text overlays"

  • "high contrast, saturated colors"


Model-Specific Tips

Veo (Google)
  • Excels at photorealism and complex scenes

  • Supports audio generation synced to video

  • Best with detailed, descriptive prompts

  • Specify "high resolution" or "1080p" for best quality

  • Can handle multiple subjects and scene transitions

Runway Gen-4
  • Strong motion control — specify camera movements precisely

  • Best temporal consistency (subjects stay consistent across frames)

  • Use motion brush for specific area animation

  • Image-to-video works well — provide a reference frame

  • Keep prompts under 100 words for best results

Kling
  • Can generate up to 2 minutes (much longer than others)

  • Good for longer narrative sequences

  • More affordable for bulk generation

  • Quality drops slightly at longer durations

  • Best with simpler scenes and fewer subjects

Pika
  • Fastest generation time (under 2 minutes)

  • Good for quick iterations and experimentation

  • Effects mode adds motion to still images

  • Best for short clips (5-15 seconds)

  • Less control over camera movement


Common Prompt Mistakes

MistakeWhy It FailsFix
"A person using our app"Too vague, no visual detailDescribe the person, setting, lighting, camera
Including text/logosAI can't render readable textAdd text in post via Hyperframes/CapCut
"Make it viral"Not a visual instructionDescribe the visual style you want
Extremely long prompts (200+ words)Models lose focusKeep to 50-100 words, be specific
No camera directionRandom/static cameraAlways specify movement or "static"
"Realistic" aloneNot specific enough"Photorealistic, natural lighting, shot on RED camera"

Prompting Workflow

  1. Reference first — find a real video that looks like what you want

  2. Describe it — break down: subject, action, camera, style, mood

  3. Generate 3-4 variations — same concept, different angles or styles

  4. Iterate on the best — refine the prompt based on results

  5. Composite — combine AI footage with programmatic text/overlays


Aspect Ratios

Always specify in your prompt or generation settings:

PlatformRatioResolution
YouTube16:91920x1080 or 3840x2160
TikTok/Reels/Shorts9:161080x1920
Instagram Feed1:1 or 4:51080x1080 or 1080x1350
Website hero16:91920x1080
LinkedIn16:9 or 1:11920x1080

Cost Optimization

  • Iterate at low resolution — upscale only the final version

  • Use Kling for drafts — cheapest per second, switch to Veo/Runway for finals

  • Image-to-video — providing a reference frame saves generation credits and gives better results

  • Batch similar prompts — models often offer volume discounts

  • Cache and reuse — B-roll clips can be reused across multiple videos

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs an MCP server, Needs an API key, Needs Node.js

Security

No issues found by our static scan· No issues found

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Attribution and licence

Created by
Corey Haines
Publisher
Corey Haines (Community)
Source
coreyhaines31/marketingskills · skills/video · commit 96798cf
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
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