MCPInstall

video-production

Plan and route programmable or automated video production across code-first, template-first, and hybrid content pipelines. Use when the user needs repeatable video generation, branded short-form content, personalized videos, social clip batches, captioned/localized variants, video APIs, or video creation from data and templates — even if they only say video production. Also the direct owner of explicit Remotion requests (React video compositions, scenes, render workers) and of the retired remotion-video-production name. Triggers on: Remotion, Remotion render pipeline, React video composition, programmatic video, automated video creation, video API, personalized video, render videos from code. Route conversational raw video editing to video-use, long-form video clipping and speaker-tracking to autoclip, and one-click topic-to-video generation to moneyprinter-turbo.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/akillness/jeo-skills --skill video-production
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads video-production automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Video Production

Use this skill as the canonical programmable-video and automated-video production anchor for the repository.

The job is not to dump a generic storyboard or act like a manual editor tutorial. The job is to:

  1. normalize the production request,
  2. choose the best production mode,
  3. return one implementation-ready packet,
  4. leave explicit asset, QA, and handoff guidance.

Read references/production-modes.md, references/asset-and-qa-checklist.md, and references/handoff-boundaries.md before routing broad requests.

When to use this skill

  • The user wants automated, repeatable, or template-driven video production
  • The request involves short-form content ops, campaign variants, personalized videos, localized versions, or batched social assets
  • The user mentions Remotion, rendering from code, video APIs, templates, or connecting app/product data into video output
  • The workflow needs a production plan that can span generation, asset prep, QA, and a publishing handoff

When not to use this skill

  • Conversational raw footage editing with coding agents (cutting filler words, auto color grading, audio fades, animation overlays) → use video-use
  • Extracting highlights from long-form video into vertical 9:16 clips with speaker tracking & animated captions → use autoclip
  • Generating short-form videos from scratch using a topic/keyword with stock media and TTS → use moneyprinter-turbo
  • Cinematic product launch promo videos with Remotion 2.5D camera recipe cards → use video-shotcraft
  • Offline video compression, trimming, or format conversion without programmable code → use compresso
  • The job is purely a one-off manual edit in Premiere / After Effects / CapCut with no automation or repeatability goal
  • The task is only final creative polish, color, taste-based pacing, or bespoke motion-design critique
  • The user needs only transcript cleanup, clip selection, or direct publishing with no template/render layer
  • The request is really an ad-strategy, content-strategy, or product-launch brief rather than a video-production workflow

Supported production modes

Use these as routing targets inside the skill:

1) Code-first programmable video

  • Best when the user explicitly wants Remotion, React-based composition, dynamic data injection, or custom product-integrated rendering
  • Default stack: Remotion

2) Template/API automation

  • Best when the user needs speed, bulk generation, localization, or personalized variants without owning a full rendering codebase
  • Typical comparators: Shotstack, Creatomate, Bannerbear

3) Hybrid clip / repurposing pipeline

  • Best when the source material is long-form audio/video and the main problem is extracting, captioning, resizing, and packaging clips at volume
  • Common workflow shape: transcript or clip-selection tool + template/render layer + manual QA

4) Manual-finish hybrid

  • Best when automated generation exists but editorial polish, captions, timing, or final approvals still need a human pass
  • Use this when the right answer is not “fully automate everything” but “automate the repeatable 80%, then define the last-mile edit pass"

Instructions

Step 1: Normalize the production brief

Capture the request in this form before choosing a mode:

video_brief:
  objective: launch | onboarding | social-clips | personalization | recap | education | ads | unknown
  primary_output: mp4 | shorts | reels | stories | multiple
  audience:
    segment: "who will watch this"
    stage: unaware | evaluating | customer | community | mixed | unknown
  source_material:
    type: script | existing-video | screenshots | product-data | slides | mixed | unknown
    assets_available:
      - logo
      - footage
      - screenshots
      - captions
      - brand-guidelines
  scale:
    volume: one-off | recurring | batch | personalized
    variants:
      - language
      - aspect-ratio
      - audience-segment
  constraints:
    stack_preference: remotion | api-platform | mixed | unknown
    timeline: immediate | this-week | this-month | longer
    quality_bar: draft-fast | production-ready | polished-final
  main_question: "what does the user need next?"

If the brief is incomplete, continue with explicit assumptions rather than stalling.

Step 2: Pick exactly one primary production mode

Choose the single mode that reduces ambiguity fastest.

  • Code-first programmable video when the user explicitly wants Remotion, full code control, or deep app/data integration
  • Template/API automation when speed, scale, or no-code / low-code batch generation matters most
  • Hybrid clip / repurposing pipeline when the source is existing long-form media and the main job is repeatable short-form extraction
  • Manual-finish hybrid when automation is useful but the real risk sits in last-mile captions, timing, approval, or platform-native polish

If more than one mode fits, choose the mode that best defines the next artifact and name the secondary handoff.

Step 3: Return one implementation-ready packet

Return one of these packet types:

  • video-production brief
  • render-stack recommendation
  • asset + template packet
  • repurposing workflow packet
  • QA + handoff checklist

Do not emit multiple half-built plans. Choose the single most useful packet for the ask.

Step 4: Add explicit asset, QA, and handoff logic

Every output must include:

  • the chosen production mode,
  • the recommended stack or workflow shape,
  • the minimum required assets,
  • the main QA risks,
  • the next handoff after generation (manual polish, approval, publishing, analytics, etc.).

Step 5: Handle Remotion explicitly when relevant

If the user names Remotion or clearly needs code-first composition:

  • say that the request fits the code-first programmable video mode,
  • structure the output around Remotion scenes/templates/components/rendering,
  • read references/remotion-route-outs.md and route back to a template/API, repurposing, or manual-finish mode when the Remotion naming hides a better fit.

Step 6: Use this output structure

# Video Production Brief

## Scope
- Objective: ...
- Primary output: ...
- Audience: ...
- Source material: ...
- Confidence: high | medium | low

## Chosen mode
- Code-first programmable video | Template/API automation | Hybrid clip / repurposing pipeline | Manual-finish hybrid

## Recommended workflow
- Stack / workflow shape: ...
- Why this mode fits: ...
- What to avoid: ...

## Minimum asset packet
| Asset | Required | Notes |
|-------|----------|-------|
| ... | yes/no | ... |

## Build plan
1. ...
2. ...
3. ...

## QA risks
- ...
- ...

## Handoffs
- Next owner / tool / workflow: ...
- Why: ...

## Success check
- Render / approval / publishing signal: ...

Output format

Always return a short operator-style video production brief.

Required qualities:

  • one primary production mode,
  • clear asset minimums,
  • explicit QA / last-mile risks,
  • concrete next artifact and handoff,
  • assumptions called out when context is missing.

Examples

Example 1: personalized campaign videos

Input

We need to generate personalized customer recap videos from product data and render hundreds every week.

Output sketch

  • Primary mode: Template/API automation
  • Packet: render-stack recommendation
  • Notes dynamic data, template ownership, localization/QA, and publishing handoff

Example 2: explicit Remotion ask

Input

Build a Remotion workflow for a branded onboarding video with screenshots, captions, and 16:9 + 9:16 variants.

Output sketch

  • Primary mode: Code-first programmable video
  • Packet: asset + template packet
  • Uses scenes/components/rendering language and mentions variant strategy

Example 3: repurposing long-form content

Input

Turn our webinar recordings into short captioned clips for Shorts and Reels every week.

Output sketch

  • Primary mode: Hybrid clip / repurposing pipeline
  • Packet: repurposing workflow packet
  • Names transcript/clip selection, caption QA, safe-area checks, and final publish handoff

Best practices

  1. Separate the scalable generation layer from the last-mile editorial polish layer.
  2. Treat captions, safe areas, and aspect-ratio variants as first-class planning items, not afterthoughts.
  3. Choose the simplest stack that meets the repeatability requirement.
  4. Preserve a reusable asset/template packet so future variants are cheaper.
  5. Make the QA checklist explicit whenever short-form/social distribution is involved.

References

  • references/production-modes.md
  • references/asset-and-qa-checklist.md
  • references/handoff-boundaries.md
  • references/remotion-route-outs.md

FAQ

What does the video-production skill do?

Plan and route programmable or automated video production across code-first, template-first, and hybrid content pipelines. Use when the user needs repeatable video generation, branded short-form content, personalized videos, social clip batches, captioned/localized variants, video APIs, or video creation from data and templates — even if they only say video production. Also the direct owner of explicit Remotion requests (React video compositions, scenes, render workers) and of the retired remotion-video-production name. Triggers on: Remotion, Remotion render pipeline, React video composition, programmatic video, automated video creation, video API, personalized video, render videos from code. Route conversational raw video editing to video-use, long-form video clipping and speaker-tracking to autoclip, and one-click topic-to-video generation to moneyprinter-turbo.

How do I install video-production?

Run npx skills add https://github.com/akillness/jeo-skills --skill video-production in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/video-production/ (personal) or .claude/skills/video-production/ (project).

Which AI agents can use video-production?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is video-production safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains video-production?

It is published by akillness in akillness/jeo-skills. It has 505 recorded installs.

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