Skill detail
video-production
Plans and routes programmable or automated video production across code-first, template-first, and hybrid pipelines including Remotion.
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SKILL.md
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--- name: video-production description: > 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, batch-create shorts, render videos from code, repurpose content into clips. allowed-tools: Write Read WebSearch WebFetch Task compatibility: > Canonical programmable-video / automated-video skill for the repo and the single entry point for Remotion-named requests; the former `remotion-video-production` alias was merged here and is listed in `skills.json` retired_skills. metadata: tags: video, automation, remotion, short-form, content-ops, templates, react platforms: Claude, ChatGPT, Gemini, Codex version: "2.0" --- # 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/production-modes.md), [references/asset-and-qa-checklist.md](references/asset-and-qa-checklist.md), and [references/handoff-boundaries.md](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 - 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 producRead the full source on GitHub (opens external page)