Product Video Pipeline

Product Video Pipeline

Turn a product message, feature, or workflow into a video that is clear, truthful, platform-ready, and reproducible. Use a lightweight path for small requests and the bundled project contracts for substantial production.

What this helps people do

• Explain how a product works with a reproducible tutorial or walkthrough.
• Launch a product or feature with a concise, evidence-backed promo.
• Combine desire and proof in a hybrid demo.
• Adapt one story into horizontal, vertical, and social cutdowns.
• Audit or revise an existing video without rebuilding unaffected work.
• Package masters, captions, sources, rights notes, and QA evidence for handoff.

Typical user requests include:

• “Make a 45-second launch video for my app.”
• “Turn this screen recording into a clear tutorial.”
• “Write a script and asset checklist before we film.”
• “Create 16:9 and 9:16 versions of this product demo.”
• “Review this video for pacing, readability, factual accuracy, and delivery specs.”

Choose the smallest useful route

Do not force reference research, effects, After Effects, AIGC, or formal project files when they do not improve the requested result.

Core rules

1. Identify tutorial, promo, or hybrid and one primary audience outcome before locking the story.
2. Confirm the primary platform, aspect ratio, duration range, language, narration, and captions before format-dependent work.
3. Use real product UI, outputs, data, and approved claims as evidence. Never present simulated or generated material as factual proof.
4. Prefer verified project assets and user-provided originals over sourced or generated substitutes.
5. Treat references as inspiration: record what to transfer, transform, and exclude.
6. Check ownership, license, privacy, likeness, and voice permissions before using an asset.
7. Ask for explicit approval before costly or irreversible work such as final voice generation, paid assets, AIGC media, AE/3D builds, or master rendering.
8. Keep user decisions and approval text in project state for substantial work; invalidate only the downstream work affected by a change.

Quick start for substantial production

Resolve bundled paths relative to this SKILL.md, then initialize the project:

python3 -m pip install -r <skill-dir>/requirements.txt
python3 <skill-dir>/scripts/video_pipeline.py init <project-root>

This creates a non-destructive video-plan/ directory with reusable YAML contracts. Update them as decisions are made, then render readable boards:

python3 <skill-dir>/scripts/video_pipeline.py render <project-root>
python3 <skill-dir>/scripts/video_pipeline.py validate <project-root> --stage intake

For a lightweight script, checklist, revision, or QA request, work directly unless the user wants these project files.

Workflow

1. Define the audience result and delivery

Confirm:

• tutorial, promo, or hybrid;
• the audience and one intended result;
• platform, canvas, duration, language, narration, and captions;
• requested scope: plan, script, asset list, production, revision, or QA.

For hybrids, choose whether conversion or successful learning is dominant. Read references/guided-intake.md for adaptive questions and references/video-type-and-script.md for type-specific scripting.

2. Choose a reference route only when useful

For promos or visually ambitious work, ask whether the user wants to:

• provide references;
• authorize research;
• proceed with original directions and no external references.

Present a small, relevant set rather than a generic mood board. Separate whole-film references (story, pace, tone) from effect references (a specific transition, animation, or camera move). Record the originality delta and rights risk. Read references/reference-and-effects.md.

3. Write the script around truth and proof

For promos, offer 2–3 meaningfully different treatments before expanding the selected one. For tutorials, work backward from the result and define the visible success state of each step. For hybrids, move clearly from desire to proof to action.

Map every public claim:

claim → source truth → source asset → script unit → final timestamp

Remove unsupported claims, label them as concepts, or request real evidence.

4. Plan assets and responsibility

Create an asset checklist that states:

• what is required and why;
• who should provide or create it;
• technical specifications;
• status, rights, privacy, and fallback;
• whether generated media is allowed.

Do not silently replace an asset the user agreed to provide. Read references/asset-responsibility.md.

5. Select an implementation route

Choose tools by the job:

Load $remotion:remotion-best-practices before editing Remotion code.

If the user has an AE/template library and the shot truly benefits from it, index preview videos, shortlist candidates against exact script jobs, inspect the selected source package, and define a deterministic fallback. Read references/ae-library-selection.md. Otherwise record the AE route as none or deterministic_rebuild.

6. Confirm before full production

For full production, render a compact card covering the outcome, delivery format, script, references, implementation route, assets, permissions, gaps, risks, and fallbacks. Ask for explicit approval and preserve the exact text:

python3 <skill-dir>/scripts/video_pipeline.py authorize <project-root> \
  --approved-by user \
  --confirmation "<exact user text>"

Never manufacture approval or interpret silence as approval. A material change to the approved story, format, claim, source, rights scope, or generated-media policy requires renewed approval.

7. Produce, preview, and validate

For substantial work, follow:

G0 preproduction lock → G1 truth/originality → G2 assets → G3 film plan → G4 animatic → G5 build preflight → G6 preview → G7 master QA → G8 package

Review a low-cost animatic before expensive production. Keep film.yaml as the canonical timeline and generate downstream artifacts from it. Read references/production-gates-and-qa.md before production or final QA.

Validate at the relevant transitions:

python3 <skill-dir>/scripts/video_pipeline.py validate <project-root> --stage preproduction
python3 <skill-dir>/scripts/video_pipeline.py validate <project-root> --stage production
python3 <skill-dir>/scripts/video_pipeline.py validate <project-root> --stage delivery

Reference map

Completion

Match the deliverable to the request. A script-only task ends with an approved script; a QA task ends with evidence-backed findings. For full production, deliver the requested masters and variants plus captions, source/asset manifest, rights and privacy notes, QA report, hashes, reproduction command, and revision record.