--- name: review-video description: Review a Remotion video with AI vision. Starts with a cheap local check of rendered still frames, then has TwelveLabs watch the full render and score it against a JSON rubric (pacing, composition, text legibility, audio sync and more) with timestamped fixes, applies the fixes and re-reviews. The feedback loop that closes the production circle. --- # Review Video โ€” AI-Powered Video Feedback Loop You are reviewing a Remotion video and providing professional feedback: first from a few rendered frames, then by having TwelveLabs "watch" the full render. This closes the production loop โ€” preview, review, improve, repeat. **Load the `remotion-production` skill** for the `video-analysis` rule. Rendering follows the official `remotion-render` skill. **Rendering is allowed here.** Invoking `/review-video` is an explicit request to render for review, so you don't need to ask again. ## Workflow ### 1. Quick Frame Check (cheap, local) Before uploading anything, render a handful of still frames and look at them yourself, as official `remotion-render` shows: ```bash npx remotion render [CompositionId] out/review-frames --frames=0,45,90,150,240 --image-format=png ``` Pick frames that cover the hook, each scene's midpoint, the busiest moments (captions, overlays) and the last frame. Read the PNGs and check: - Blank or empty frames, missing assets (a missing `staticFile()` shows as nothing or an error) - Text readability, overflow and safe areas (official `remotion-create/video-layout.md`) - Caption placement against the platform UI (the `captions-workflow` rule) If these frames show obvious bugs, fix them first (see step 6) and repeat this step. That's much cheaper than a full render plus a TwelveLabs upload. ### 2. Render the Full Video Look for an existing render: ```bash ls -t out/ 2>/dev/null | grep -E '\.(mp4|webm|mov)$' ``` If there's none, or the code changed since it was made, render it now: ```bash npx remotion render [CompositionId] out/video.mp4 ``` ### 3. Upload the Render to TwelveLabs ``` create-asset: file: [absolute path to the render, e.g. /path/to/project/out/video.mp4] ``` Keep the returned asset ID. No index is needed. If the analyse call says the asset isn't ready, wait a few seconds and retry. ### 4. Analyze โ€” The Director's Review Run **one** `sync-analyse-video` call that returns the whole review as JSON (renders over 1 hour: `async-analyse-video` with the same `prompt` and `jsonSchema`, then poll `get-analyse-task`): ``` sync-analyse-video: assetId: [asset ID] modelName: "pegasus1.5" temperature: 0.2 prompt: "You are a video director reviewing a [duration]s [platform] video at [WxH]. Intent: [one-line brief]. Script: [narration, per scene]. Score each dimension 1-10 and list concrete fixes with timestamps in seconds. Check: framing and composition; whether on-screen text is readable and on screen long enough; transitions; blank, frozen or glitchy frames; pacing (scenes too long or too short); whether the voiceover matches what's on screen; SFX timing; music mood and level under the voice; whether the first 3 seconds hook; whether the CTA is clear." jsonSchema: [the rubric below] ``` Always pass `modelName: "pegasus1.5"`: the server's default model has been removed from the API. **Rubric (`jsonSchema`):** ```json { "type": "object", "properties": { "overall_score": { "type": "integer", "description": "1-10" }, "scores": { "type": "object", "properties": { "hook": { "type": "integer", "description": "1-10, first 3 seconds" }, "pacing": { "type": "integer", "description": "1-10" }, "composition": { "type": "integer", "description": "1-10, framing and layout" }, "text_legibility": { "type": "integer", "description": "1-10, size, contrast, time on screen" }, "transitions": { "type": "integer", "description": "1-10" }, "audio_sync": { "type": "integer", "description": "1-10, voiceover and SFX against visuals" }, "audio_mix": { "type": "integer", "description": "1-10, voice clarity, music level" }, "cta": { "type": "integer", "description": "1-10, clarity of the ending" } }, "required": ["hook", "pacing", "composition", "text_legibility", "transitions", "audio_sync", "audio_mix", "cta"] }, "working": { "type": "array", "items": { "type": "string" } }, "fixes": { "type": "array", "items": { "type": "object", "properties": { "start": { "type": "number", "description": "seconds" }, "end": { "type": "number", "description": "seconds" }, "dimension": { "type": "string", "enum": ["hook", "pacing", "composition", "text_legibility", "transitions", "audio_sync", "audio_mix", "cta", "glitch"] }, "severity": { "type": "string", "enum": ["critical", "major", "minor"] }, "issue": { "type": "string" }, "fix": { "type": "string" } }, "required": ["start", "end", "dimension", "severity", "issue", "fix"] } }, "priority_fix": { "type": "string" } }, "required": ["overall_score", "scores", "working", "fixes", "priority_fix"] } ``` Save the JSON (e.g. `out/review-1.json`) so the next pass can be compared with this one, then clean up: ``` delete-asset: assetId: [asset ID] ``` Every review uploads a new asset, and assets count against the account's storage. To look closer at one stretch (say a fix at 12-18 s), run `sync-analyse-video` again with `startTime`/`endTime` around it (the window must be at least 4 s) before deleting the asset. ### 5. Present the Review Format the JSON as a professional director's review. Convert each fix's timestamps to frames (`Math.round(seconds * fps)`) and name the scene it falls in, so the fix points at code: ``` ๐ŸŽฌ Video Review: [filename] Duration: [X]s | Resolution: [WxH] ๐Ÿ“Š Overall Score: [overall_score]/10 Hook [x] ยท Pacing [x] ยท Composition [x] ยท Text [x] ยท Transitions [x] ยท Audio sync [x] ยท Mix [x] ยท CTA [x] โœ… What's Working: - [working[0]] - [working[1]] โš ๏ธ Improvements Needed (by severity): 1. [CRITICAL] [start]-[end]s (frames [a]-[b], [scene]) [issue] โ†’ [fix] 2. [MAJOR] ... 3. [MINOR] ... ๐ŸŽฏ Priority Fix: [priority_fix] ๐Ÿ”„ Next Steps: - [ ] [actionable task 1] - [ ] [actionable task 2] - [ ] [actionable task 3] Then run /review-video again. ``` Cross-check the AI review against your own frame check from step 1; if they disagree on something visible, trust the frames and say so. ### 6. Implement Fixes Ask the user if they want to apply the suggested fixes. If yes: 1. **Preserve user changes.** Re-read the files before editing. If the user changed the code or edited things in Studio since the last turn, keep their edits and apply the fixes on top; ask if a fix would undo one of them. 2. Make the code changes, critical and major first 3. Check them in Studio (`npx remotion studio`, or `--no-open` with an in-app browser; open the URL it prints). Studio stays open while you iterate. 4. Re-render (step 2) and re-review (steps 1-5) to verify the improvements, comparing the new scores with the saved JSON ### 7. Iteration Loop Keep iterating until the user is satisfied or the review shows no major issues. The loop: **Frame check โ†’ Render โ†’ Upload โ†’ Analyse with the rubric โ†’ Delete asset โ†’ Fix (in Studio) โ†’ Re-render โ†’ repeat** until quality is right. ## Review Checklist For each review, check these items: **Visuals:** - [ ] No blank/empty frames - [ ] Text is readable at target resolution - [ ] Colors are consistent throughout - [ ] Animations are smooth (no stuttering) - [ ] Images/footage are high quality (not pixelated) **Audio:** - [ ] Voiceover is clear and audible - [ ] Music volume doesn't overpower voice - [ ] Sound effects are timed correctly - [ ] No audio clipping or distortion - [ ] Fade in/out at start and end **Structure:** - [ ] Strong opening hook (first 2-3 seconds) - [ ] Clear narrative flow - [ ] Appropriate pacing for platform/audience - [ ] Clean ending with CTA (if applicable) - [ ] Total duration matches target **Technical:** - [ ] Correct aspect ratio (16:9 or 9:16) - [ ] Correct FPS (30 or 60) - [ ] File size reasonable for target platform - [ ] No rendering artifacts