review-cut

name	review-cut
description	Render a quick review cut with burned-in timecode and watermark, then feed it to Gemini so the AI can see the current state of the timeline and give editorial feedback.
disable-model-invocation	true

/review-cut — Review Cut + AI Visual Feedback

Render a lightweight review export, then upload it to Gemini so the AI can actually watch the timeline and give feedback. Optionally save the review file for sending to clients.

Arguments

• No arguments: render review, upload to Gemini, get AI feedback
• save to /path/: also save the review render to disk
• for client: render with watermark text (e.g., "REVIEW COPY — NOT FOR DISTRIBUTION")
• feedback on pacing: give Gemini a specific focus area

Workflow

1. Get timeline info

Use resolve_get_timeline_info to get the timeline name, duration, frame rate, and resolution.

2. Render a low-res review cut

Set up a lightweight render specifically for AI review and client screening:

• Use resolve_set_render_format_and_codec → MP4 / H.264
• Use resolve_set_render_settings with:

  {
    "SelectAllFrames": true,
    "FormatWidth": "1280",
    "FormatHeight": "720",
    "VideoQuality": "10000000"
  }
  

  (720p, low bitrate — fast to render, small enough to upload to Gemini)

Burned-in timecode: Check if a burn-in preset exists with resolve_get_render_presets. If there's one with "burn" or "timecode" in the name, load it. Otherwise, set render settings to enable data burn-in if the API supports it, or inform the user to enable it manually in the Deliver page.

Watermark: If the user requested for client, note that the watermark text should be set manually in Resolve's burn-in settings (the scripting API has limited burn-in control). Mention this to the user.

• Use resolve_add_render_job to queue
• Use resolve_start_render to begin
• Poll with resolve_get_render_status until complete

3. Upload to Gemini for visual analysis

This is the key differentiator — the AI actually watches the edit.

• Use resolve_analyze_timeline which uploads the timeline's source proxies to Gemini and runs a full editorial critique
• This gives Gemini visual context of what's actually on the timeline

If resolve_analyze_timeline is not available (no Gemini key), skip this step and just deliver the rendered file.

4. Return feedback

Combine the Gemini critique with practical next steps:

• Pacing notes — which sections drag, which feel rushed
• Cut quality — jump cuts, bad match cuts, continuity issues
• Audio — gaps in dialogue, music drops, levels
• Story — does the narrative track? Are the best moments featured?
• Technical — any obvious issues (black frames, flash frames, out-of-sync)

If the user specified a focus area (e.g., "feedback on pacing"), tell Gemini to prioritize that.

5. Save if requested

If the user asked to save, report the render output path. If they asked for client, remind them to verify the watermark/burn-in before sending.

Example Interactions

User: /review-cut → Render 720p H.264, run resolve_analyze_timeline for AI feedback, report critique.

User: /review-cut save to ~/Desktop/ → Same + save the rendered file.

User: /review-cut for client → Render with TC burn-in note about watermark, save for sending.

User: /review-cut feedback on pacing and music sync → Render, upload, ask Gemini to focus on pacing and music sync specifically.