review-cut — Gemini AI integration review-cut, resolve-mcp, community, Gemini AI integration, ide skills, video review automation, lightweight review export, AI-powered video feedback, review-cut install, Claude Code, Cursor

v1.0.0
GitHub

About this Skill

Ideal for Video Editing Agents seeking to automate review processes with AI-powered feedback review-cut is a skill that renders lightweight review exports and uploads them to Gemini for AI visual feedback, optionally saving the review file for client distribution.

Features

Renders lightweight review exports for efficient video review
Uploads review exports to Gemini for AI-powered visual feedback
Optionally saves review renders to disk for client distribution
Supports rendering with watermark text for client reviews
Provides specific feedback on pacing through Gemini integration

# Core Topics

jenkinsm13 jenkinsm13
[0]
[0]
Updated: 2/22/2026

Agent Capability Analysis

The review-cut skill by jenkinsm13 is an open-source community AI agent skill for Claude Code and other IDE workflows, helping agents execute tasks with better context, repeatability, and domain-specific guidance. Optimized for Gemini AI integration, video review automation, lightweight review export.

Ideal Agent Persona

Ideal for Video Editing Agents seeking to automate review processes with AI-powered feedback

Core Value

Empowers agents to render lightweight review exports, upload them to Gemini for AI visual feedback, and optionally save review files for client distribution, utilizing protocols like video rendering and upload APIs, and supporting file formats for review exports

Capabilities Granted for review-cut

Automating video review workflows
Generating AI-powered feedback on video pacing
Creating watermarked review copies for client distribution

! Prerequisites & Limits

  • Requires Gemini upload capability
  • Dependent on AI feedback availability
  • Optional save to disk functionality requires filesystem access
Labs Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

review-cut

Install review-cut, an AI agent skill for AI agent workflows and automation. Works with Claude Code, Cursor, and Windsurf with one-command setup.

SKILL.md
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/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:
    json
    1{ 2 "SelectAllFrames": true, 3 "FormatWidth": "1280", 4 "FormatHeight": "720", 5 "VideoQuality": "10000000" 6}
    (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.

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is review-cut?

Ideal for Video Editing Agents seeking to automate review processes with AI-powered feedback review-cut is a skill that renders lightweight review exports and uploads them to Gemini for AI visual feedback, optionally saving the review file for client distribution.

How do I install review-cut?

Run the command: npx killer-skills add jenkinsm13/resolve-mcp. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for review-cut?

Key use cases include: Automating video review workflows, Generating AI-powered feedback on video pacing, Creating watermarked review copies for client distribution.

Which IDEs are compatible with review-cut?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for review-cut?

Requires Gemini upload capability. Dependent on AI feedback availability. Optional save to disk functionality requires filesystem access.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add jenkinsm13/resolve-mcp. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use review-cut immediately in the current project.

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