QCut Toolkit

Unified entry point for QCut's six sub-skills. Route tasks to the appropriate sub-skill based on what the user needs.

Sub-Skills

1. native-cli — Project Setup & Native Pipeline Commands

When: Setting up a project, cleaning up files, organizing workspace, importing media Invoke: /native-cli Skill path: .claude/skills/native-cli/SKILL.md

Handles:

• Initializing the standard project layout (input/*, output/*, config/)
• Organizing media by extension with organize-project
• Running structure audits with structure-info
• Running editor media/timeline/export/diagnostic commands (editor:*)
• Running additional native pipeline commands when needed

2. ffmpeg-skill — Media Processing

When: Converting, compressing, trimming, resizing, extracting audio, adding subtitles, creating GIFs, applying effects Invoke: /ffmpeg-skill Skill path: .claude/skills/qcut-toolkit/ffmpeg-skill/SKILL.md

Handles:

• Format conversion (MP4, MKV, WebM, MP3, etc.)
• Video compression (-crf), resizing (scale=), trimming (-ss/-t)
• Audio extraction, subtitle burn-in, text overlays
• GIF creation, speed changes, merging/concatenation
• Streaming (HLS, DASH, RTMP) and complex filtergraphs

3. ai-content-pipeline — AI Content Generation & Analysis

When: Generating images/videos/avatars, transcribing audio, analyzing video, running AI pipelines Invoke: /ai-content-pipeline Skill path: .claude/skills/qcut-toolkit/ai-content-pipeline/SKILL.md

Handles:

• Text-to-image (FLUX, Imagen 4, Nano Banana Pro, GPT Image)
• Image-to-video (Veo 3, Sora 2, Kling, Hailuo)
• Avatar/lipsync generation (OmniHuman, Fabric, Multitalk)
• Speech-to-text transcription with word-level timestamps (Scribe v2)
• Video analysis with Gemini 3 Pro
• YAML pipeline orchestration with parallel execution
• Motion transfer between images and videos

4. seedance — Video Prompt Engineering

When: Writing video prompts, Seedance/即梦 workflows, AI video prompt generation, video descriptions (Chinese or English) Invoke: /seedance Skill path: .claude/skills/qcut-toolkit/seedance/SKILL.md

Handles:

• Seedance 2.0 (即梦) prompt generation in Chinese
• Multi-modal video prompts (text-to-video, image-to-video, video extension)
• Short drama (短剧), advertising video, and cinematic prompt templates
• Prompt engineering best practices for ByteDance video models

5. qcut-mcp-preview-test — MCP Preview Testing

When: Testing MCP app preview, toggling "MCP Media App" mode, debugging iframe rendering, troubleshooting mcp:app-html events or /api/claude/mcp/app Invoke: /qcut-mcp-preview-test Skill path: .claude/skills/qcut-toolkit/qcut-mcp-preview-test/SKILL.md

Handles:

• Switching preview panel between video preview and MCP app mode
• Validating iframe srcDoc rendering for MCP HTML content
• Debugging IPC (mcp:app-html) and HTTP (/api/claude/mcp/app) delivery
• Crafting prompts that modify MCP media app UI safely

6. pr-comments — PR Review Processing

When: Exporting PR comments, evaluating code reviews, fixing review feedback from CodeRabbit/Gemini bots Invoke: /pr-comments Skill path: .claude/skills/pr-comments/SKILL.md

Handles:

• Export review comments from GitHub PRs to markdown files
• Preprocess comments into evaluation task files
• Analyze comment groupings by source file
• Evaluate, fix, or reject individual review comments
• Batch process all comments with bottom-up line ordering
• Resolve threads on GitHub and track completed tasks

Routing Logic

When the user's request involves multiple sub-skills, chain them in this order:

1. Organize first — Ensure project structure exists before processing
2. Process with FFmpeg — Convert, trim, or prepare source media
3. Generate with AI — Create new content or analyze existing media
4. Write prompts — Generate video prompts for Seedance/即梦 if needed
5. Control editor — Use native-cli editor:* commands to update timeline, settings, or import results
6. Organize output — Place results in media/generated/ or output/

Quick Routing Table

Multi-Step Workflow Example

User: "Take my raw footage, trim the first 30 seconds, compress it, then generate AI thumbnails"

1. /native-cli — Run init-project / organize-project to prepare the project structure and source media
2. /ffmpeg-skill — ffmpeg -ss 00:00:30 -i input.mp4 -c copy trimmed.mp4 then compress
3. /ai-content-pipeline — Extract a frame, generate styled thumbnail with flux_dev
4. Place output in input/, output/, or media/generated/ as needed

Output Structure

All sub-skills follow the same project structure:

Documents/QCut/Projects/{project-name}/
├── input/              ← native-cli init-project / organize-project
│   ├── images/
│   ├── videos/
│   ├── audio/
│   ├── text/
│   └── pipelines/
├── output/             ← final exports
│   ├── images/
│   ├── videos/
│   └── audio/
├── config/
└── media/generated/    ← ai-content-pipeline outputs (when used)

Full Production Workflow

$ARGUMENTS

Break the request into steps, invoke each sub-skill in sequence, and report progress after each step. Always confirm destructive operations (overwriting files, deleting temp data) before executing.