Qcut Toolkit

QCut Toolkit

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

Voiceover Policy

Finished narration must use ByteDance Seed Audio through QCut:

bun run pipeline gen tts -m seed_audio -t "<directed narration>" \
  --audio-format mp3 --sample-rate 48000

• Route voiceover generation to ai-content-pipeline; promo-specific timing and mixing rules live in qcut-shot and qcut-cityfilm.
• Never ship macOS say, Windows SAPI, espeak, or another operating-system voice. System TTS may only create a temporary timing placeholder.
• If Seed Audio or its provider credentials are unavailable, fail explicitly and keep the previous deliverable unchanged. Do not silently fall back to system TTS.

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. qcut-vlog — Talking-Head Edit & Publishing Package

When: Turning talking-head/vlog footage into a verified social-ready edit and publishing package: clean baseline, restrained sticker/SFX variant, rights-aware B-roll version, Xiaohongshu copy, and a 9:16 cover Invoke: /qcut-vlog Skill path: .claude/skills/qcut-toolkit/qcut-vlog/SKILL.md

Handles:

• Word-level transcription for filler, stutter, and silence decisions
• Non-destructive FFmpeg trim/concat with retained cut metadata
• Shared QCut portrait filters and restrained skin smoothing through the native CLI
• Person cutout and still-image background replacement through the native CLI
• Post-cut retranscription so subtitle timing cannot drift
• Editable MP4 plus sidecar SRT, alongside a hard-captioned publishing MP4
• Sticker/SFX variant with a semantic cue sheet and a preserved audio master
• B-roll research with license archiving, FFmpeg 8 color preflight, and boundary checks
• Xiaohongshu titles, body copy, hashtags, and an exact 1080×1920 cover
• Safe resume based on artifact dependency timestamps

3. qcut-cityfilm — Reference-Driven City / Promo Films

When: Reproducing the structure and feel of a reference city, travel, or promo film with your own or licensed footage, including multi-language narration Invoke: /qcut-cityfilm Skill path: .claude/skills/qcut-toolkit/qcut-cityfilm/SKILL.md

Handles:

• Reference breakdown: contact sheets, transcript, and scene-cut pacing profile
• Shot-language inventory turned into licensed-footage search queries with attribution manifest
• Segment picking against per-act target shot lengths
• Per-act emotional narration through Seed Audio, one pass per language
• QCut project assembly (import, timeline, subtitles, export) via the editor CLI
• Final audio bed mixed outside the editor: ambience, segmented music, ducked narration
• Level and frame verification of the exported file, not just the timeline

4. 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

5. 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

6. 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

7. 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

8. ipad-cli — Real iPad & Simulator Automation

When: Installing on iPad, testing on iPad, taking iPad screenshots, running E2E device tests, sending CLI commands to the iPad app Invoke: /ipad-cli Skill path: .claude/skills/qcut-toolkit/ipad-cli/SKILL.md

Handles:

• Building, deploying, and launching QCut on real iPad or simulator
• Sending deep link commands via Darwin notifications (real device) or simctl openurl (simulator)
• Taking screenshots remotely (pymobiledevice3 tunnel for device, simctl io for simulator)
• E2E testing: navigate to editor, trigger exports, check state, FPS benchmarks
• Managing pymobiledevice3 tunnels for advanced device access

9. jianying-reference — Jianying Effect Reverse-Engineering

When: Matching a QCut effect to Jianying's (剪映) behavior, finding out exactly how a Jianying text animation / filter / transition is implemented, harvesting its effect-package source, capturing stepped reference frames Invoke: /jianying-reference Skill path: .claude/skills/qcut-toolkit/jianying-reference/SKILL.md

Handles:

• Mapping a Jianying effect card to its on-disk package via mtime markers
• Reading TextAnim.lua / Transform.lua tweens for exact easing, distances, and per-character timing
• Node-graph (lsproj/lsanim) parameter extraction where the Lua tier is absent
• Stepped-frame capture protocol in the Jianying UI (playhead anchoring, preview-contamination checks)
• Porting the math into editor-core presets and locking it with frame-parity tests

10. 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. Use the dedicated vlog flow — Route talking-head cleanup through qcut-vlog instead of manually chaining generic tools
3. Process with FFmpeg — Convert, trim, or prepare other source media
4. Generate with AI — Create new content or analyze existing media
5. Write prompts — Generate video prompts for Seedance/即梦 if needed
6. Control editor — Use native-cli editor:* commands to update timeline, settings, or import results
7. 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.