| name | mtv-maker |
| version | 2.1.0 |
| description | Full end-to-end MTV music video creator. From a song concept and optional character reference photo, produces a complete cinematic MTV: (1) writes lyrics and generates music with ACE-Step, (2) generates cinematic scene images, (3) animates with I2V (Grok/Seedance), (4) assembles clips with audio and crossfade transitions, (5) transcribes audio for accurate lyric timing, (6) burns synced lyric subtitles + opening/ending credits with branding. Use when user says "make an MTV", "create a music video", "generate MTV", "/mtv", or describes a song they want turned into a full visual music video. |
MTV Maker v2 — I2V Pipeline
End-to-end pipeline: song concept + character photo → music (ACE-Step) → scene images (image_to_image) → I2V video clips (Grok/Seedance) → assembled MTV with synced bilingual lyrics + credits.
Inputs
The user provides:
- Song concept — genre, mood, style, voice, language, any reference artist/style
- Character reference photo (optional) — used for
image_to_image to generate consistent scene photos. If none provided, generate original scene images with text_to_image.
- MTV length preference — full song or chorus-only clip (default: 30-45s chorus clip)
Pipeline Mode
ALWAYS use I2V (image-to-video). NEVER use Ken Burns for MTV production — it looks cheap and static. Every scene must have real AI-generated motion.
| Mode | Description | Time | Quality |
|---|
| Photo + I2V | Photos animated by Grok or Seedance AI | ~45 min | Cinematic |
Phase Overview
| Phase | What | Tool/Skill | Output |
|---|
| 1 | Song creation | acestep skill | Full MP3 |
| 2 | Chorus extraction | ffmpeg | Trimmed MP3 clip |
| 3 | Scene image generation | image_to_image or text_to_image | 6 cinematic photos (16:9) |
| 4 | I2V animation | grok-video-gen or seedance-api | 6 video clips (~5-6s each) |
| 5 | Video assembly + audio | ffmpeg xfade | Raw MTV with music |
| 6 | Lyric transcription | video-processor (Groq Whisper) or manual | SRT with timestamps |
| 7 | Caption burn + credits | ffmpeg + ASS subtitles | Final MTV |
Phase 1: Song Planning & Generation
Use the acestep skill (which in turn uses acestep-songwriting for lyric craft).
Workflow
- Plan the song — decide genre, BPM, key, duration, vocal style, lyric theme
- Write complete lyrics — structured with
[Intro], [Verse], [Chorus], [Bridge], [Outro] tags
- Generate with ACE-Step — always
--batch 2 for two versions
- User picks preferred version
Key Parameters
- Full song: 150-200s duration
- Chorus clip: user selects the best ~30-45s segment after listening
- Always generate 2 versions for A/B comparison
Output
{song_name}_v1.mp3, {song_name}_v2.mp3
Phase 2: Chorus Extraction
After user picks a version and specifies the time range:
ffmpeg -y -ss {START} -i "{full_song}.mp3" -t {DURATION} \
-af "afade=t=in:st=0:d=2,afade=t=out:st={DURATION-2}:d=2" \
-b:a 192k \
"{song_name}_chorus.mp3"
CRITICAL BUG FIX: When trimming MP3 files, always place -ss BEFORE -i (input seeking). Placing -ss after -i causes silent output due to MP3 frame boundary issues. This was a hard-won lesson.
Verification
ffmpeg -i "{song_name}_chorus.mp3" -af "volumedetect" -f null - 2>&1 | grep mean_volume
Phase 3: Scene Image Generation (6 Images)
Planning the Visual Storyboard
Design 6 scenes that follow an emotional arc matching the lyrics. Each scene should:
- Correspond to a specific lyric section
- Progress the emotional narrative (e.g., intimacy → heartbreak → acceptance)
- Vary in composition: mix close-ups, medium shots, and wide shots
- Build from intimate/close to distant/wide for a "proximity to distance" narrative arc
Storyboard Template
| # | Lyric Section | Scene Description | Emotion | Shot Type |
|---|
| 1 | Opening line | [setting + character + action] | [emotion] | Close-up / Medium |
| 2 | Next section | ... | ... | Medium |
| 3 | Building tension | ... | ... | Medium |
| 4 | Emotional peak | ... | ... | Close-up / Medium |
| 5 | Bridge/reflection | ... | ... | Medium / Wide |
| 6 | Final line | ... | ... | Wide / Silhouette |
Image Generation Rules
With character reference photo (typical case):
- Use
image_to_image tool with the reference photo
- Prompt must be cinematic — think Wong Kar-wai, Sofia Coppola, Fincher
- 16:9 aspect ratio, 2K resolution minimum
- FACE MUST BE LARGE AND CLEAR — use medium or medium-close shots so face fills at least 15-20% of the frame. If the face is too small (full-body wide shot), I2V will lose facial identity mid-generation, causing cross-eyes, morphing, or identity drift. This is the #1 cause of bad I2V output.
- Face must be front-facing or 3/4 angle — the image will be used as I2V reference, so face stability matters
- NO accessories that clash with the mood — match props to MTV emotion
- Lighting should be dramatic and atmospheric: neon reflections, candlelight, moonlight, golden hour, rain
Without character reference (abstract/scenic MTV):
- Use
text_to_image tool
- Same cinematic quality requirements
Image Prompt Structure
Cinematic [shot type] of [character description] in [setting].
[Emotional atmosphere description]. [Lighting description].
[Character pose/action — must be subtle, not posed].
16:9 widescreen composition, shallow depth of field, film grain,
[color palette]. Shot on Arri Alexa Mini, anamorphic lens flare.
DO NOTs for Images
- NO stiff poses — character should look natural, candid
- NO cluttered backgrounds — MTV scenes need clean, atmospheric backdrops
- NO bright/cheerful lighting for sad songs (match mood!)
- NO tiny figures lost in the frame — character should be clearly visible
- Face must be recognizable for I2V consistency
Naming Convention
mtv_photo_01_{scene_keyword}.jpg through mtv_photo_06_{scene_keyword}.jpg
User Approval Flow
Show images one by one for approval. If user says "do it on your own" or similar, generate all 6 autonomously using the storyboard plan.
Phase 4a: Ken Burns Animation (Default — Photo Mode)
Convert each still photo into a ~7s cinematic clip using ffmpeg zoompan. This is fast, reliable, and looks great for emotional/melancholy MTVs.
Ken Burns Presets
Vary the motion per scene for visual interest:
| Scene | Motion | ffmpeg filter |
|---|
| 1 | Slow zoom in | zoompan=z='min(zoom+0.0015,1.5)':d=168:x='iw/2-(iw/zoom/2)':y='ih/2-(ih/zoom/2)' |
| 2 | Pan left→right | zoompan=z='1.3':d=168:x='iw*0.1+iw*0.4*(on/168)':y='ih/2-(ih/zoom/2)' |
| 3 | Slow zoom out | zoompan=z='max(zoom-0.0015,1.0)':d=168:x='iw/2-(iw/zoom/2)':y='ih/2-(ih/zoom/2)' |
| 4 | Pan right→left | zoompan=z='1.3':d=168:x='iw*0.5-iw*0.4*(on/168)':y='ih/2-(ih/zoom/2)' |
| 5 | Zoom in + pan up | zoompan=z='min(zoom+0.001,1.4)':d=168:x='iw/2-(iw/zoom/2)':y='ih*0.6-(ih/zoom/2)' |
| 6 | Static + fade | zoompan=z='1.2':d=168:x='iw/2-(iw/zoom/2)':y='ih/2-(ih/zoom/2)' |
Command Template
ffmpeg -y -loop 1 -i "{photo}.jpg" \
-vf "zoompan=z='min(zoom+0.0015,1.5)':d=168:x='iw/2-(iw/zoom/2)':y='ih/2-(ih/zoom/2)',scale=1920:1080" \
-r 24 -t 7 -c:v libx264 -preset fast -crf 20 \
"mtv_video_01_{keyword}.mp4"
Important: -loop 1 is required for still images. Output must be at least as long as needed for the assembled MTV.
Phase 4b: I2V Video Generation (Optional — Animated Mode)
Tool Selection
Primary: grok-video-gen skill (recommended default)
- Fast, free, good motion quality
- Output: ~752×416 (will be upscaled in Phase 5)
- Use
--video --aspect 16:9 -r {photo_path} flags
Alternate: seedance-api skill
- Higher resolution, better face consistency
- Output: native 1280×720
- Slower (1-4 min per clip)
- Use
--ref-image {photo_path} --duration 5
I2V Prompt Guidelines
Every I2V prompt must carry the emotional DNA of the ENTIRE storyboard, not just describe one scene in isolation. If the MTV is about heartbreak, every prompt should breathe heartbreak — the grief, the stillness, the loss.
Motion must match the MTV mood:
| MTV Mood | Motion Style | Example Prompt |
|---|
| Sad/melancholy | Slow, subtle, minimal | "Subtle breathing, slight head tilt, wind gently moves hair, slow blink" |
| Energetic/upbeat | Dynamic, expressive | "Dancing, spinning, arms moving, hair flowing with movement" |
| Reflective/nostalgic | Medium, contemplative | "Slowly walking, looking around, hand touches surface gently" |
| Dramatic/powerful | Bold, sweeping | "Turns toward camera, dramatic wind, fabric flowing, strong pose" |
Critical I2V Rules:
- SLOW motion for sad songs — no fast walking, no catwalk strut
- Maintain distance — if camera is too close, face degrades. For walking scenes, camera tracks backward to maintain distance
- Describe motion, not appearance — I2V inherits appearance from the photo. Focus prompt on WHAT MOVES and HOW
- Camera movement matters — specify: "camera slowly tracks backward", "camera static", "slight camera drift to the right"
- Match motion to storyboard context — if the storyboard calls for stillness, prompt for stillness; if it calls for singing, let her sing. The storyboard is the source of truth for what each scene's motion should be
Gacha Management (CRITICAL)
I2V is probabilistic. The same prompt can produce wildly different results. Follow this workflow:
- Generate raw I2V clip
- Show raw clip to user for review BEFORE assembly — never assemble blindly
- Common I2V artifacts to watch for:
- Character starts talking/moving lips (most common)
- Eyes cross or drift mid-clip (caused by small face in reference)
- Purposeful gazing instead of vacant stare
- Unnatural head movement or body distortion
- If rejected, regenerate — keep previous take as backup (sometimes the next roll is worse)
- Only proceed to assembly after all 6 clips are approved
- Iterate on the weakest link — don't redo everything, identify the one scene breaking coherence and fix just that
Grok I2V Command
SKILL_DIR="/Users/zanearcher/.claude/skills/grok-video-gen"
npx -y bun ${SKILL_DIR}/scripts/main.ts --video \
-r "{photo_path}" \
--aspect 16:9 \
"{motion_prompt}" \
--output "{output_path}" \
--timeout 600
Seedance I2V Command
python3 ~/.claude/skills/seedance-api/scripts/seedance_worker.py \
--prompt "{motion_prompt}" \
--ref-image "{photo_path}" \
--duration 5 \
--output-dir "{session_dir}"
Naming Convention
mtv_video_01_{scene_keyword}.mp4 through mtv_video_06_{scene_keyword}.mp4
Phase 5: Video Assembly
Step 1: Upscale & Slow Down Clips
Grok outputs ~752×416. Upscale to 1920×1080 and apply 0.75x slowdown for cinematic feel:
for i in 01 02 03 04 05 06; do
ffmpeg -y -i "mtv_video_${i}_*.mp4" \
-vf "setpts=1.33*PTS,scale=1920:1080:flags=lanczos" \
-r 24 -c:v libx264 -preset fast -crf 20 \
"clip_${i}_upscaled.mp4"
done
If using Seedance (1280×720), still upscale to 1920×1080 but skip the slowdown unless desired:
ffmpeg -y -i input.mp4 \
-vf "scale=1920:1080:flags=lanczos" \
-r 24 -c:v libx264 -preset fast -crf 20 \
output_upscaled.mp4
Step 2: Check Clip Durations
for f in clip_*_upscaled.mp4; do
echo "$f: $(ffprobe -v quiet -show_entries format=duration -of csv=p=0 "$f")s"
done
Step 3: Crossfade Assembly
Calculate total duration: N clips × avg_clip_duration - (N-1) × crossfade_duration
Target: match audio clip duration. Adjust clip speed or add/remove clips as needed.
ffmpeg -y \
-i clip_01_upscaled.mp4 \
-i clip_02_upscaled.mp4 \
-i clip_03_upscaled.mp4 \
-i clip_04_upscaled.mp4 \
-i clip_05_upscaled.mp4 \
-i clip_06_upscaled.mp4 \
-filter_complex "
[0:v][1:v]xfade=transition=fade:duration=1:offset={OFF1}[v1];
[v1][2:v]xfade=transition=fade:duration=1:offset={OFF2}[v2];
[v2][3:v]xfade=transition=fade:duration=1:offset={OFF3}[v3];
[v3][4:v]xfade=transition=fade:duration=1:offset={OFF4}[v4];
[v4][5:v]xfade=transition=fade:duration=1:offset={OFF5}[v5];
[v5]fade=t=in:st=0:d=2,fade=t=out:st={TOTAL-2}:d=2[vout]
" \
-map "[vout]" -c:v libx264 -preset fast -crf 20 -r 24 \
"mtv_video_assembled.mp4"
Offset calculation:
OFF1 = duration_of_clip1 - 1OFF2 = OFF1 + duration_of_clip2 - 1OFF3 = OFF2 + duration_of_clip3 - 1- ... and so on
Step 4: Add Audio
ffmpeg -y -i mtv_video_assembled.mp4 -i "{chorus_clip}.mp3" \
-c:v copy -c:a aac -b:a 192k \
-shortest \
"mtv_with_audio.mp4"
This produces the clean base video — never burn captions onto a previously captioned video.
Phase 6: Lyric Timing via Transcription
Method 1: Groq Whisper (Recommended)
Use the video-processor skill's transcriber to get accurate timestamps:
GROQ_API_KEY="{key}" python3 ~/.claude/skills/video-processor/scripts/transcriber.py \
"{chorus_clip}.mp3"
This outputs {name}_original.srt with segment timestamps.
Method 2: Manual Mapping
If transcription is unavailable or inaccurate (common with sung Chinese), manually map known lyrics to approximate timestamps by:
- Dividing the audio duration by number of lyric lines
- Adjusting based on musical structure (verses vs chorus timing)
Why ASR Is Mandatory (Never Use Input Lyrics as Captions)
CRITICAL: The lyrics you feed into ACE-Step are a prompt, not a transcript. The AI model interprets them loosely — it may rearrange words, skip lines, change phrasing, add ad-libs, or alter sentence structure. The generated song's actual vocals will often differ from the input lyrics.
Therefore: NEVER use the ACE-Step input lyrics directly as captions. Always run ASR (Groq Whisper) on the final generated audio to transcribe what was actually sung. This gives you:
- Accurate timestamps — synced to the real audio
- Actual phrasing — what the model actually sang, not what you asked it to sing
Lyrics Correction After ASR (MANDATORY)
Whisper will misrecognize some sung words (especially names, slang, or stylized delivery). After transcription:
- Read the Whisper output (words JSON or SRT)
- Listen to the audio and compare — fix obvious mishears (e.g., "y'all" → "Yao", "undecided" → "sends it")
- Keep all timestamps intact — Whisper timing is accurate even when text recognition is wrong
- The corrected words JSON becomes the source of truth for caption generation
Caption Line Breaking (CRITICAL)
Each caption line MUST be one complete, meaningful sentence. Never break mid-sentence.
The caption_video.py script now uses Whisper segment boundaries for line grouping (segments = natural sentence breaks). But when manually building ASS files, follow these rules:
| DO | DON'T |
|---|
| "Chalk on her hands and fire in her eyes" | "her eyes Edge of the" |
| "Edge of the mountain touching the sky" | "the sky First time hanging but" |
| "Teresa Yao don't mess around" | "around SHE SENDS IT no" |
Each lyric line should appear and disappear as a complete unit. Analyze lyrics grammatically — identify sentence boundaries, not arbitrary word counts.
Caption Font & Styling (MTV Standard)
- Font: Impact or Bebas Neue — thick, bold, high-contrast. NOT thin fonts like PingFang SC or Helvetica Neue.
- Size: 50-56pt minimum for 1280x720, 70-80pt for 1920x1080. Captions must be readable at a glance.
- Outline: 3-4px black outline + 1-2px drop shadow for legibility on any background.
- Chorus lines: Use a distinct style (larger font, different color like gold/cyan) to differentiate from verses.
Outro Best Practices
- Pure black background — not a video frame.
- Fade in/out — all text must animate in and out. Never snap on/off.
- Differentiate credits from title text:
- Title ("SHE SENDS IT"): large, white, bold.
- Attribution labels ("Credit to", "Powered by"): small, grey, subtle.
- Names ("Mavis", "EnConvo"): medium, distinct color (gold, cyan), bold — visually separate from the title above.
- Stagger fade-in timing: title first, credits delayed by 0.5-1s.
Crossfade Transitions
Always use crossfade between intro→main and main→outro. 1s fade duration is standard. Use ffmpeg xfade=transition=fade:duration=1:offset=X.
Phase 7: Captions & Credits (ASS Format)
ASS File Structure
[Script Info]
Title: {Song Title} MTV
ScriptType: v4.00+
PlayResX: 1920
PlayResY: 1080
WrapStyle: 0
[V4+ Styles]
Format: Name, Fontname, Fontsize, PrimaryColour, SecondaryColour, OutlineColour, BackColour, Bold, Italic, Underline, StrikeOut, ScaleX, ScaleY, Spacing, Angle, BorderStyle, Outline, Shadow, Alignment, MarginL, MarginR, MarginV, Encoding
Style: Title,PingFang SC,100,&H00FFFFFF,&H000000FF,&H00000000,&H80000000,1,0,0,0,100,100,15,0,1,5,0,5,50,50,80,1
Style: OpenCredit,PingFang SC,48,&H00FFFFFF,&H000000FF,&H00000000,&H80000000,0,0,0,0,100,100,8,0,1,3,0,5,50,50,60,1
Style: LyricCN,Noto Serif TC,56,&H00FFFFFF,&H000000FF,&H60000000,&HA0000000,0,0,0,0,100,100,5,0,1,3,5,2,50,50,100,1
Style: LyricEN,PingFang SC,32,&H80FFFFFF,&H000000FF,&H50000000,&HA0000000,0,1,0,0,100,100,3,0,1,2,3,2,50,50,55,1
Style: EndCredit,PingFang SC,62,&H00FFFFFF,&H000000FF,&H00000000,&H00000000,1,0,0,0,100,100,10,0,1,0,0,5,50,50,80,1
Style: Brand,PingFang SC,42,&H00FFFFFF,&H000000FF,&H00000000,&H00000000,0,0,0,0,100,100,6,0,1,0,0,5,50,50,30,1
Caption Layout
Bilingual lyrics (default):
- Chinese (LyricCN): 56pt Noto Serif TC, white with dark outline + shadow, bottom-center
- English (LyricEN): 32pt PingFang SC italic, semi-transparent white, below Chinese line
- Both use
\fad(800,600) for smooth transitions
Title card (dedicated black frames, first 5-6 seconds):
- Title card MUST be on dedicated black frames, NOT overlaid on video content
- Song title: 100-120pt bold uppercase, centered,
\fad(2000,1200)
- Artist/brand credit below: 48pt regular weight,
\fad(1500,1000)
- Give the title card breathing room — at least 5-6 seconds
- Format:
{Artist Name} on one line, EnConvo on next
End credits (on black frames, last 6+ seconds):
- Main credit: 62pt bold,
词 · 曲 · 演唱 {Artist}
- Brand line: 42pt,
Powered by EnConvo
- Both use
\fad(1500,3000) — long 3-second fade-out
- Must last at least 6 seconds and extend to the final frame
Timing Rules (CRITICAL)
| Element | When | Rule |
|---|
| Title + OpenCredit | 0:00 - 0:04.5 | Must fade out COMPLETELY before first lyric |
| LyricCN + LyricEN | Synced to audio | NO credits visible during lyrics |
| EndCredit + Brand | Black frames only | Start at song_end + 1.5s, end at final frame |
Black Frame Ending
Append 8 seconds of black frames + fade audio out 2s before song ends:
SONG_DUR=$(ffprobe -v quiet -show_entries format=duration -of csv=p=0 mtv_with_audio.mp4)
FADE_START=$(echo "$SONG_DUR - 2" | bc)
SOURCE_FPS=24
ffmpeg -y -i mtv_with_audio.mp4 \
-af "afade=t=out:st=${FADE_START}:d=2" \
-vn -c:a aac -b:a 192k audio_faded.m4a
ffmpeg -y \
-i mtv_with_audio.mp4 \
-f lavfi -i "color=black:s=1920x1080:r=${SOURCE_FPS}" \
-filter_complex "[0:v][1:v]concat=n=2:v=1:a=0[outv]" \
-map "[outv]" -c:v libx264 -preset fast -crf 20 -r ${SOURCE_FPS} \
-t $(echo "$SONG_DUR + 8" | bc) video_extended.mp4
ffmpeg -y \
-i audio_faded.m4a \
-f lavfi -i "anullsrc=r=48000:cl=stereo" \
-filter_complex "[0:a][1:a]concat=n=2:v=0:a=1[outa]" \
-map "[outa]" -t $(echo "$SONG_DUR + 8" | bc) -c:a aac -b:a 192k audio_full.m4a
ffmpeg -y -i video_extended.mp4 -i audio_full.m4a \
-c:v copy -c:a copy -shortest muxed_clean.mp4
CRITICAL: Black frame fps MUST match source video fps. Mismatch causes wrong duration.
Final Burn (LAST STEP)
ffmpeg -y -i muxed_clean.mp4 \
-vf "ass=captions.ass" \
-c:v libx264 -preset fast -crf 18 \
-c:a copy \
"{SongTitle}_MTV_final.mp4"
NEVER burn captions onto a previously captioned video — captions stack and become unreadable. Always burn onto the clean source.
Common Pitfalls & Lessons Learned
| Problem | Cause | Fix |
|---|
| Trimmed MP3 is silent | -ss placed after -i | Put -ss BEFORE -i for input seeking |
| Face degrades in I2V | Camera too close, or fast motion | Keep distance, slow motion, camera tracks backward |
| Cross-eyed / identity drift in I2V | Face too small in reference photo | Use medium-close shots, face must fill 15-20% of frame |
| I2V motion doesn't match vibe | Prompt describes generic motion, not storyboard emotion | Every I2V prompt must carry the emotional DNA of the whole storyboard |
| Lyrics too bold/heavy | Bold weight + thick outline | Use regular weight (not bold) for elegance, 3px outline max |
| I2V looks like a fashion show | Prompt describes appearance, not motion | Focus on subtle motion: breathing, wind, slow turn |
| Catwalk walk in sad MTV | Default I2V motion is energetic | Explicitly prompt: "slow defeated walk", "subtle movement" |
| Subtitle timing wrong | Whisper misrecognizes sung lyrics | Keep Whisper timestamps, replace text with correct lyrics |
| Credits overlap lyrics | ASS timing miscalculation | Verify: OpenCredit fades out before first lyric line |
| Double captions | Burned onto already-burned video | Always use clean (no-caption) source for final burn |
| Framerate mismatch in concat | Black frames at 30fps, source at 24fps | Check source fps with ffprobe, match exactly |
| Video too large for sharing | High bitrate + long duration | Use -crf 20 for clips, -crf 18 for final |
| Ken Burns motion jerky | zoompan fps mismatch | Always set -r 24 on output and d= to match: d=fps×seconds |
| Ken Burns black borders | Image resolution too small | Use images ≥1920×1080; add scale=1920:1080 before zoompan |
| Caption breaks mid-sentence | Line grouping by word count, not meaning | Use Whisper segments for line breaks; manually verify each line is a complete phrase |
| Captions too thin/small | Using PingFang SC or Helvetica at small size | Use Impact or Bebas Neue at 50pt+ with 3-4px outline |
| Outro text snaps on/off | No fade animation on drawtext | Use ffmpeg alpha expression for fade in/out on every text element |
| Credits blend with title | Same font/color/size for everything | Differentiate: title=white/large, labels=grey/small, names=gold or cyan/medium |
| Captions don't match audio | Used ACE-Step input lyrics as captions | ACE-Step interprets lyrics loosely — always ASR the final audio with Groq Whisper, then correct mishears |
Delivery
- Save final MTV in session directory
- Present with
Deliverable tool
- Optionally send via Telegram using
im_channels/telegram_actions/reply with files array
- Caption with song title
Quick Reference: Full Command Sequence
1. acestep skill → generate song (2 versions)
2. User picks version + time range
3. ffmpeg -ss BEFORE -i → trim chorus with fade in/out
4. ffmpeg volumedetect → verify not silent
5. image_to_image × 6 → cinematic scene photos (16:9, 2K+)
--- I2V MODE (always) ---
6. grok-video-gen --video × 6 → I2V clips (review each raw clip before proceeding!)
7. ffmpeg upscale + slow → 1920×1080, 0.75x speed
--- ASSEMBLY ---
7. ffmpeg xfade → crossfade assembly
8. ffmpeg mux → add audio → mtv_with_audio.mp4 (CLEAN SOURCE)
9. Groq Whisper → transcribe for timing
10. Correct lyrics in SRT
11. Write ASS file (bilingual lyrics + title card + end credits on black frames)
12. Check source fps: ffprobe → match black frame fps exactly
13. ffmpeg: audio fade-out 2s before end, extend video + audio with 8s black/silence
14. ffmpeg mux → muxed_clean.mp4 (still no captions)
15. ffmpeg ass burn onto muxed_clean.mp4 → {SongTitle}_MTV_final.mp4
