repurpose-content

name	repurpose-content
description	Turn one long video (or podcast/audio) into many pieces — vertical Shorts/Reels clips, quote images, captions, and a thread. Use when the user says "repurpose this video", "turn my podcast into clips", "make shorts from this", "slice this up for social".
allowed-tools	Bash Read Write Edit Glob Grep

Repurpose Content

One long asset → a week of content. Pipeline: transcribe → find the moments → cut clips → derive posts → package per platform.

Commands used (argument shapes in workflows/WORKFLOWS.md § Publish & Repurpose): transcribeVideo (needs OPENROUTER_API_KEY) · extractClip · packageContent (both local/free) · generateSingleImage · generateCaption.

STEP 1: Intake

1. Confirm the source file exists; note duration:

   ffprobe -v error -show_entries format=duration -of csv=p=0 "<file>"
   

2. Ask (one batch): which platforms? how many clips (default 3-5)? quote images / caption thread wanted too?
3. Run /content-preflight if a project exists (brand tone for captions); minimal mode is fine for a quick job.

STEP 2: Transcribe

node workflows/cli.cjs transcribeVideo '{"mediaPath":"<file>","outputPath":"projects/{name}/output-contents/{piece}/transcript.txt"}'

• No OPENROUTER_API_KEY → tell the user transcription needs one (https://openrouter.ai/keys), or ask them to paste a transcript/subtitles file instead. Don't guess the content.
• Cost is roughly $0.006/minute — state it for long files (>30 min) before running.

STEP 3: Find the moments

Read the transcript and select clip candidates — you do this, no API call needed. Look for: strong hooks/claims, complete self-contained thoughts (15-60s), emotional peaks, concrete tips, quotable one-liners.

The transcript has no timestamps. Estimate each moment's position from its word offset (spoken English ≈ 150 words/min), then cut generously (start ~5s early) — you'll verify in the next step.

Present candidates and let the user pick:

Found 6 clip candidates:
  1. ~02:10  "The roast date matters more than the price tag" (hook, ~25s)
  2. ~08:45  The 3-signs-of-stale-beans tip (self-contained, ~40s)
  ...
Which ones? (numbers / all / adjust)

STEP 4: Cut and verify each clip

node workflows/cli.cjs extractClip '{"videoPath":"<file>","outputPath":".../clips/clip-01.mp4","start":"02:05","duration":35,"cropTo":"9:16"}'

• cropTo: "9:16" center-crops for Shorts/Reels — warn if the speaker may be off-center; omit cropTo to pad instead at packaging time.
• Timestamps are estimates: after each cut, transcribe the CLIP (cheap — it's short) or ask the user to check it, and adjust start/duration if the cut clips a sentence. Iterate until clean.

STEP 5: Derive the other formats (as requested)

• Quote images: pull the strongest lines → /generate-image with brand style (or a clean typographic card), 4:5.
• Captions per clip: generateCaption (or /write-copy) from the clip's transcript segment — hook first line, platform hashtags.
• Thread/text post: distill the transcript's core argument into a numbered thread (twitter/linkedin), respecting char limits.

STEP 6: Package everything

For each clip/image: /package-content into output-contents/{piece}/publish/{clip-id}/. Then report:

✅ REPURPOSED — podcast-ep12 (42 min source)
  3 clips (9:16)  → publish/clip-01..03/  (tiktok, youtube, instagram)
  2 quote images  → publish/quote-01..02/ (instagram, linkedin)
  1 thread        → publish/thread.txt    (twitter)
  Spend: $0.31 (transcription $0.25, images $0.06 — clips/packaging free)

recordCost any paid steps against the project budget.

Pipeline-first + audit trail (mandatory)

• Author <content-id>.pipeline.json IN the content folder BEFORE running the chain (nodes = CLI commands — transcribe → extract → package — {{node.data.field}} refs wire outputs to inputs), then node workflows/cli.cjs runPipeline @<file>. See workflows/pipelines/README.md.
• The content folder gets a prompts.txt: quote-image prompts and caption/thread copy; update it on every retry with a one-line RESULT note.
• Log each paid generation via createGenerationManifest / addManifestEntry (AGENT-GUIDE Step 5).