content-repurposer

name

content-repurposer

description

Turn one short-form video (an Instagram Reel or a TikTok) into platform-correct versions for Instagram, TikTok, and YouTube — then auto-schedule TikTok and YouTube through the user's own Zernio account. It transcribes the video and OCRs the frames to find the call-to-action, then TRANSLATES that CTA per platform: Instagram keeps "comment <word> and I'll send you the link" (the DM mechanic), while TikTok becomes "link in bio" and YouTube becomes "link in description" — in the on-screen text, the voiceover, AND the caption. If the CTA only lives in the description, it rewrites the description per platform instead. Use this whenever the user wants to repurpose, cross-post, or adapt a reel/TikTok for other platforms; fix or translate a CTA, outro, or ending across platforms; write per-platform captions; or schedule the same video to TikTok/YouTube. Trigger even if they don't say "CTA" — "post my reel everywhere", "make TikTok + YouTube versions and schedule them", or "repurpose this short" should all use this skill. On first use it runs a one-time SETUP that installs the (free) transcription tools and walks the user through connecting Zernio. The original file is never modified.

Content Repurposer

One video, edited once, becomes three platform-correct posts — and TikTok + YouTube get scheduled automatically. The thing that breaks when you cross-post is the call-to-action: "comment WORD and I'll send the link" is right on Instagram (DMs are the mechanic) but means nothing on TikTok or YouTube, where the link lives in the bio / description. This skill detects the CTA and translates it per platform — on the video and in the caption — then schedules the result.

The source file is read-only. Every output is a new file in a separate folder.

---

Phase 0 — Setup (first run only)

Before anything else, check whether setup has been done. Look for both repurpose-config.md and .env at the skill root.

• If either is missing → run setup now (below).
• If both exist → skip straight to Phase 1.

Setup steps:

1. Install the tools. Run:

   bash scripts/setup.sh
   

   This installs ffmpeg, tesseract, faster-whisper, and Pillow (all free, all local — faster-whisper is the no-key, no-cost transcription engine) and creates .env from the template. If it reports a failure, walk the user through references/setup-guide.md for their OS, then re-run it.

2. Connect Zernio. Read references/zernio-setup.md to the user and have them: create a Zernio account → connect TikTok + YouTube (first 2 accounts free) → copy their API key (sk_…) from Settings → API Keys → paste it into .env as ZERNIO_API_KEY=…. Confirm with:

   python scripts/schedule_zernio.py --list-accounts
   

3. Write their config. Interview the user for the values in assets/repurpose-config.example.md (handle, the link, default trigger word, timezone + default post time, TikTok privacy, YouTube visibility, whether Instagram is connected). Copy the example to repurpose-config.md at the skill root and fill it in. Paste the TikTok/YouTube account IDs from the --list-accounts output so later runs skip the lookup. Show a short summary to confirm.

Re-customizing later = editing repurpose-config.md or .env. Never edit code.

---

Phase 1 — Analyze the video

Run both passes on the source (audio CTAs and on-screen-text CTAs are different problems — always do both):

# Spoken CTA: transcript + classification + trigger word, into a report
python scripts/repurpose.py "PATH/TO/video.mp4" --out-dir output --dry-run

# On-screen text CTA: OCR the final seconds
python scripts/scan_text_cta.py "PATH/TO/video.mp4"

From the two reports, decide where the CTA lives — this drives everything:

• Spoken (in the voiceover) → repurpose.py found it (cta_type, trigger_word).
• On-screen text (a card / overlay) → scan_text_cta.py found it (card_start, type, trigger).
• Description/caption only (nothing on the video) → both report nothing; the video is reused as-is and only the captions change.

Also note the source platform (ask if unclear). The usual case is an Instagram-style master (ends with "comment WORD"). If the source is already a TikTok-style "link in bio" video, the translation runs the other direction (see the table below) — the mechanics are symmetric.

---

Phase 2 — Translate the CTA per platform (core logic)

The link delivery differs per platform, so the CTA must change to match:

Platform	CTA the video/caption should end on
Instagram	"comment {TRIGGER} and I'll send you the link" (the DM mechanic)
TikTok	"Link in bio"
YouTube	"Link in description"

How you produce each platform's video depends on where the CTA lived:

A. Spoken CTA

Use repurpose.py's trim. Instagram keeps the spoken comment-CTA; TikTok and YouTube get the tail trimmed (the CTA then lives only in their captions). The defaults already do this:

python scripts/repurpose.py "PATH/TO/video.mp4" --out-dir output
# -> video__tiktok.mp4, video__youtube_shorts.mp4 (CTA trimmed), + report.json
# Instagram version = the original master (CTA kept).

Confirm the cut in report.json (cut_if_removed lands after the last real sentence) before trusting the encode.

B. On-screen text CTA

First look at the actual frame (ffmpeg -ss <card_start> -i video.mp4 -frames:v 1 frame.png) and get the caption's pixel box via Tesseract TSV (see the recipe in the original engine docs / scan_text_cta.py). Then:

• Standalone trailing card (CTA is the whole screen) → treat like a spoken CTA: trim for TikTok/YouTube with --cta-at <card_start>; keep it for Instagram.
• Caption overlaid on real content (the video keeps playing under the card) → do not trim. Cover and replace the words per platform with cover_cta.py, one render per platform because the text differs:

  # TikTok
  python scripts/cover_cta.py video.mp4 output/video__tiktok.mp4 \
    --box X Y W H --window T0 T1 --line1 "Link in bio" --line2 "for the full guide"
  # YouTube
  python scripts/cover_cta.py video.mp4 output/video__youtube.mp4 \
    --box X Y W H --window T0 T1 --line1 "Link in description" --line2 "for the full guide"
  # Instagram keeps the original "comment {TRIGGER}" card (use the master as-is),
  # OR re-render it to the exact config phrasing if needed.
  

  Always extract a frame from each output and view it to confirm the old text is fully covered.

C. Description/caption-only CTA

No video edit. The same master video file is scheduled to all platforms; only the caption text changes (Phase 3).

Name outputs *__instagram.mp4, *__tiktok.mp4, *__youtube.mp4. If a platform needs no edit (e.g. Instagram in cases A/C), reuse the original master for it.

---

Phase 3 — Write the captions + descriptions

Using references/caption-patterns.md, report.json (real offer + trigger word), and the voice sample in repurpose-config.md, write one caption per platform with the right CTA baked in:

• Instagram — "comment {TRIGGER} and I'll send you the link".
• TikTok — "link in bio 🔗".
• YouTube — a title (≤100 chars) and a description with the link.

Keep the hook and topic identical across all three; only the CTA line changes. Save them to output/<name>__captions.md so they're easy to copy.

---

Phase 4 — Schedule TikTok + YouTube (Zernio)

Build a job.json (see assets/job.example.json) listing the TikTok and YouTube posts — each with its file, content (caption/description), scheduledFor (ISO 8601, derived from the user's requested date or the config's default time), plus the YouTube title/visibility and TikTok privacy from repurpose-config.md. Pull timezone from the config.

Validate first, then schedule:

python scripts/schedule_zernio.py --job job.json --dry-run   # check payloads
python scripts/schedule_zernio.py --job job.json             # upload + schedule

The script uploads each video (presigned URL), creates one scheduled post per platform, and prints a table (platform · when · status · post id).

Instagram is manual by default: print the Instagram caption + the video path and tell the user to post it themselves. Only schedule Instagram if the config says it's connected (Zernio premium) — then add an instagram post to job.json.

---

Reporting back

Give the user, per platform: where the CTA ended up (comment / bio / description), the output path, and the scheduled time + Zernio post id (or "manual" for Instagram). Then paste the three captions. Keep prose short — they can watch the files themselves.

Notes and limits

• CTA detection is keyword-based (transcript + OCR), tuned for "comment X", "link in bio", "follow me" endings. Novel phrasing may need repurpose.py --cta-at. Patterns live at the top of repurpose.py / scan_text_cta.py.
• Run both detection passes — audio detection misses silent on-screen text CTAs.
• cover_cta.py cleanly replaces a solid caption box; it's not built for text baked into busy footage (moving text, text over a face) — surface a frame and ask.
• Zernio's first 2 connected accounts are free (TikTok + YouTube). Instagram auto-scheduling needs a 3rd (paid) account; otherwise it stays manual.
• TikTok may restrict which privacy_level the API can use until the account is approved for public posting — if a post is rejected, lower it in the config.