Repurpose One Source into Distinct Platform Drafts
Adapt an owned article or subtitle file into distinct platform drafts while keeping source locations visible. Review the meaning of every claim before publishing.
Fastest way
Ask your AI to do it
Paste this into the AI agent you already use:
Use Content Repurpose Studio with my owned or permitted source. Ask which audiences, platforms, voice and action I need. Prepare the unchanged source, then author 2–6 distinct drafts with segment references, exact quotes and marked commentary. Build into a fresh folder, review meaning against the source and check each platform budget. Deliver editable drafts and the source map; do not publish them.
Can one source become several useful drafts?
Content Repurpose Studio packages 2–6 separately authored drafts for X threads, WeChat, Rednote, LinkedIn, newsletters or short scripts. The Python tools prepare the source and validate the plan; your agent writes the drafts. They do not call a writing model, record a video or publish posts.
Keep the original source and name each audience
- Supply an owned or permitted UTF-8 Markdown, text, SRT or VTT file. Read references/input.md: the source supports up to 96 KiB and 120 paragraphs or subtitle cues.
- Choose the platforms, audience, voice and action. A research-team newsletter and a creator's short script should have different openings and evidence order.
- Prepare your real source with --real. Keep the original bytes unchanged while drafting; editing the source may change its hash and segment IDs.
Rewrite the opening, preserve the facts
An illustrative three-draft plan can use a practical checklist for a newsletter, a single observation for an X thread and a visual sequence for a short script. Write each version deliberately. Attach factual blocks to sourceIds, use exact substrings for quotes and mark new interpretation as commentary. A valid reference tells you where to look; it does not establish that a paraphrase is true.
Practice preparation and draft packaging
From the installed package folder, Python 3.10+ runs these offline commands without dependencies or API keys. The included fictional plan already matches the included source hash. For your source, first read writing-brief.md and source-map.csv, author a matching plan, then use it instead of examples/plan.json.
Read this release’s setup before running the example
Confirm installation and invocation in your host
python3 scripts/prepare-source.py --source examples/source.md --title "Juniper Field Notes" --demo --output ./practice-source
python3 scripts/build-studio.py --input examples/plan.json --source examples/source.md --output ./practice-contentReview meaning as well as character budgets
- Open index.html and compare each draft with its source segments. Check headlines, openings and CTAs too; those are authored metadata outside the source-linked blocks.
- Check exact quotes and missing context. Review transcription errors and cue intervals when working from subtitles; cue timing is not word-level alignment.
- Inspect the supplied budgets and the target platform editor separately. Unicode code-point checks do not reproduce every platform's weighted posting limits. Script durations are planned, not recorded.
Inspect the current example output → — Compare the visible result with the exported files and checks described in this section.
Keep editable drafts beside the source map
Deliver the per-platform Markdown, plan.json, source map and reviewed handoff. Regenerate into a new folder after edits. The output may contain the full original source, so check it before sharing. For a visual companion, take an approved cover brief to Brand Carousel Studio; image creation and publishing are separate steps.
Build a listening home for approved source audio
Explain one source-backed idea as a reviewed sketchnote
Turn approved drafts into a branded carousel — Carry over the reviewed claims and adapt one idea per card.