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Tt Repurposer

Community
sergebulaev
tt-repurposer

Repurpose content into a native TikTok script and caption. Take a LinkedIn post, blog, newsletter, or X thread that worked elsewhere and rebuild it as a spoken script: hook in the first second, every line sayable in one breath, open on the payoff, a trend angle where it fits, plus a caption, published via Publora on approval. Adapts content across platforms. Not for a fresh hook (use tt-hook-scripter), not the caption only (use tt-caption-writer), not auditing a script (use tt-humanizer --mode audit).

Overview

Publishersergebulaev
Repositorytiktok-skills
Skill namett-repurposer
Stars
101
Forks
22
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by sergebulaev on GitHub. Read the source before you install it.

Installation

Install the Tt Repurposer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/sergebulaev/tiktok-skills/tree/main/skills/tt-repurposer
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/sergebulaev/tiktok-skills.git /tmp/tiktok-skills
mkdir -p .claude/skills
cp -r /tmp/tiktok-skills/skills/tt-repurposer .claude/skills/tt-repurposer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Tt Repurposer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Tt Repurposer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Tt Repurposer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

TikTok Repurposer

Turn something you already made into a TikTok video script that sounds like it was born on camera. Repurposing is not copy-paste. A post that killed on LinkedIn will die on TikTok if you read it aloud: wrong open, wrong rhythm, sentences no one can say in one breath, and artifacts ("link in bio", hashtag walls, corporate phrasing) that scream off-platform.

This skill transforms, it does not generate. It reads your source, keeps the idea, and rebuilds the delivery as a spoken script plus a short caption for TikTok.

When to use

  • "Turn this LinkedIn post into a TikTok script"
  • "Repurpose my blog post / newsletter / X thread for TikTok"
  • "This worked on Instagram, adapt it into a video I can film"
  • "I have a rough idea in another format, make it native here"

Not for a blank-page hook (use tt-hook-scripter), not for the caption on its own (use tt-caption-writer), and not for reviewing an already-TikTok script (use tt-humanizer --mode audit).

How it works

Voice profile first (all drafts). If ../../references/voice-profile.md has filled: yes, load it and match the user's voice fingerprint, hard rules, and CTA/link style throughout. If it is not filled, mention once that tt-humanizer --mode profile can learn their voice from a few posts, then proceed with the generic voice rules.

Never invent the specifics. The rules below ask for a concrete number, a date and a named entity, because that is what separates a real post from a generated one. Take them from what the user actually said in this conversation. Do not invent a figure, a date, a client name or a result, and do not soften a vague claim into a plausible-looking number. If the user has nothing concrete for a beat, ask them once, and if they still have nothing, drop the claim rather than decorate it. A published invented number is a retraction; a missing one is only a weaker post.

  1. Take the source. Any format: a post, a paragraph, a newsletter, a thread, a caption, a transcript, a bullet list, a link to read. Ask for the source and the goal (completion / saves / comments / shares) if not given.
  2. Extract the spine. Strip the source platform's shell and pull out the one claim, the one story, or the one number worth keeping. Most repurposing fails because it keeps the words instead of the point.
  3. Open on the payoff. TikTok decides in the first second. Lead with the result, not the setup. "Here is the fix" beats "let me walk you through the context". The source's opener almost never survives.
  4. Re-hook for the first second. Hand the opening line to tt-hook-scripter: the spoken line, the on-screen text, and the opening visual firing at once, picked by the goal.
  5. Choose the native shape. A blog or long post -> a 3-part spoken script (hook, value, loop-close). A listicle -> a fast on-screen-text list script, one item per beat. A long video or transcript -> a script that delivers the single payoff, not a summary.
  6. Make every line sayable. Rewrite each line so it can be said out loud in one breath: contractions, fragments, short lines. If you cannot read it without stopping for air, cut it.
  7. Add a trend or sound angle where it fits. If a trending sound or format carries the idea, reference tt-trend-mapper to check fit and script the twist. Skip it if forcing a trend would bury the point.
  8. Write the caption. Hand the short caption to tt-caption-writer: under 2,200 chars, 3 to 5 mixed-reach hashtags, TikTok settings.
  9. Strip off-platform artifacts. Remove "link in bio" from other platforms, hashtag walls beyond a few, "smash subscribe", @-handles that only exist elsewhere, corporate phrasing, and any "as I posted on LinkedIn" throat-clearing. A repurposed script should not admit it was repurposed.
  10. Humanizer pass. Run tt-humanizer V3: it scrubs 2026 AI vocab by density, em dashes above the cap (caption about one per 100 words, card at most one), stacked triads, reveal bridges, sincerity openers and "hey guys" filler, fixes only a teleprompter-flat run (never inserts a punch line), and checks every line is sayable out loud in one breath. Keep the user's real numbers and named entities from the source.
  11. Approval card. Show: source -> TikTok mapping (what became what), the script (hook / value / loop-close), on-screen text, the trend or sound angle if any, the caption, char counts, primary goal.
  12. On approval. Publish the caption via lib.publish("video", draft_text=<approved caption>, target_url="https://www.tiktok.com/upload", video_path=<render_or_None>, platforms=[<TIKTOK_PLATFORM_ID>], scheduled_time=<iso_or_None>). Without a rendered .mp4, lib.publish returns the script, caption, and settings as a copy-paste block to upload in the TikTok app.

Native-fit rules (source -> TikTok)

  • LinkedIn post -> TikTok: cut the warm-up. LinkedIn tolerates a slow build; TikTok does not. Rewrite the hook to open on the payoff, and turn the body into lines you can say out loud.
  • Blog / newsletter -> script: pick the single most repeatable claim as the spoken hook, then a 3-part script (hook, value, loop-close). Do not narrate the whole piece.
  • Listicle -> on-screen-text list: one item per beat, each a short spoken line with matching on-screen text, not a wall of bullets.
  • X thread -> script: the thread's best tweet becomes the hook; the rest become beats you speak. Drop the numbering and the "1/" scaffolding.
  • Long video / transcript -> script: lead with the payoff, deliver one idea, close the loop. Never a summary.
  • Instagram / any caption -> caption: strip hashtag blocks down to 3 to 5, drop off-platform CTAs, keep it short.

Hard rules

Global voice rules: see root SKILL.md Voice rules. Additional skill-specific rules:

  • Keep the source's claim and facts intact. Repurposing changes the delivery, never the meaning or the numbers.
  • Every line must be sayable out loud in one breath. If it needs a pause for air, cut it.
  • The first second must land the whole promise. Open on the payoff, not the setup.
  • Never read the source verbatim. Rebuild the hook and rhythm from the spine.
  • One specific number where the source offers one. Keep it.
  • Do not hard-sell the user's product. One natural mention max.

Anti-patterns (skill will refuse)

  • Copy-pasting the source and reading it aloud (that is not repurposing).
  • Keeping the source platform's artifacts ("link in bio", "smash subscribe", hashtag walls, corporate phrasing).
  • A slow open that saves the payoff for the end.
  • Lines too long to say in one breath.
  • Em dashes above the cap in the caption or on a card, or an em dash swapped for a period.
  • "The result?" reveals and staccato stacks added for punch.
  • Rule-of-three lists without specifics.
  • "leverage", "fundamentally", "game-changer", "deep dive", "hey guys".
  • Forcing a trending sound that buries the point.

Resources

  • ../../references/hook-formulas.md - the 10 TikTok 3-second hook formulas to re-hook with
  • ../../references/algorithm-heuristics.md - 2026 TikTok ranking rules (completion, rewatch, shares, sound timing)
  • ../../references/voice-rules.md - the canonical spoken-script and caption voice rules

Related skills

  • tt-hook-scripter - script the first-second hook (repurposer hands the open here)
  • tt-trend-mapper - check trend fit and script the twist for a sound angle
  • tt-caption-writer - write the caption, hashtags, and settings (repurposer hands the caption here)
  • tt-humanizer - scrub AI tells and check lines are sayable, plus --mode audit to review the result

Frequently asked questions

What does the Tt Repurposer AI skill do?

Repurpose content into a native TikTok script and caption. Take a LinkedIn post, blog, newsletter, or X thread that worked elsewhere and rebuild it as a spoken script: hook in the first second, every line sayable in one breath, open on the payoff, a trend angle where it fits, plus a caption, published via Publora on approval. Adapts content across platforms. Not for a fresh hook (use tt-hook-scripter), not the caption only (use tt-caption-writer), not auditing a script (use tt-humanizer --mode audit).

Why use Tt Repurposer on TypingMind?

Because you install it once and use it with any model. Tt Repurposer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Tt Repurposer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/sergebulaev/tiktok-skills/tree/main/skills/tt-repurposer. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Tt Repurposer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Tt Repurposer?

As many as you like. As long as a model supports skills, you can use Tt Repurposer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Tt Repurposer AI skill free?

Yes. It is published on GitHub by sergebulaev under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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