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Multi Clips To Reels

CommunityPopular
0xsline
multi-clips-to-reels

Turn multiple product shots, event footage, travel clips, gameplay moments, UGC/product footage, B-roll, or mixed media into social-ready reels, highlights, recaps, or montage-style short videos from existing project media.

Overview

Publisher0xsline
RepositoryOpenChatCut
Skill namemulti-clips-to-reels
Stars
1.9K
Forks
277
Bundled files
1
LicenseAGPL-3.0
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by 0xsline on GitHub. Read the source before you install it.

Installation

Install the Multi Clips To Reels 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.
  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/0xsline/OpenChatCut.git /tmp/OpenChatCut
mkdir -p .claude/skills
cp -r /tmp/OpenChatCut/src/agent/skills/multi-clips-to-reels .claude/skills/multi-clips-to-reels
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Multi Clips To Reels 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 Multi Clips To Reels 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 Multi Clips To Reels 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.

Multi Clips to Reels

Use this workflow when multiple raw clips or assets carry the output. The task is to select, sequence, and package the strongest footage into one or more reels, highlights, recaps, or short videos.

This is a OpenChatCut-native workflow. Use the current project, source assets, asset-frame inspection, AV/script context, and OpenChatCut editing tools. Use the current timeline when it already contains relevant cuts or for final verification; do not depend on timeline screenshots as the primary way to understand raw source clips. Do not depend on external download, transcription, ffmpeg, or auto-crop pipelines unless the user explicitly asks for an external source that is not already in the project.

Workflow

  1. Read the project state before editing. Inventory usable source assets: duration, aspect ratio, visual subject, motion/energy, audio quality, duplicates, current timeline state when relevant, obvious hero shots, and fixed-role assets such as logos, QR codes, product photos, brand screenshots, or supplied audio.
  2. Confirm that multiple clips carry the output. If one long source clearly defines the story and other assets are only support, switch to the Long Video to Shorts workflow.
  3. Identify the user's starting point:
    • open_media_reel: uploaded clips/photos and a loose goal.
    • script_or_storyboard: supplied script, timestamps, shot list, scene notes, or exact copy.
    • asset_pack_promo: product/event/place assets with logos, screenshots, QR codes, audio, or brand constraints.
    • highlight_selection: many clips where the main work is selecting the strongest visual moments.
  4. Determine only missing constraints that would change the edit: platform, output count, target duration, audience, style, captions/title text, music, and whether the user wants options or direct creation.
  5. If more than one missing constraint remains, ask for them in one <widget> after loading widget-forms. Use text fields for open-ended fields like premise, audience, product/context, or goals; use single/multi choice fields for bounded choices like platform, count, duration, captions, or music.
  6. Assign source assets a possible role: hook, context, proof, demonstration, emotional beat, transition, payoff, end card, logo/QR, product evidence, or audio bed. Do not assume every uploaded clip deserves screen time.
  7. Match the planning style to the starting point. For script_or_storyboard, preserve the user's scene order, copy, timestamps, and claims while mapping each source asset to the requested shot. For asset_pack_promo, lock the product/place/event identity and reserve fixed-role assets for brand, proof, or CTA moments. For open_media_reel and highlight_selection, select and sequence the strongest moments instead of averaging every asset.
  8. Compare possible hooks and sequences using references/short-form-selection.md. Use read_script for the speech/script overview, view_asset_frames for specific source frames and frame-block analysis to select high points or verify what happens on screen. Select for strength, variety, continuity, and fit to the requested platform.
  9. Build a compact sequence plan before heavy editing. For each output include selected assets/ranges, opening hook, shot order, role of each shot, rhythm, target duration, platform treatment, and risks.
  10. If the user gave enough constraints and asked to create directly, proceed after stating the plan. If the material is varied or the requested count is high, create or preview the first strongest reel before batching the rest.
  11. Edit around a viewer-facing arc: hook, context, escalation or proof, payoff. For a pure highlight reel, the payoff can be the strongest final moment or a satisfying recap beat.
  12. Package for the target platform: aspect ratio/crop, title text, styled captions, music/beat sync, light motion graphics, transitions, speed ramps, or zooms only when they improve rhythm or clarity.
  13. QA before reporting done: strongest shot first, clear sequence purpose, distinct outputs, no unsupported claims, platform fit, requested count/duration, timeline names, and export readiness.

Plan Format

When presenting a plan, use this compact shape:

  • Clip/reel number/title
  • Starting point: open_media_reel, script_or_storyboard, asset_pack_promo, or highlight_selection
  • Selected source assets or ranges
  • Source evidence used, such as read_script, source frames, or visual-analysis notes
  • Opening hook visual or line
  • Shot order and role of each shot
  • Rhythm or sequence shape
  • Target duration/platform treatment
  • Edit notes and risks

When creating clips, report timeline names, durations, packaging applied, assumptions, and what to review first.

Rules

  • Start with the strongest visual or clearest promise. Do not slowly introduce every asset.
  • Trim clips aggressively enough to maintain rhythm, but keep enough context for the sequence to make sense.
  • Do not evenly sample every asset.
  • Do not build a contextless montage when the user needs a clear reel, recap, or highlight.
  • Do not repeat visually similar shots unless repetition creates rhythm or comparison.
  • Do not use captions/title text to invent unsupported claims.
  • Do not let packaging effects hide weak source selection.
  • For multiple requested reels or short videos, create distinct angles instead of near-duplicate edits from the same footage.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Multi Clips To Reels AI skill do?

Turn multiple product shots, event footage, travel clips, gameplay moments, UGC/product footage, B-roll, or mixed media into social-ready reels, highlights, recaps, or montage-style short videos from existing project media.

Why use Multi Clips To Reels on TypingMind?

Because you install it once and use it with any model. Multi Clips To Reels 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 Multi Clips To Reels in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/0xsline/OpenChatCut/tree/main/src/agent/skills/multi-clips-to-reels. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Multi Clips To Reels?

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 Multi Clips To Reels?

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

Is the Multi Clips To Reels AI skill free?

Yes. It is published on GitHub by 0xsline under the AGPL-3.0 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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