Ecommerce Product Montage logo

Ecommerce Product Montage

CommunityPopular
0xsline
ecommerce-product-montage

Assemble product footage, UGC, and b-roll into a conversion-oriented montage with a hook → pain → demo → proof → CTA rhythm. Use for 带货混剪, 产品混剪, 商品短视频, 种草视频, ecommerce montage, product reel, UGC cutdown, or when the user wants selling footage cut into a short that converts.

Overview

Publisher0xsline
RepositoryOpenChatCut
Skill nameecommerce-product-montage
Stars
1.9K
Forks
277
Bundled files
3
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.

  • 3 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 Ecommerce Product Montage 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/ecommerce-product-montage .claude/skills/ecommerce-product-montage
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ecommerce Product Montage 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 Ecommerce Product Montage 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 Ecommerce Product Montage 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.

Ecommerce Product Montage

Use this workflow when the goal is a short that sells, not just one that looks good. The failure mode to avoid is a pretty montage with no sales spine: strong footage, pleasant cuts, and zero reason for the viewer to act.

This workflow decides structure and sequencing for selling footage. It does not write the ad copy — when the hook, angles, or CTA text are not given, hand off to product-ad-video-script for the script, then come back here to assemble. It does not re-explain music tooling — for beat-driven placement use beat-sync-montage or music-intelligence.

This is a OpenChatCut-native workflow. Use the current project, source assets, asset-frame inspection, AV/script context, and OpenChatCut editing tools.

When to switch workflows

  • No script yet, only a product/offer → product-ad-video-script first, return here to cut.
  • Music should drive the cut placement → beat-sync-montage (and music-intelligence for tools).
  • Many clips, no selling intent, just the strongest cut → multi-clips-to-reels.
  • N distinct selling variants from one pool → batch-montage-variants, using this workflow per cut.

Workflow

  1. Fix the one job the edit must do: which objection it dissolves or which action it drives (save, tap, buy, follow). If the brief names none, propose one and confirm.
  2. Inventory the material by sales role, not by file: hero demo, UGC reaction, proof (review/result), context b-roll, price/offer card. See references/material-roles.md. Footage that fills no role is parked, not force-inserted.
  3. Lay the sales spine before cutting: hook (0–3s, the open loop) → pain/context → demo → proof → CTA. See references/sales-spine.md. Every beat maps to a spine position; a clip with no spine position is cut.
  4. Lead with the hook from a real moment, not a title card. The first three seconds either open a loop ("you are doing X wrong") or show the payoff; a logo sting as opener loses the scroll.
  5. Place the demo where the viewer is curious, not where the script says "demo." Demo proves the hook; if the hook is a result, demo the path to it.
  6. Insert proof as a pattern interrupt, not a block. One real review line or result frame beats a stacked proof montage. See references/proof-placement.md.
  7. Hold the CTA long enough to read. Price, offer, and the exact action each get a legible beat; a CTA flashed for one cut is a CTA nobody acts on.
  8. Keep claims grounded. Do not manufacture prices, guarantees, medical, or earnings claims the assets do not support. Pull offer text from the product page or user notes; if absent, ask.
  9. QA by the spine, not by the cut list: can a cold viewer state the offer and the action after watching once? If not, the edit sells nothing.
  10. Report the spine coverage and any role with no usable footage, so a thin section is flagged before shipping.

Plan Format

  • The one job this edit does
  • Material inventory by role, with what is missing
  • Spine map: timestamp → spine position → which clip → why it earns that slot
  • Hook type (open loop / payoff) and the moment used
  • Proof placement and the interrupt it creates
  • CTA beats: price, offer, action, each with duration
  • Risks: ungrounded claims, thin demo, CTA too short, hook that does not land

Rules

  • Spine over polish. A serviceable cut in the right spine position beats a beautiful cut that breaks the argument.
  • Hook is a moment, not a card. Open on footage that creates tension or shows the result; title cards come later if at all.
  • One job per edit. An edit trying to handle every objection handles none. Pick the one that converts this audience.
  • Proof interrupts, it does not pile. One credible proof point lands harder than five weak ones.
  • CTA must be legible. Price, offer, and action each get a readable beat; never flash the CTA.
  • Claims stay grounded. No invented price, guarantee, medical, or earnings claim. Ask when the asset is silent.
  • Park, do not force. Footage that fits no spine position weakens the edit; leave it out and say so.

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 Ecommerce Product Montage AI skill do?

Assemble product footage, UGC, and b-roll into a conversion-oriented montage with a hook → pain → demo → proof → CTA rhythm. Use for 带货混剪, 产品混剪, 商品短视频, 种草视频, ecommerce montage, product reel, UGC cutdown, or when the user wants selling footage cut into a short that converts.

Why use Ecommerce Product Montage on TypingMind?

Because you install it once and use it with any model. Ecommerce Product Montage 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 Ecommerce Product Montage in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/0xsline/OpenChatCut/tree/main/src/agent/skills/ecommerce-product-montage. 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 Ecommerce Product Montage?

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 Ecommerce Product Montage?

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

Is the Ecommerce Product Montage 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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