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Storyboard Shot Breakdown

CommunityPopular
0xsline
storyboard-shot-breakdown

Break down each shot and turn the analysis into a storyboard reference. Use when the user wants shot-by-shot film analysis, director logic, cinematography breakdown, or a storyboard-style reference from a video.

Overview

Publisher0xsline
RepositoryOpenChatCut
Skill namestoryboard-shot-breakdown
Stars
1.9K
Forks
277
Bundled files
Instructions only
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.

  • Self-contained

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

  • Open source

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

Installation

Install the Storyboard Shot Breakdown 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/storyboard-shot-breakdown .claude/skills/storyboard-shot-breakdown
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Storyboard Shot Breakdown 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 Storyboard Shot Breakdown 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 Storyboard Shot Breakdown 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.

Storyboard Shot Breakdown

Use this skill to analyze a video shot by shot and produce a storyboard-style reference that explains the director's visual decisions.

Core Philosophy

Do not merely describe what is visible. Deduce why each visual choice was made.

Analyze each shot across five director-decision dimensions:

DimensionCore question
CompositionWhat is the viewer forced to look at? What pressure does space, symmetry, depth, or framing create?
Focal lengthWhat psychological distance does the lens create? Does it compress, expand, isolate, or invade?
MovementWhy does the camera move or stay still at this exact moment? What changes before and after?
CutWhy cut here instead of earlier or later? Is the driver emotion, story, rhythm, eye trace, action, or sound?
Narrative functionWhat new information does this shot deliver: setup, turning point, emphasis, concealment, revelation?

Workflow

  1. Read project state and source media.
  2. Read transcript or audio context when available so narrative interpretation is grounded.
  3. Detect or mark shot boundaries with available OpenChatCut/media tooling.
  4. Extract representative frames for each shot in batch when possible.
  5. Inspect frames before writing analysis. Do not invent details that are not visible.
  6. For high shot counts, tell the user the count and offer output scope choices before spending effort.
  7. Analyze each selected shot using the five dimensions.
  8. Summarize the overall visual rule of the scene in 1-2 concise sentences.
  9. Generate a storyboard reference image or structured analysis artifact if the user wants a visual output.

Internal Reasoning

Use a counterfactual test: if the conventional alternative were used, what emotion or information would be lost? The answer is usually the director's motive.

Use this reasoning to improve the analysis, but do not output the counterfactual test as a separate section unless the user asks.

Output Format

Per shot:

text
S{N} - {scale} · {lens/mood} · {movement} · {timecode} · {duration} · {narrative function}

Composition: [what attention is forced onto and what pressure the frame creates]
Focal Length: [psychological distance and dramatic effect]
Movement: [why it moves or stays still, and what changes]
Cut: [why the cut lands here, including rhythm/eye trace/sound when relevant]
Narrative: [what story information this shot adds]

Overall:

text
Director's Logic: [3-5 sentences summarizing the visual strategy]
Visual Rule: [1-2 sentences the user can reuse as a shooting/editing reference]

Rules

  • Write from visible evidence and available transcript/audio context.
  • Do not borrow details from adjacent shots unless clearly stated as sequence-level analysis.
  • Keep shot numbering stable.
  • User owns scope trade-offs: if output must be reduced, propose choices.
  • Prefer current OpenChatCut/media tools over hardcoded local commands. Use external scripts only when they are available and clearly help.

Frequently asked questions

What does the Storyboard Shot Breakdown AI skill do?

Break down each shot and turn the analysis into a storyboard reference. Use when the user wants shot-by-shot film analysis, director logic, cinematography breakdown, or a storyboard-style reference from a video.

Why use Storyboard Shot Breakdown on TypingMind?

Because you install it once and use it with any model. Storyboard Shot Breakdown 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 Storyboard Shot Breakdown in TypingMind?

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

Which AI models can use Storyboard Shot Breakdown?

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 Storyboard Shot Breakdown?

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

Is the Storyboard Shot Breakdown 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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