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Papercut Qa

Community
0xS4N4TG
papercut-qa

Check a papercut reel's stills against the style DNA and the storyboard. Renders contact sheets at a few timestamps, runs the full checklist, then writes the delivery summary. Use for "QA the reel", "check my scenes look like paper", "is this ready to post".

Overview

Publisher0xS4N4TG
Repositorypapercut-explainer
Skill namepapercut-qa
Stars
106
Forks
10
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 0xS4N4TG on GitHub. Read the source before you install it.

Installation

Install the Papercut Qa 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/0xS4N4TG/papercut-explainer/tree/main/skills/papercut-qa
  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/0xS4N4TG/papercut-explainer.git /tmp/papercut-explainer
mkdir -p .claude/skills
cp -r /tmp/papercut-explainer/skills/papercut-qa .claude/skills/papercut-qa
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Papercut Qa 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 Papercut Qa 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 Papercut Qa 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.

Papercut QA

Compare stills for style, not content, against the Style DNA and the storyboard. Run it per scene while building and once on the whole reel before the final render.

Preflight

  • Install: Standard or Full. Stills need a scaffolded project with Remotion, and the contact sheets need Python with numpy and Pillow ($PAPERCUT_PY). Missing pieces: ./install.sh --doctor, then papercut-setup.
  • Library: $PAPERCUT_LIB, else the PAPERCUT_LIB= line in ~/.config/papercut-explainer/config.env, else ask once.
  • Read first: Style DNA in ../papercut-explainer/references/style-guide.md section 2, and the backdrop sheet library/papercut/public/bg/backdrops/_sheet.jpg. Each image costs about 0.7-1.5k tokens, so open only what the step needs.
  • For density, ../papercut-explainer/references/frame-breakdown.md ("Pacing stats" at the end): scenes average 2.8 s, 2-4 discrete visual events per scene, one every 0.4-0.8 s on a stressed word, a new caption page about every 0.6 s. Copy the density, not the content.

1. Render stills

From the project's papercut/ folder:

$PAPERCUT_LIB/tools/qa.sh NAME FROM-TO NTH [SCALE=0.3] [COLS=9]
  • Use 4-6 timestamps per check. For a scene, NTH is about its length in frames divided by 4. Leave FROM-TO out for the whole reel and raise NTH.
  • The output is out/qa/NAME_0.jpg (and _1, _2 for longer ranges), at most 45 frames per sheet. Read the sheet; keep sheets small.
  • One QA command per scene, and never two renders at once. Keep fixes to two rounds per scene.
  • Check against the storyboard: the scene's frame 0, its key events on their words, nothing clipped, nothing covering the banner or caption bands.

2. Checklist

  • Every object reads as paper: grain, rough edge, drop shadow, stacked-piece shading, no outlines or gradients.
  • The world camera moves smoothly. Only the banner and labels boil (stepped, subtle).
  • The banner is fixed in position and taped, 3-7 words, one fact each, never repeats the VO. The banners alone read as a fact sheet.
  • Every set illustrates a concrete word in its VO line, numbers are physical props, and there is one callback set before the CTA.
  • Every number and UI label traces to the facts list. The script has at least one honest limitation and a feature stack of exactly three.
  • Captions: one tag per word, tilted, popping on onset, pages of 1-3, in the 68-80% band, never on a face.
  • Saturation only on characters, captions and signals.
  • A visual event on every stressed word, with ambient motion always running.
  • Cuts on banner changes (sets 1.5-3 s in tours and news, up to 5 s in a metaphor beat), bottom 20% clear.
  • The HOOK block (SAY / WRITE / SHOW / ALIGN) is on screen exactly as written: frame 0 shows the SHOW moment mid-action with the WRITE title on it, and the first VO line is SAY.
  • Every scene has a camera move, at most one page turn or tear, a tape pull or whip into the CTA, and every transition has its SFX.
  • Humour pass visible on screen: one format throughout, a costume prop per idea, one struggling beat, the frame-0 prop returns changed in the CTA set, and every gag reads in under 1 s and never covers the banner, the captions or the key number.
  • Vocabulary in the VO and banners matches the audience level in SERIES.md.
  • Voiceover, captions and events are in sync (scrub the Studio at every cut).

For a failed item, fix the scene file (or the kit in the library, never src/lib/ in the project) and re-run the one scene. Rebuild a scene with papercut-build.

3. Deliver

Open the Studio preview, list the scenes with timings, and say what is placeholder: voice, music, SFX, assets. If the voice is a placeholder, say how to re-voice it (papercut-voice). After posting, the numbers go to papercut-strategy for the autopsy.

Principles pass

Scrub one scene at 5 fps and check against ../papercut-explainer/references/motion-principles.md: anticipation before each big move (2), everything eased (6), something trailing after impacts (5), one focal prop (3), one exaggerated beat (10), stacked shading and a consistent shadow (11).

Hand-off

Fixes go back to papercut-build (scene or sound) or papercut-voice (sync). A clean pass ends the reel: render with $PAPERCUT_LIB/tools/render.sh when the user asks.

Frequently asked questions

What does the Papercut Qa AI skill do?

Check a papercut reel's stills against the style DNA and the storyboard. Renders contact sheets at a few timestamps, runs the full checklist, then writes the delivery summary. Use for "QA the reel", "check my scenes look like paper", "is this ready to post".

Why use Papercut Qa on TypingMind?

Because you install it once and use it with any model. Papercut Qa 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 Papercut Qa in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/0xS4N4TG/papercut-explainer/tree/main/skills/papercut-qa. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Papercut Qa?

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 Papercut Qa?

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

Is the Papercut Qa AI skill free?

Yes. It is published on GitHub by 0xS4N4TG 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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