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Papercut Setup

Community
0xS4N4TG
papercut-setup

Install, check or upgrade the papercut toolchain. Runs the doctor, asks how much to set up (Minimal, Standard, Full), then runs install.sh with flags and fixes dependency errors. Use for "set up papercut-explainer", "install papercut", "check my papercut install", "set up the voice", "why won't it render".

Overview

Publisher0xS4N4TG
Repositorypapercut-explainer
Skill namepapercut-setup
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 Setup 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-setup
  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-setup .claude/skills/papercut-setup
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Papercut Setup 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 Setup 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 Setup 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 setup

A guided wrapper around install.sh. It checks what is installed, asks how much the user wants, runs the installer non-interactively and reports. Use it whenever another papercut skill finds something missing.

Preflight

  • Find the repo root (where install.sh lives): readlink on the installed skill folder ends in <root>/skills/papercut-setup. Look in each harness's skills folder in turn (the table is harnesses.sh; typically ~/.claude/skills, ~/.agents/skills, ~/.config/opencode/skills, or the same under <project>/). Failing that, PAPERCUT_HOME= in ${XDG_CONFIG_HOME:-~/.config}/papercut-explainer/config.env. If neither exists, the skills probably came from npx skills add (skills only, no library). Ask where to clone the repo (default ~/papercut-explainer), run git clone https://github.com/0xS4N4TG/papercut-explainer <dir>, and use that as the root. The installer then replaces the copied skill folders with links into the checkout (it backs up real folders first). Never guess a path.
  • Run every install.sh command from that root. It needs bash, and macOS or Linux (Windows: use WSL).
  • The installer's own prompts need a terminal, which the agent's shell tool lacks. Always pass --yes and the answers as flags. Tell the user they can run ./install.sh themselves for the interactive menu.

1. Doctor

./install.sh --doctor

Add --project DIR, --skills-dir DIR or --target <names> if the skills went somewhere other than the detected defaults; the doctor only looks where you point it, and with no --target one complete install location is enough. It prints [ok], [--] (missing) or [!!] (wrong). Summarise it in plain words:

  • skills installed, config file and PAPERCUT_LIB
  • node 20+, npm, ffmpeg, python3
  • Remotion agent skills, Python tools (numpy + Pillow)
  • voice: qwen_tts importable, a CustomVoice model in the Hugging Face cache
  • library files present

Then say which install mode that adds up to (see papercut-explainer, Install modes).

2. Ask

Ask only what is still open, in one call (your agent's question tool, for example AskUserQuestion in Claude Code). Run ./install.sh --dry-run --mode minimal --yes first if you need to know which harnesses it detected (--target auto, the default):

QuestionOptions
How much?Minimal: skills only, seconds. Standard: render with a placeholder voice, ~0.7 GB and a few minutes. Full: Standard + local voiceover, +4-6 GB (a 1.5 GB venv plus a 2.3 or 4.2 GB model) and a 2-minute smoke test. Custom: pick components.
Which agents?Detected on this machine (default, --target auto; Claude Code if none), a list such as --target claude,codex,gemini, or --target all. Names are in harnesses.sh; the README's Works with table says which are tested.
Where do the skills go?User-wide (the default) or one project (--project DIR).
Copy or link?Symlink (default, updates with git pull) or --copy (a snapshot).
Scene-agent model, per agent with file subagents (claude, opencode, codex, gemini; skip the rest)?One question per selected agent, each with Inherit (use the session model) as an option. Claude Code: Sonnet (default: cheapest, what the scene agents were tuned on) · Opus (strongest; every parallel scene agent bills at Opus rates) · Haiku · Inherit. Maps to --claude-model sonnet|opus|haiku|inherit|<id>. Other agents: default Inherit, or a model id in that agent's own format (opencode provider/model-id, for example anthropic/claude-sonnet-5-5; Codex and Gemini plain ids). Maps to --opencode-model M or --agent-model codex=M.
Another provider's model (DeepSeek and others)?Only if the user asks. Connect the provider inside the agent first (OpenCode /connect; Codex config.toml provider; Claude Code's ANTHROPIC_* variables), then pass its model id as above. The README's Models other than Claude section has the steps and the DeepSeek ids. Say plainly that it is untested end to end and that weaker models cost more QA rounds.
TTS model size (Full)1.7B, better prosody, ~4.2 GB (default). 0.6B, lighter and faster, ~2.3 GB.
Voice-clone model (Full)No (default), or --with-clone: the Base model of the same size again.

Confirm before any multi-GB download. On a machine with no GPU (not Apple Silicon, no NVIDIA), TTS generation takes minutes per line; suggest recording the voiceover or the placeholder voice instead.

3. Install

./install.sh --mode <minimal|standard|full> --yes [--target auto|all|claude,codex,...] [--claude-model M] [--opencode-model M] [--agent-model NAME=M] [--skills-dir DIR | --project DIR] [--copy] [--tts-model 1.7B|0.6B] [--with-clone]
./install.sh --mode custom --components skills,deps,remotion-skills,pytools,tts,verify --yes
  • Add --dry-run first if the user wants to see the plan; it changes nothing.
  • The scene-builder agent is written as a copy per harness, in that harness's own format (Claude and OpenCode markdown, Codex TOML, Gemini markdown), with the chosen model line or none for Inherit. Harnesses without file subagents get none; papercut-build then builds scenes itself or uses the harness's own parallel tasks. Skills stay symlinks. To change a model later: ./install.sh --mode custom --components skills --target codex --agent-model codex=<id> --yes (or --claude-model, --opencode-model).
  • Standard and Full take minutes (npm install, Remotion's Chrome, venvs, model download). Run them in the background and check the output; do not hold a foreground call.
  • What each mode does: Minimal links the skills and the scene-builder agent (into each selected harness's skills and agents folders). Standard adds a dependency check, the Remotion agent skills (npx skills add remotion-dev/skills -g -y -a <harness id> once per selected harness, installed user-wide, so say so when you confirm the plan), a Python venv with numpy, Pillow and soundfile, and a self-test render. Full adds library/voice/setup_tts.sh: a voice venv with Qwen3-TTS, an ASR backend (mlx-whisper on Apple Silicon, faster-whisper elsewhere), the model download and a one-line smoke test.
  • The installer writes PAPERCUT_HOME, PAPERCUT_LIB, PAPERCUT_PY, QWEN_TTS_PY and ASR_PY into ~/.config/papercut-explainer/config.env. An existing skill folder that differs from this checkout is backed up to ~/.config/papercut-explainer/backups/ (not into the skills folder, so it is not loaded twice); an identical copy, such as one from npx skills add, is just replaced.

4. Verify and report

Run ./install.sh --doctor again with the same --project, --skills-dir or --target. Report what is installed, which scene-agent model each agent got, what failed (the installer prints needs attention: with component names), and the fix. A new Claude Code, Codex or Gemini CLI session picks up newly linked skills (restart it); opencode reloads configuration automatically. Then suggest: "make a papercut explainer about ", or one stage at a time ("write a hook for...", "storyboard this script", "set up the voice").

Troubleshooting

SymptomFix
node older than 20, or missingInstall Node 20+ (nodejs.org, brew install node), then ./install.sh --mode custom --components deps,verify --yes.
ffmpeg missingbrew install ffmpeg or apt install ffmpeg.
Voice venv: "need Python 3.10-3.12"Qwen3-TTS has no wheels for newer Python. Install uv (https://docs.astral.sh/uv/) or brew install python@3.12, rerun the tts component.
Hugging Face download stalls or failsRerun; finished files are kept and the script retries 3 times. It sets HF_HUB_DISABLE_XET=1; set it yourself for manual downloads.
First render is slowRemotion downloads its headless Chrome once. The audio render and capture.mjs use your own Chrome; set CHROME_PATH if it isn't in a usual place.
Self-test failsRun library/tools/selftest.sh directly to see the failing step.
Skills don't showRestart Claude Code, Codex or Gemini CLI (opencode reloads). Check the harness's folder (harnesses.sh; ~/.agents/skills for most) and run ./install.sh --doctor.
opencode: "Configuration is invalid ... tools"An old copy of the Claude agent file sits in an opencode agents folder. Rerun ./install.sh --target opencode; it writes the opencode version.
Scene agents cost too much, or run on the wrong modelRerun the skills step with another model: ./install.sh --mode custom --components skills --claude-model sonnet --yes (or --opencode-model inherit). inherit means the session model.
Move from Minimal to Standard./install.sh --mode custom --components deps,remotion-skills,pytools,verify --yes
Add the voice later./install.sh --mode custom --components tts --yes [--tts-model 0.6B] [--with-clone]
Remove it./install.sh --uninstall removes the links it recorded. It leaves config.env, the venvs under ~/.local/share/papercut-explainer and the Hugging Face cache; delete those by hand for the space.
WindowsNot supported directly. Use WSL.

Hand-off

Return to the skill that sent you here, or to papercut-explainer for the stage table. Files hold the state: config.env carries the library path, so the other skills resolve it without asking again.

Frequently asked questions

What does the Papercut Setup AI skill do?

Install, check or upgrade the papercut toolchain. Runs the doctor, asks how much to set up (Minimal, Standard, Full), then runs install.sh with flags and fixes dependency errors. Use for "set up papercut-explainer", "install papercut", "check my papercut install", "set up the voice", "why won't it render".

Why use Papercut Setup on TypingMind?

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

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

Which AI models can use Papercut Setup?

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 Setup?

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

Is the Papercut Setup 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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