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Papercut Strategy

Community
0xS4N4TG
papercut-strategy

Decide what a papercut reel should be. Picks the topic, one familiar format, the audience level, the comment-keyword funnel and caption, studies competitor reels, and runs the post-publish autopsy. Use before any hook or script, or when reviewing how a posted reel did.

Overview

Publisher0xS4N4TG
Repositorypapercut-explainer
Skill namepapercut-strategy
Stars
106
Forks
10
Bundled files
1
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.

  • 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 0xS4N4TG on GitHub. Read the source before you install it.

Installation

Install the Papercut Strategy 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-strategy
  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-strategy .claude/skills/papercut-strategy
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Papercut Strategy 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 Strategy 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 Strategy 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 strategy

These notes decide what a reel says and why it holds attention. The other papercut skills decide how it is written, staged and built. The rules come from studying high-performing faceless tech reels and from reading platform insights after posting. Keep your own evidence in the series' research/analytics/.

Preflight

  • Install: Minimal is enough. No library needed.
  • Find the series folder and read its SERIES.md first. It holds the audience (who, level, regions to aim for and avoid), voice, palette and mascot notes, the visual style, the keyword log and what has worked so far. If it is missing, ask the user for those fields and write the file.
  • For a competitor study: yt-dlp, ffmpeg and any speech-to-text tool. For an autopsy: the platform's insights numbers from the user.

1. Topic

  • Re-skin proven winners. A topic that worked (for you or a competitor) in a new familiar format beats a new topic in a plain format. Example: a reel about running several AI agents as a council, remade as "a jury of 12 AIs puts your idea on trial".
  • The viewer must be able to use the outcome. If they can't do anything with it, skip it.
  • Something to give away: every winner promises a free skill, prompt, template, cheat sheet or setup by DM.
  • Speed on a hot repo. The first reel on a trending repo takes most of the views. Ship within a day or two, on an angle the earlier reels didn't use (../papercut-hook/references/hook-patterns.md).
  • Demand signals: competitor outliers (likes at 5x or more of their median), trending repos (stars per day), front-page threads, same-day launches. Save candidates to the series' idea backlog.

2. Format

Pick one familiar real-world format for the whole reel before writing a word: courtroom, pitch show, cooking show, heist movie, nature documentary, dating show, character-select screen, boss fight, job interview, Olympic podium. The viewer gets the premise in a second and every set and gag comes from it. A plain list of facts has no premise to grasp, so it gets less attention than the same facts told inside a format. The bank, with the story each format carries, is ../papercut-script/references/comedy.md.

3. Audience level

Write at the level SERIES.md sets. There is no default audience. The feeling to leave behind: you're not behind, and now you know something most people don't.

4. Funnel and caption

  • Spoken CTA: "Good thing I made [freebie]. For the link, comment KEYWORD." One short keyword tied to the topic.
  • Deliver the freebie by DM with whatever comment-to-DM tooling the account allows. Keep sends slow and spaced, because platforms rate-limit bursts.
  • Caption: the hook as the first line, a follow line so the DM lands, "READ BELOW" with the useful part written out, one send prompt ("Send this to the friend who..."), 3-5 hashtags.
  • Shares matter most to the algorithm. A funny or useful reel gets sent.

5. Write the BRIEF

Put this block at the top of episodes/NN-slug/research/facts.md. papercut-hook and papercut-script read it.

BRIEF
Source:   <link(s)>
Claim:    <the one claim the video proves>
Role:     <who or what does the work vs who advises or approves>
Mode:     open-source drop | news launch / worth-it | feature unlock
Format:   <the one familiar format>
Audience: <level, copied from SERIES.md>
CTA:      <KEYWORD> -> <the freebie>
Length:   22-30 s

6. Competitor study (when the user shares reels)

Method, setup and the subagent prompt: references/competitor-analysis.md.

  • One subagent per reel, up to 4 at a time. Each downloads the reel, extracts frames at 2 fps, transcribes it, applies the six-question hook check and returns a fixed-format report.
  • Synthesise into a comparison table (likes and comments vs the creator's typical reel, age at fetch, look, length), what drove the outliers, what to borrow and what stays your difference.
  • Save it to research/analytics/YYYY-MM-DD-<creator>-reels.md. One reel is noise; look for a pattern across 4 or more.

7. After posting: the autopsy

  • At about 2 h and 24 h collect views, skip rate, average watch time, the retention curve, likes, comments, saves, shares, follows, traffic source, top countries and ages.
  • Read them in this order: hook, topic, format, audience, timing. Fix the earliest thing that failed before touching later ones.
  • If most viewers are gone by 3-5 s, or the skip rate is clearly worse than your own median, the hook failed. Run papercut-hook.
  • Write research/analytics/YYYY-MM-DD-autopsy.md and update SERIES.md with what changed.

Gate

  • SERIES.md read; audience, regions and voice respected.
  • Topic has a demand signal, a usable outcome and a freebie by DM.
  • One format named in a line.
  • Vocabulary and the DM match the audience level.
  • BRIEF written; caption planned.

Hand-off

Next is papercut-hook. It reads the BRIEF in episodes/NN-slug/research/facts.md and writes the HOOK block at the top of episodes/NN-slug/papercut/STORYBOARD.md. If the episode folder isn't scaffolded yet, create research/ and papercut/ by hand; papercut-build merges them when it scaffolds.

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 Papercut Strategy AI skill do?

Decide what a papercut reel should be. Picks the topic, one familiar format, the audience level, the comment-keyword funnel and caption, studies competitor reels, and runs the post-publish autopsy. Use before any hook or script, or when reviewing how a posted reel did.

Why use Papercut Strategy on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/0xS4N4TG/papercut-explainer/tree/main/skills/papercut-strategy. 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 Papercut Strategy?

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 Strategy?

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

Is the Papercut Strategy 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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