cheat-on-content README

The project's README from github.com/XBuilderLAB/cheat-on-content. As one markdown file: README.md.

Cheat on Content

Cheat on Content

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For content creators — a skill that turns every post into a calibrated experiment.

You're reading this. The skill predicted it.
It turns every "I feel this will go viral" into a calibrated experiment.
It took me from zero to 1M followers in a month. It said I'd write this. I did.
Your doubt — predicted too.

🎬 What it actually does

Most creators live in the same gambling loop:

Publish → Numbers come in → Learn nothing → Roll the dice again

A creator who's shipped 200 pieces is barely 10% sharper than someone who's shipped 1 — because they never kept books after each round.

Cheat on Content makes every judgment get logged, retrospected, absorbed into the next:

📊 Score → 🎯 Blind-predict → 🚀 Publish → 📈 T+3d retro → 🧬 Evolve your rubric

This isn't motivation. It's compounding — every piece you don't retro is silently eroding your ability to see yourself.

One month in = you have a hit-formula that's only yours. Three months in = you're 10× sharper than your first-day self.

🌀 Origin

I never believed in fate. Until this skill made me film a video — and predicted exactly how much traffic that video would pull.

I tried to break it. I told my audience. I hoped collective observation would collapse the wave function and shift the trajectory.

The data was accurate.

I didn't escape fate. I just moved from first-order to second-order.

If even my awakening — even my audience's observation — was already in its prediction, then right now, reading this: are you here out of curiosity, or just closing the algorithm's last move?

— the creator

⚖️ How it differs from other "creator tools"

Others This
Give you "inspiration" Make your own intuition measurable
AI writes for you AI judges for you — the script stays yours
Ship 10 versions, A/B test Ship one — bet in writing, settle the books with data
Static dashboard An evolving rubric — your formula 3 months from now isn't the starting one

In a sentence: other tools help you "ship more." This helps you "judge sharper."

🤔 Can't I just use ChatGPT / DeepSeek / Doubao?

Those are general assistants — they tell everyone the same thing. You ask "will this go viral?" and the answer is fitted to global average opinion, not your channel. Ask again tomorrow — same answer. It doesn't remember you. It doesn't change because of you.

This is your own ops expert — serving only your one channel:

General LLMs help everyone. This helps your account.

🛡️ Why the loop actually evolves

📝 Every piece is logged: Score and prediction get written before publish, archived end-to-end. Three days later you settle accounts — you see exactly where you were sharp, where you were off. No more vague "I feel this one didn't land."

🔁 It gets sharper: Three same-direction misses in a row, the tool actively prompts you to upgrade your scoring formula. You don't have to remember — it remembers for you.

🛡️ Upgrades have a brake: Switching the formula requires re-scoring all historical samples — only released if it ranks more accurately than the old. Plus a cross-model independent audit — so you can't fool yourself.

🪒 The rubric is a workbench, not a museum: Observations refuted by data get deleted; observations absorbed into formal dimensions also get deleted. It only holds what's most useful right now.

📦 Install

git clone https://github.com/XBuilderLAB/cheat-on-content.git
cd cheat-on-content
bash install.sh

⚠️ Upgrading from v0.x? Run /cheat-migrate in your content project after git pull. The 1.3 → 1.4 migration is BREAKING for blind-channel integrity — it splits rubric_notes.md so the blind sub-agent can't leak actuals. Without migrate, blind scoring will keep flagging non_blind_warning. See CHANGELOG and migrations/1.3-to-1.4.md.

14 sub-skills are symlinked into your agent's skill directory. One install, every content project gets it.

Supported agents: Claude Code (default) · Codex (bash install.sh --codex) · Both (bash install.sh --all)

Frozen version: bash install.sh --copy / bash install.sh --codex --copy

Uninstall: bash uninstall.sh / bash uninstall.sh --codex (your content data is not touched)

🚀 First run

In your content project directory, open a skill-compatible agent and say:

初始化 cheat-on-content

(or init cheat-on-content)

Five yes/no questions complete onboarding. Strongly recommend importing a benchmark account — 5–10 samples and the tool gets an anchor immediately. Without one, your first 5 predictions land at ±50% precision.

⚡ Daily use

score this scripts/<...>.md       → grade only
start prediction scripts/<...>.md → blind prediction + decision log
shot scripts/<...>.md             → create video folder + buffer +1
shipped https://...                → buffer -1
retro videos/<...>/                → T+3d data + retrospective
status / fetch trends / find topic / bump rubric / find benchmark

Hook-aware agents auto-report buffer + pending retros + top candidates at every session start — no need to ask. Other agents: just say status.

Full workflow + sub-skill details: see SKILL.md.

📈 Star History

Star History Chart

📜 License

MIT. Commercial use, modification, closed-source integration — all fine.

Is this cheating? So was the calculator. So was Google. The future doesn't reward effort — it rewards those who see the pattern first.

You reading this line — that's predicted too.

cheat-on-content (XBuilderLAB/cheat-on-content)

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7.3K ·GitHub
Cheat-on-content
What is this?A skill for AI coding agents aimed at content creators: every post becomes a calibrated experiment — score it, blind-predict its performance, publish, retro the numbers at T+3 days, and evolve your scoring rubric. The author credits it with going from 0 to 1M followers in a month.
So is it a standalone app, or something that lives inside my AI agent?It lives inside your AI agent, not as a separate app: the installer symlinks 14 sub-skills into the agent's skill directory, and one install covers every content project you run.
How do I set it up and start using it?Run bash install.sh from the repo, then open a skill-compatible agent inside your content project and say 'init cheat-on-content' — five yes/no questions finish onboarding.
Which coding agents can run it?Claude Code works by default, Codex via bash install.sh --codex, or both via --all. Hook-aware agents auto-report buffer and pending retros at each session start; with other agents you just say 'status'.
Will its predictions be any good when I'm just starting out?Cold start is the catch: without an imported benchmark account (5–10 samples) your first 5 predictions land at ±50% precision. Also, the 1.3 to 1.4 upgrade is a breaking migration — run /cheat-migrate after git pull or blind scoring keeps flagging nonblindwarning.
Who is this for, and do I need to be a developer to use it?Content creators who publish regularly and want their intuition made measurable rather than motivated. You do need a coding agent like Claude Code or Codex and a terminal for the bash install, so some comfort with developer tooling helps.
Does my operating system matter for this?Only in that your coding agent must run there — the project targets Linux, macOS and Windows.
Is it free to use, even commercially?Yes — MIT license, and commercial use, modification and closed-source integration are all explicitly allowed.
How is this different from just asking ChatGPT if my post will go viral?General assistants answer from the global average and forget you after the reply. This builds a scoring formula reverse-engineered from your channel's own history, updates it with every post, and remembers your benchmark account, cadence and last three flops.
What does one full cycle of using it look like?You score the piece and log a blind prediction before publishing, then settle the books against real numbers three days later. The loop is score → blind-predict → publish → T+3d retro → evolve, and three same-direction misses in a row prompt you to upgrade your formula.
How does it stop me from fooling myself with wishful scoring?Formula switches force a re-score of all historical samples and only ship if the new rubric ranks more accurately than the old one, plus a cross-model independent audit. Observations refuted by data get deleted, so the rubric only keeps what works right now.
If I uninstall it, do I lose my logged predictions?No — bash uninstall.sh (or bash uninstall.sh --codex) removes the skill from your agent, and your content data is not touched.
What are similar projects?cy-carousel-skill, marketing-agi, linkedin-agent-skill, dbskill, youtube-agent-skill, linkedin-skills, no-ai-slop, codex-ppt-skill
Which topics is it in?forecasting, decision-making, social-media, content-creation, analytics, agent-skill, evaluation, workflow, skill, productivity, codex, claude-code
Creator
XBuilderLAB
Size
0.5 MB
Stars
7.3K
Updated
CommitOct 12
Age
5mo
Commits · 90 Days