Probability Mean Reversion logo

Probability Mean Reversion

Organization
Superior-Trade
probability-mean-reversion

Use when a Polymarket outcome appears to overreact and then stall away from recent filled-price range.

Overview

PublisherSuperior-Trade
Repositorysuperior-skills
Skill nameprobability-mean-reversion
Stars
215
Forks
9
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 Superior-Trade on GitHub. Read the source before you install it.

Installation

Install the Probability Mean Reversion 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/Superior-Trade/superior-skills/tree/main/skills/probability-mean-reversion
  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/Superior-Trade/superior-skills.git /tmp/superior-skills
mkdir -p .claude/skills
cp -r /tmp/superior-skills/skills/probability-mean-reversion .claude/skills/probability-mean-reversion
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Probability Mean Reversion 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 Probability Mean Reversion 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 Probability Mean Reversion 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.

Strategy: Polymarket · Probability Mean Reversion

When to use

Use this when someone asks for fade, overreaction, mean reversion, range trading, panic buy, euphoria selloff, or probability jumps with weak follow-through.

What the agent should look for

  • Canonical Polymarket market from GET /context/markets?venue=polymarket.
  • A stable market with enough historical fills.
  • Probability significantly far from a rolling median.
  • Weak follow-through after the jump.
  • No fresh catalyst changing the thesis.
  • Enough time before resolution to allow drift back.

Backtest fit with filled data

Moderate fit. Filled TradeTick history can test whether probability moves have a measurable reversion pattern, while using actual fills as the execution proxy.

Limit: backtests cannot validate resting liquidity, spread paid, or what is missed in the maker queue.

Strategy logic

Enter when the outcome trades below a lower band and exit near the rolling median. If your implementation permits, do the inverse for above-band conditions when downside overextension appears.

Nautilus strategy shape

  • Keep a rolling window of trade prices.
  • Compute median and deviation thresholds.
  • Enter only after sufficient tick history is collected.
  • Exit on median reversion or max holding ticks.

Example strategyConfig

json
{
  "window_ticks": 40,
  "entry_deviation": 0.08,
  "exit_deviation": 0.02,
  "order_size": 10,
  "max_holding_ticks": 80
}

Iteration knobs

KnobEffect
window_ticksLarger windows produce a smoother baseline.
entry_deviationHigher values wait for stronger overreactions.
exit_deviationLower values demand tighter reversion before exit.
max_holding_ticksPrevents stale positions through stale conditions.

Failure modes

  1. Real information shocks rarely mean-revert.
  2. Markets near resolution can trend cleanly to 0 or 1.
  3. Low liquidity can create fake extremes.
  4. Backtests may look strong when spread and order-book pressure are ignored.

User-facing framing

"This is an overreaction fade. It works best in noisy markets without new decisive information. I’ll backtest it on filled prices first, then verify trade frequency and liquidity before suggesting live use."

Frequently asked questions

What does the Probability Mean Reversion AI skill do?

Use when a Polymarket outcome appears to overreact and then stall away from recent filled-price range.

Why use Probability Mean Reversion on TypingMind?

Because you install it once and use it with any model. Probability Mean Reversion 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 Probability Mean Reversion in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Superior-Trade/superior-skills/tree/main/skills/probability-mean-reversion. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Probability Mean Reversion?

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 Probability Mean Reversion?

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

Is the Probability Mean Reversion AI skill free?

Yes. It is published on GitHub by Superior-Trade 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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