Agent skill

Bollinger Reverter 4h

by Superior-Trade in Superior-Trade/superior-skills

A skill your agent uses when writing a symmetric Bollinger-band mean-reversion strategy on the 4h timeframe — BB reverter, range trader, chop strategy, ADX<25 mean reversion, band-fade with a…

MITAuto-check passedBusiness, Finance & HR

Install Bollinger Reverter 4h

skills CLI
$ npx skills add Superior-Trade/superior-skills --skill bollinger-reverter-4h -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Superior-Trade/superior-skills bollinger-reverter-4h --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Superior-Trade/superior-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/bollinger-reverter-4h .claude/skills/bollinger-reverter-4h && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
bollinger-reverter-4h
GitHub stars
215
Token cost
~1.8k tokens
SKILL.md length
542 words
Files
1
Skills in repo
31
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when writing a symmetric Bollinger-band mean-reversion strategy on the 4h timeframe — BB reverter, range trader, chop strategy, ADX<25 mean reversion, band-fade with a…

  • Writing a symmetric Bollinger-band mean-reversion strategy on the 4h timeframe — BB reverter
  • SKILL.md covers Backtest evidence, Thesis, Mechanics and Full strategy code, plus 6 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • ADX<25 mean reversion

What it does

Bollinger Reverter 4h is an agent skill from Superior-Trade/superior-skills. Use when writing a symmetric Bollinger-band mean-reversion strategy on the 4h timeframe — BB reverter, range trader, chop strategy, ADX<25 mean reversion, band-fade with a minimalroi ladder. Long-or-short on 2-sigma band touches with RSI confirmation. Validated on BTC/ETH/SOL/DOGE; numbers and the exact ROI ladder are in the body.

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Business, Finance & HR, covering Trading and backtesting. It works with Circle USDC. The repository describes itself as: Open agent skills and tool schemas for Superior Trade — build, backtest, and deploy trading strategies on Hyperliquid. The licence is MIT.

When your agent uses it

  • Writing a symmetric Bollinger-band mean-reversion strategy on the 4h timeframe — BB reverter
  • ADX<25 mean reversion
  • Band-fade with a minimalroi ladder

Example prompts

  • “/bollinger-reverter-4h”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit 9d41db5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are python and json).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Bollinger Reverter 4h loads about 1.8k tokens when it runs. Until then it costs about 89 tokens; SKILL.md has 542 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~89
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Superior-Trade/superior-skills at commit 9d41db5, republished under its MIT licence (© Superior-Trade). 542 words, ~1,778 tokens.

Download SKILL.mdSave it as .claude/skills/bollinger-reverter-4h/SKILL.md (or your agent's skills folder).
name
bollinger-reverter-4h
description
Use when writing a symmetric Bollinger-band mean-reversion strategy on the 4h timeframe — BB reverter, range trader, chop strategy, ADX<25 mean reversion, band-fade with a minimal_roi ladder. Long-or-short on 2-sigma band touches with RSI confirmation. Validated on BTC/ETH/SOL/DOGE; numbers and the exact ROI ladder are in the body.
metadata.version
0.1.0
metadata.updated
2026-05-18

Bollinger Reverter 4h

Symmetric mean-reversion strategy on the 4h timeframe. Long-or-short on band touches, gated to range regimes via ADX. Validated across BTC/ETH/SOL/DOGE over 162 days.

Searchable under: mean reversion, bollinger band, range trader, chop strategy, ADX filter.

Backtest evidence

ConfigTradesWin rateProfitMax DD
BTC/USDC:USDC, 162d1872.2%+8.14%10%
BTC/USDC:USDC, second-half / chop (80d)8100%+9.88%0%
BTC/USDC:USDC, first-half / strong bear (82d)1050%-1.75%10%
Multi-pair (BTC/ETH/SOL/DOGE), 162d8465.5%+8.77%18.5%

Per-pair breakdown (multi-pair 162d):

PairTradesWinProfit
BTC/USDC:USDC2972%+3.76%
ETH/USDC:USDC1974%+4.39%
SOL/USDC:USDC1560%+1.27%
DOGE/USDC:USDC2152%-0.65%

3 of 4 majors profitable, DOGE marginally negative. Generalizes well; not BTC-specific.

Thesis

When the market is range-bound (ADX < 25), price touching the upper or lower Bollinger Band is statistically likely to revert to the midline. Tight ROI ladder takes profit fast since mean-reversion targets are small; tight stop prevents the position from holding if the band touch turns into a trend break.

Mechanics

  • Pair: validated on majors; extend to any pair with sustained 24h volume > $50M
  • Timeframe: 4h
  • Indicators: 20-bar Bollinger Bands (2σ), RSI(14), ADX(14)
  • Entry short: close > upper_band AND RSI > 65 AND ADX < 25
  • Entry long: close < lower_band AND RSI < 35 AND ADX < 25
  • Exit short: close < bb_mid
  • Exit long: close > bb_mid
  • Stops: -2% hard stop
  • ROI ladder: 2.5% immediate, 1.5% after 4h, 0.5% after 12h, breakeven after 24h
  • No trailing stop (mean reversion targets are short — let ROI or signal-exit fire)

Full strategy code

python
from freqtrade.strategy import IStrategy
import pandas as pd
import talib.abstract as ta


class BollingerReverter4hStrategy(IStrategy):
    INTERFACE_VERSION = 3
    timeframe = "4h"
    can_short = True

    stoploss = -0.02
    trailing_stop = False

    minimal_roi = {
        "0": 0.025,    # take 2.5% immediately
        "240": 0.015,  # 1.5% after 4 hours (1 bar)
        "720": 0.005,  # 0.5% after 12 hours (3 bars)
        "1440": 0,     # breakeven after 24 hours
    }

    process_only_new_candles = True
    startup_candle_count = 60
    use_exit_signal = True

    def populate_indicators(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame:
        bb = ta.BBANDS(dataframe, timeperiod=20, nbdevup=2.0, nbdevdn=2.0)
        dataframe["bb_upper"] = bb["upperband"]
        dataframe["bb_mid"] = bb["middleband"]
        dataframe["bb_lower"] = bb["lowerband"]

        dataframe["rsi"] = ta.RSI(dataframe, timeperiod=14)
        dataframe["adx"] = ta.ADX(dataframe, timeperiod=14)
        return dataframe

    def populate_entry_trend(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame:
        cond_short = (
            (dataframe["close"] > dataframe["bb_upper"])
            & (dataframe["rsi"] > 65)
            & (dataframe["adx"] < 25)
        )
        dataframe.loc[cond_short, "enter_short"] = 1
        dataframe.loc[cond_short, "enter_tag"] = "bb_upper_revert"

        cond_long = (
            (dataframe["close"] < dataframe["bb_lower"])
            & (dataframe["rsi"] < 35)
            & (dataframe["adx"] < 25)
        )
        dataframe.loc[cond_long, "enter_long"] = 1
        dataframe.loc[cond_long, "enter_tag"] = "bb_lower_revert"
        return dataframe

    def populate_exit_trend(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame:
        dataframe.loc[dataframe["close"] < dataframe["bb_mid"], "exit_short"] = 1
        dataframe.loc[dataframe["close"] > dataframe["bb_mid"], "exit_long"] = 1
        return dataframe

Reference config (multi-pair)

json
{
  "exchange": {
    "name": "hyperliquid",
    "pair_whitelist": ["BTC/USDC:USDC", "ETH/USDC:USDC", "SOL/USDC:USDC", "DOGE/USDC:USDC"]
  },
  "stake_currency": "USDC",
  "stake_amount": 75,
  "dry_run_wallet": {"USDC": 350},
  "timeframe": "4h",
  "max_open_trades": 4,
  "minimal_roi": {"0": 100.0},
  "stoploss": -0.02,
  "trading_mode": "futures",
  "margin_mode": "isolated",
  "entry_pricing": {"price_side": "same", "price_last_balance": 0.0},
  "exit_pricing": {"price_side": "same", "price_last_balance": 0.0},
  "pairlists": [{"method": "StaticPairList"}]
}

Strategy-level minimal_roi overrides config-level — the ROI ladder is what makes this work.

Honest framing

The 100% second-half BTC win rate is partly small sample (8 trades). The full-period multi-pair result (+8.77%, 84 trades, 65.5% win) is the more credible expectation. Range-bound regimes are when this prints; in strong trends it modestly loses (-1.75% on BTC during the first-half strong bear) because band touches keep continuing rather than reverting.

In any window with mixed regimes, the strategy should be net positive because the chop periods dominate by count.

The DOGE result (-0.65%) is the failure case — meme-coin volatility breaks more bands than reverts to them. Use this strategy on majors, not meme pairs.

Show full SKILL.md (179 more words)Show less

Tunables

ParameterRangeEffect
BB period18 - 24Length of mean-reversion window
BB σ1.8 - 2.5Wider = rarer signals, deeper reversion
RSI confirmation60-70 / 30-40Confirms exhaustion at band edge
ADX cutoff20 - 30Below = range regime; above = trend (skip)
ROI tier 00.020 - 0.030Initial take-profit
Stop-0.015 to -0.025Tight enough that one trend break doesn't erase the lifetime edge

Known failure modes

  • Regime transition: when chop turns into trend mid-trade, the band-touch-revert signal becomes a band-break-continuation. Stops should fire fast; this is what the -2% stop is for
  • Meme/low-cap pairs: bands break more than they revert. Restrict to majors
  • News spikes: a sudden 5%+ move blows through multiple bands; the stop will fire but execution slippage hurts. Consider pausing during scheduled macro events

Pairing

  • Designed to coexist with donchian-strong-regime — they fire on mutually exclusive regimes (ADX < 25 here, regime-strong gate there)
  • Supersedes the prior 1h variant of mean-reversion

Deployment recommendation

Run as its own sub-account with stake_amount sized so 4× max_open_trades fits within the wallet plus 1.5× buffer. Multi-pair allocation across BTC/ETH/SOL is the validated default.

© Superior-Trade, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/bollinger-reverter-4h of Superior-Trade/superior-skills.

Open the folder on GitHubat commit 9d41db5

Compare with similar skills

Bollinger Reverter 4h next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Works with

Questions about Bollinger Reverter 4h

What does Bollinger Reverter 4h do?

A skill your agent uses when writing a symmetric Bollinger-band mean-reversion strategy on the 4h timeframe — BB reverter, range trader, chop strategy, ADX<25 mean reversion, band-fade with a…. Bollinger Reverter 4h is an agent skill from Superior-Trade/superior-skills. Use when writing a symmetric Bollinger-band mean-reversion strategy on the 4h timeframe — BB reverter, range trader, chop strategy, ADX<25 mean reversion, band-fade with a minimalroi ladder.

When should I use Bollinger Reverter 4h?

Bollinger Reverter 4h fits situations like: writing a symmetric Bollinger-band mean-reversion strategy on the 4h timeframe — BB reverter; ADX<25 mean reversion; band-fade with a minimalroi ladder.

How do I install Bollinger Reverter 4h in Claude Code?

Run `npx skills add Superior-Trade/superior-skills --skill bollinger-reverter-4h -a claude-code`. Or copy the skill folder (skills/bollinger-reverter-4h in Superior-Trade/superior-skills) into .claude/skills/bollinger-reverter-4h in your project. Claude Code loads it when a task matches its description.

How do I install Bollinger Reverter 4h in Codex?

Run `npx skills add Superior-Trade/superior-skills --skill bollinger-reverter-4h -a codex`. Or copy the skill folder (skills/bollinger-reverter-4h in Superior-Trade/superior-skills) into .agents/skills/bollinger-reverter-4h in your project. Codex loads it when a task matches its description.

Can I use Bollinger Reverter 4h in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Superior-Trade/superior-skills --skill bollinger-reverter-4h -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/bollinger-reverter-4h, .gemini/skills/bollinger-reverter-4h, .github/skills/bollinger-reverter-4h and .opencode/skills/bollinger-reverter-4h in your project.

What does Bollinger Reverter 4h need to run?

SKILL.md names no scripts, command-line tools or credentials: Bollinger Reverter 4h is instructions for the agent only. Our summary lists: Python 3.

Does Bollinger Reverter 4h access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Bollinger Reverter 4h safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Bollinger Reverter 4h use?

Bollinger Reverter 4h is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Bollinger Reverter 4h use?

About 1.8k tokens (SKILL.md is roughly 7.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Bollinger Reverter 4h?

Skills that share tags, products or a category with Bollinger Reverter 4h: Polymarket Trading (BlockRunAI/ClawRouter, 6.6k stars), Solana Payments Wallets Trading (npc-live/clawfirm, 156 stars), Nansen Trading (nansen-ai/nansen-cli, 139 stars) and Shipp Sports Data (moonpay/skills, 113 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Bollinger Reverter 4h?

Superior-Trade (a GitHub organization) maintains it in Superior-Trade/superior-skills, which has 215 GitHub stars. The repository holds 31 skills in this directory. The repository was last updated on September 10, 2026.

Source: Superior-Trade/superior-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.