Repository Analysis

freqtrade/freqtrade-strategies

Free trading strategies for Freqtrade bot

64.7 Strong AI signal View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of freqtrade/freqtrade-strategies, a Python project with 5,357 GitHub stars. SynthScan v2.0 examined 10,427 lines of code across 76 source files, recording 360 pattern matches distributed across 11 syntactic categories. The overall adjusted score of 64.7 places this repository in the Strong AI signal band.

The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).

64.7
Adjusted Score
64.7
Raw Score
100%
Time Factor
2026-08-12
Last Push
5.4K
Stars
Python
Language
10.4K
Lines of Code
76
Files
360
Pattern Hits
2026-08-13
Scan Date
0.45
HC Hit Rate

What These Metrics Mean

Adjusted Score
Primary synthetic code indicator. Raw score normalised per 1,000 lines of code and multiplied by the temporal discount factor. This is the definitive comparative metric — use it to rank repositories by AI authorship density.
Raw Score
The unmodified sum of all severity-weighted, context-multiplied pattern match scores before temporal discounting. Reflects the absolute signal strength independent of when the repository was last active.
Time Factor
The temporal discount multiplier (0–100%) applied to the raw score. Repositories last updated before ChatGPT's launch (Nov 2022) receive a 5% factor. Full signal is only assigned to repositories active in the post-adoption era (Jan 2024+).
Pattern Hits
Total count of individual pattern matches across all files and categories. A high hit count with a low score may indicate a very large codebase with isolated AI snippets; a low count with a high score indicates dense, concentrated AI signatures.
HC Hit Rate
High+Critical pattern hits per file, averaged across the repository. This orthogonal signal catches repositories where a few files are densely packed with high-severity AI tells — a strong indicator even when the normalised score appears moderate due to codebase size.
Lines of Code / Files
Total lines and files analysed. The scanner examines 94 file extensions. These denominators are used to normalise the score, enabling fair comparison between repositories of vastly different sizes.

Score History

Longitudinal tracking requires multiple scan runs. Once this repository is re-scanned after new commits land, this chart will visualise how the synthetic code signal evolves over time — enabling you to detect whether AI authorship is growing, stabilising, or being actively corrected by human engineers.

No multi-scan history yet — run the scanner again to build trend data.

Severity Breakdown

Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.

CRITICAL 0HIGH 34MEDIUM 78LOW 248

Directory Score Breakdown

This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.

Pattern Findings

The scanner identified 360 distinct pattern matches across 11 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.

Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.

Unused Imports212 hits · 212 pts
SeverityFileLineSnippetContext
LOWuser_data/hyperopts/GodStraHo.py13CODE
LOWuser_data/hyperopts/GodStraHo.py22CODE
LOWuser_data/hyperopts/GodStraHo.py23CODE
LOWuser_data/strategies/SwingHighToSky.py14CODE
LOWuser_data/strategies/SwingHighToSky.py18CODE
LOWuser_data/strategies/SwingHighToSky.py19CODE
LOWuser_data/strategies/hlhb.py3CODE
LOWuser_data/strategies/hlhb.py4CODE
LOWuser_data/strategies/InformativeSample.py4CODE
LOWuser_data/strategies/InformativeSample.py4CODE
LOWuser_data/strategies/InformativeSample.py5CODE
LOWuser_data/strategies/InformativeSample.py10CODE
LOWuser_data/strategies/Diamond.py48CODE
LOWuser_data/strategies/Strategy001_custom_exit.py4CODE
LOWuser_data/strategies/Strategy001_custom_exit.py4CODE
LOWuser_data/strategies/Strategy001_custom_exit.py5CODE
LOWuser_data/strategies/FixedRiskRewardLoss.py4CODE
LOWuser_data/strategies/FixedRiskRewardLoss.py5CODE
LOWuser_data/strategies/FixedRiskRewardLoss.py13CODE
LOWuser_data/strategies/FixedRiskRewardLoss.py15CODE
LOWuser_data/strategies/Bandtastic.py2CODE
LOWuser_data/strategies/Bandtastic.py3CODE
LOWuser_data/strategies/Bandtastic.py7CODE
LOWuser_data/strategies/Bandtastic.py7CODE
LOWuser_data/strategies/Heracles.py20CODE
LOWuser_data/strategies/Heracles.py23CODE
LOWuser_data/strategies/Heracles.py25CODE
LOWuser_data/strategies/Strategy004.py4CODE
LOWuser_data/strategies/Strategy004.py4CODE
LOWuser_data/strategies/Strategy004.py5CODE
LOWuser_data/strategies/multi_tf.py1CODE
LOWuser_data/strategies/multi_tf.py2CODE
LOWuser_data/strategies/multi_tf.py5CODE
LOWuser_data/strategies/multi_tf.py7CODE
LOWuser_data/strategies/multi_tf.py8CODE
LOWuser_data/strategies/multi_tf.py11CODE
LOWuser_data/strategies/CustomStoplossWithPSAR.py4CODE
LOWuser_data/strategies/CustomStoplossWithPSAR.py5CODE
LOWuser_data/strategies/CustomStoplossWithPSAR.py13CODE
LOWuser_data/strategies/CustomStoplossWithPSAR.py15CODE
LOWuser_data/strategies/MultiMa.py13CODE
LOWuser_data/strategies/Strategy001.py4CODE
LOWuser_data/strategies/Strategy001.py4CODE
LOWuser_data/strategies/Strategy001.py5CODE
LOWuser_data/strategies/PowerTower.py5CODE
LOWuser_data/strategies/PowerTower.py6CODE
LOWuser_data/strategies/PowerTower.py8CODE
LOWuser_data/strategies/PowerTower.py9CODE
LOWuser_data/strategies/PowerTower.py9CODE
LOWuser_data/strategies/PowerTower.py11CODE
LOWuser_data/strategies/PowerTower.py11CODE
LOWuser_data/strategies/PowerTower.py11CODE
LOWuser_data/strategies/PowerTower.py11CODE
LOWuser_data/strategies/PowerTower.py16CODE
LOWuser_data/strategies/PowerTower.py17CODE
LOWuser_data/strategies/PowerTower.py18CODE
LOWuser_data/strategies/Strategy002.py4CODE
LOWuser_data/strategies/Strategy002.py4CODE
LOWuser_data/strategies/Strategy002.py5CODE
LOWuser_data/strategies/GodStra.py13CODE
152 more matches not shown…
Decorative Section Separators62 hits · 192 pts
SeverityFileLineSnippetContext
MEDIUMuser_data/hyperopts/GodStraHo.py19# --------------------------------COMMENT
MEDIUMuser_data/strategies/hlhb.py92 # ------------------------------------COMMENT
MEDIUMuser_data/strategies/InformativeSample.py7# --------------------------------COMMENT
MEDIUMuser_data/strategies/Diamond.py45# --------------------------------COMMENT
MEDIUMuser_data/strategies/Strategy001_custom_exit.py7# --------------------------------COMMENT
MEDIUMuser_data/strategies/FixedRiskRewardLoss.py10# --------------------------------COMMENT
MEDIUMuser_data/strategies/BreakEven.py5# --------------------------------COMMENT
MEDIUMuser_data/strategies/HourBasedStrategy.py13# --------------------------------COMMENT
MEDIUMuser_data/strategies/Heracles.py17# --------------------------------COMMENT
MEDIUMuser_data/strategies/Strategy004.py7# --------------------------------COMMENT
MEDIUMuser_data/strategies/mabStra.py9# --------------------------------COMMENT
MEDIUMuser_data/strategies/CustomStoplossWithPSAR.py10# --------------------------------COMMENT
MEDIUMuser_data/strategies/MultiMa.py9# --------------------------------COMMENT
MEDIUMuser_data/strategies/Strategy005.py7# --------------------------------COMMENT
MEDIUMuser_data/strategies/Strategy005.py135 # ------------------------------------COMMENT
MEDIUMuser_data/strategies/Strategy001.py7# --------------------------------COMMENT
MEDIUMuser_data/strategies/PowerTower.py14# --------------------------------COMMENT
MEDIUMuser_data/strategies/Strategy002.py7# --------------------------------COMMENT
MEDIUMuser_data/strategies/GodStra.py28# --------------------------------COMMENT
MEDIUMuser_data/strategies/Strategy003.py7# --------------------------------COMMENT
MEDIUMuser_data/strategies/PatternRecognition.py12# --------------------------------COMMENT
MEDIUMuser_data/strategies/UniversalMACD.py14# --------------------------------COMMENT
MEDIUMuser_data/strategies/futures/FReinforcedStrategy.py18# --------------------------------COMMENT
MEDIUMuser_data/strategies/futures/FAdxSmaStrategy.py18# --------------------------------COMMENT
MEDIUMuser_data/strategies/futures/FSampleStrategy.py17# --------------------------------COMMENT
MEDIUMuser_data/strategies/futures/FSampleStrategy.py89 # ------------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/Quickie.py6# --------------------------------COMMENT
MEDIUM…data/strategies/berlinguyinca/ReinforcedSmoothScalp.py9# --------------------------------COMMENT
MEDIUM…_data/strategies/berlinguyinca/ASDTSRockwellTrading.py7# --------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/CMCWinner.py5# --------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/SmoothScalp.py6# --------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/SmoothScalp.py12# --------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/BinHV27.py5# --------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/BinHV27.py12# --------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/Scalp.py6# --------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/ClucMay72018.py6# --------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/ClucMay72018.py13# --------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/AwesomeMacd.py8# --------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/ADXMomentum.py7# --------------------------------COMMENT
MEDIUM…linguyinca/Freqtrade_backtest_validation_freqtrade1.py9# --------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/MACDStrategy.py6# --------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/Low_BB.py6# --------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/Low_BB.py13# --------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/AdxSmas.py8# --------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/AverageStrategy.py6# --------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/BbandRsi.py8# --------------------------------COMMENT
MEDIUM…_data/strategies/berlinguyinca/MACDStrategy_crossed.py7# --------------------------------COMMENT
MEDIUM…r_data/strategies/berlinguyinca/DoesNothingStrategy.py4# --------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/BinHV45.py6# --------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/CCIStrategy.py6# --------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/MultiRSI.py4# --------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/ReinforcedQuickie.py6# --------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/ReinforcedQuickie.py13# --------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/Simple.py6# --------------------------------COMMENT
MEDIUM…/strategies/berlinguyinca/ReinforcedAverageStrategy.py6# --------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/CofiBitStrategy.py9# --------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/SmoothOperator.py6# --------------------------------COMMENT
MEDIUMuser_data/strategies/berlinguyinca/EMASkipPump.py5# --------------------------------COMMENT
MEDIUM…r_data/strategies/berlinguyinca/CombinedBinHAndCluc.py4# --------------------------------COMMENT
MEDIUMuser_data/strategies/lookahead_bias/wtc.py27# --------------------------------COMMENT
2 more matches not shown…
Cross-File Repetition34 hits · 170 pts
SeverityFileLineSnippetContext
HIGHuser_data/strategies/InformativeSample.py0define additional, informative pair/interval combinations to be cached from the exchange. these pair/interval combinatioSTRING
HIGHuser_data/strategies/Strategy001_custom_exit.py0define additional, informative pair/interval combinations to be cached from the exchange. these pair/interval combinatioSTRING
HIGHuser_data/strategies/Strategy004.py0define additional, informative pair/interval combinations to be cached from the exchange. these pair/interval combinatioSTRING
HIGHuser_data/strategies/Strategy005.py0define additional, informative pair/interval combinations to be cached from the exchange. these pair/interval combinatioSTRING
HIGHuser_data/strategies/Strategy001.py0define additional, informative pair/interval combinations to be cached from the exchange. these pair/interval combinatioSTRING
HIGHuser_data/strategies/Strategy002.py0define additional, informative pair/interval combinations to be cached from the exchange. these pair/interval combinatioSTRING
HIGHuser_data/strategies/Strategy003.py0define additional, informative pair/interval combinations to be cached from the exchange. these pair/interval combinatioSTRING
HIGH…_data/strategies/berlinguyinca/TDSequentialStrategy.py0define additional, informative pair/interval combinations to be cached from the exchange. these pair/interval combinatioSTRING
HIGHuser_data/strategies/InformativeSample.py0adds several different ta indicators to the given dataframe performance note: for the best performance be frugal on the STRING
HIGHuser_data/strategies/Strategy001_custom_exit.py0adds several different ta indicators to the given dataframe performance note: for the best performance be frugal on the STRING
HIGHuser_data/strategies/Strategy004.py0adds several different ta indicators to the given dataframe performance note: for the best performance be frugal on the STRING
HIGHuser_data/strategies/Strategy005.py0adds several different ta indicators to the given dataframe performance note: for the best performance be frugal on the STRING
HIGHuser_data/strategies/Strategy001.py0adds several different ta indicators to the given dataframe performance note: for the best performance be frugal on the STRING
HIGHuser_data/strategies/Strategy002.py0adds several different ta indicators to the given dataframe performance note: for the best performance be frugal on the STRING
HIGHuser_data/strategies/Strategy003.py0adds several different ta indicators to the given dataframe performance note: for the best performance be frugal on the STRING
HIGHuser_data/strategies/berlinguyinca/CMCWinner.py0adds several different ta indicators to the given dataframe performance note: for the best performance be frugal on the STRING
HIGHuser_data/strategies/InformativeSample.py0based on ta indicators, populates the sell signal for the given dataframe :param dataframe: dataframe :return: dataframeSTRING
HIGHuser_data/strategies/Strategy001_custom_exit.py0based on ta indicators, populates the sell signal for the given dataframe :param dataframe: dataframe :return: dataframeSTRING
HIGHuser_data/strategies/Strategy004.py0based on ta indicators, populates the sell signal for the given dataframe :param dataframe: dataframe :return: dataframeSTRING
HIGHuser_data/strategies/Strategy005.py0based on ta indicators, populates the sell signal for the given dataframe :param dataframe: dataframe :return: dataframeSTRING
HIGHuser_data/strategies/Strategy001.py0based on ta indicators, populates the sell signal for the given dataframe :param dataframe: dataframe :return: dataframeSTRING
HIGHuser_data/strategies/Strategy002.py0based on ta indicators, populates the sell signal for the given dataframe :param dataframe: dataframe :return: dataframeSTRING
HIGHuser_data/strategies/Strategy003.py0based on ta indicators, populates the sell signal for the given dataframe :param dataframe: dataframe :return: dataframeSTRING
HIGH…_data/strategies/berlinguyinca/ASDTSRockwellTrading.py0based on ta indicators, populates the sell signal for the given dataframe :param dataframe: dataframe :return: dataframeSTRING
HIGHuser_data/strategies/berlinguyinca/CMCWinner.py0based on ta indicators, populates the sell signal for the given dataframe :param dataframe: dataframe :return: dataframeSTRING
HIGHuser_data/strategies/berlinguyinca/ClucMay72018.py0based on ta indicators, populates the sell signal for the given dataframe :param dataframe: dataframe :return: dataframeSTRING
HIGHuser_data/strategies/berlinguyinca/MACDStrategy.py0based on ta indicators, populates the sell signal for the given dataframe :param dataframe: dataframe :return: dataframeSTRING
HIGHuser_data/strategies/berlinguyinca/Low_BB.py0based on ta indicators, populates the sell signal for the given dataframe :param dataframe: dataframe :return: dataframeSTRING
HIGHuser_data/strategies/berlinguyinca/AverageStrategy.py0based on ta indicators, populates the sell signal for the given dataframe :param dataframe: dataframe :return: dataframeSTRING
HIGH…_data/strategies/berlinguyinca/MACDStrategy_crossed.py0based on ta indicators, populates the sell signal for the given dataframe :param dataframe: dataframe :return: dataframeSTRING
HIGHuser_data/strategies/berlinguyinca/CCIStrategy.py0based on ta indicators, populates the sell signal for the given dataframe :param dataframe: dataframe :return: dataframeSTRING
HIGHuser_data/strategies/berlinguyinca/ReinforcedQuickie.py0based on ta indicators, populates the sell signal for the given dataframe :param dataframe: dataframe :return: dataframeSTRING
HIGH…/strategies/berlinguyinca/ReinforcedAverageStrategy.py0based on ta indicators, populates the sell signal for the given dataframe :param dataframe: dataframe :return: dataframeSTRING
HIGHuser_data/strategies/berlinguyinca/CofiBitStrategy.py0based on ta indicators, populates the sell signal for the given dataframe :param dataframe: dataframe :return: dataframeSTRING
Self-Referential Comments9 hits · 33 pts
SeverityFileLineSnippetContext
MEDIUMuser_data/strategies/multi_tf.py49 # This method is not required.COMMENT
MEDIUMuser_data/strategies/futures/FReinforcedStrategy.py26# This class is a sample. Feel free to customize it.COMMENT
MEDIUMuser_data/strategies/futures/FReinforcedStrategy.py53 # Define the guards spacesCOMMENT
MEDIUMuser_data/strategies/futures/FReinforcedStrategy.py57 # Define the parameter spacesCOMMENT
MEDIUMuser_data/strategies/futures/FAdxSmaStrategy.py24# This class is a sample. Feel free to customize it.COMMENT
MEDIUMuser_data/strategies/futures/FAdxSmaStrategy.py51 # Define the guards spacesCOMMENT
MEDIUMuser_data/strategies/futures/FAdxSmaStrategy.py55 # Define the parameter spacesCOMMENT
MEDIUMuser_data/strategies/futures/FSampleStrategy.py23# This class is a sample. Feel free to customize it.COMMENT
MEDIUMuser_data/strategies/berlinguyinca/CMCWinner.py13# This class is a sample. Feel free to customize it.COMMENT
Slop Phrases7 hits · 27 pts
SeverityFileLineSnippetContext
MEDIUMuser_data/hyperopts/GodStraHo.py26# you can change it and see the results...COMMENT
MEDIUMuser_data/strategies/Diamond.py17# of buy/sell signals, But you can add your indicators and addCOMMENT
MEDIUMuser_data/strategies/Diamond.py118 # you can add new indicators and enable them insideCOMMENT
MEDIUMuser_data/strategies/futures/FReinforcedStrategy.py26# This class is a sample. Feel free to customize it.COMMENT
MEDIUMuser_data/strategies/futures/FAdxSmaStrategy.py24# This class is a sample. Feel free to customize it.COMMENT
MEDIUMuser_data/strategies/futures/FSampleStrategy.py23# This class is a sample. Feel free to customize it.COMMENT
MEDIUMuser_data/strategies/berlinguyinca/CMCWinner.py13# This class is a sample. Feel free to customize it.COMMENT
Over-Commented Block15 hits · 15 pts
SeverityFileLineSnippetContext
LOWuser_data/strategies/Diamond.py1# 𝐼𝓉 𝒾𝓈 𝒟𝒾𝒶𝓂𝑜𝓃𝒹 𝒮𝓉𝓇𝒶𝓉𝑒𝑔𝓎.COMMENT
LOWuser_data/strategies/Diamond.py21# Author: @Mablue (Masoud Azizi)COMMENT
LOWuser_data/strategies/HourBasedStrategy.py1# Hour StrategyCOMMENT
LOWuser_data/strategies/HourBasedStrategy.py21 # SHIB/USDT, 1000$x1:100daysCOMMENT
LOWuser_data/strategies/Heracles.py1# Heracles Strategy: Strongest Son of GodStraCOMMENT
LOWuser_data/strategies/PowerTower.py21class PowerTower(IStrategy):COMMENT
LOWuser_data/strategies/PowerTower.py41 # "dry_run_wallet": 1000,COMMENT
LOWuser_data/strategies/GodStra.py1# GodStra StrategyCOMMENT
LOWuser_data/strategies/UniversalMACD.py21class UniversalMACD(IStrategy):COMMENT
LOWuser_data/strategies/UniversalMACD.py41 # "trading_mode": "spot",COMMENT
LOWuser_data/strategies/berlinguyinca/SmoothOperator.py101 dataframe['sma_fast'] = ta.SMA(dataframe, timeperiod=50, price='close')COMMENT
LOWuser_data/strategies/berlinguyinca/SmoothOperator.py121 # (dataframe['close'] > dataframe['open'])COMMENT
LOWuser_data/strategies/lookahead_bias/wtc.py1# WTC Strategy: WTC(World Trade Center Tabriz)COMMENT
LOWuser_data/strategies/lookahead_bias/wtc.py21#COMMENT
LOWuser_data/strategies/lookahead_bias/DevilStra.py1# DevilStra StrategyCOMMENT
Deep Nesting10 hits · 10 pts
SeverityFileLineSnippetContext
LOWuser_data/hyperopts/GodStraHo.py76CODE
LOWuser_data/hyperopts/GodStraHo.py148CODE
LOWuser_data/hyperopts/GodStraHo.py80CODE
LOWuser_data/hyperopts/GodStraHo.py152CODE
LOWuser_data/strategies/GodStra.py97CODE
LOWuser_data/strategies/GodStra.py140CODE
LOWuser_data/strategies/lookahead_bias/GodStraNew.py260CODE
LOWuser_data/strategies/lookahead_bias/GodStraNew.py328CODE
LOWuser_data/strategies/lookahead_bias/DevilStra.py335CODE
LOWuser_data/strategies/lookahead_bias/DevilStra.py403CODE
Structural Annotation Overuse3 hits · 7 pts
SeverityFileLineSnippetContext
LOW.github/ISSUE_TEMPLATE/strategy_request.md13## Step 1: What indicators are required?COMMENT
LOW.github/ISSUE_TEMPLATE/strategy_request.md17## Step 2: Explain the Buy StrategyCOMMENT
LOW.github/ISSUE_TEMPLATE/strategy_request.md22## Step 1: Explain the Sell StrategyCOMMENT
Modern Structural Boilerplate4 hits · 4 pts
SeverityFileLineSnippetContext
LOWuser_data/strategies/TrendRiderStrategy.py19logger = logging.getLogger(__name__)CODE
LOWuser_data/strategies/FixedRiskRewardLoss.py18logger = logging.getLogger(__name__)CODE
LOWuser_data/strategies/AlmgrenChrissStrategy.py10logger = logging.getLogger(__name__)CODE
LOWuser_data/strategies/multi_tf.py13logger = logging.getLogger(__name__)CODE
AI Slop Vocabulary2 hits · 3 pts
SeverityFileLineSnippetContext
LOWuser_data/strategies/Diamond.py16# It is just use the pure dataframe ohlcv data for calculationCOMMENT
LOWuser_data/strategies/HourBasedStrategy.py3# Because of that you should just use 1h timeframe on this strategy.COMMENT
Hyper-Verbose Identifiers2 hits · 2 pts
SeverityFileLineSnippetContext
LOWuser_data/strategies/berlinguyinca/SmoothOperator.py275 def four_green_one_red_candle(dataframe):CODE
LOWuser_data/strategies/berlinguyinca/SmoothOperator.py291 def four_red_one_green_candle(dataframe):CODE