Open‑source DOE indicators push SMC tools into wider use among traders
Two recently posted open‑source scripts using the DOE label have drawn attention for packaging Smart Money Concepts (SMC) workflows — including Fair Value Gap (FVG) retests and order‑block detection — into user‑friendly indicators and a strategy. The creators emphasize transparency and free access, while cautioning that reuse of code is limited by the host site's rules.
What the DOE tools do
The release consists of a pair of scripts: one that focuses on a high‑probability SMC setup combining Market Structure Shifts (MSS) and FVG retests, and another that builds a broader SMC strategy with ICT‑style order blocks and FVG detection tailored for cryptocurrency markets. Both scripts are open source, enabling traders to inspect the codebase, tweak parameters and test logic before applying them in live conditions.
Core features described by the authors include automatic identification of MSS events, highlighted FVG zones where price could retest, and graphical marking of order blocks to flag potential liquidity areas. The strategy script includes configurable rules for entries, stop placement and position sizing aimed at Bitcoin markets, while the indicator version is positioned as a reusable tool for multi‑instrument charting.
Authors note the scripts are free to use for personal testing and research. At the same time, they remind users that republishing the code or redistributing modified versions is constrained by the hosting site's house rules. That mix of accessibility and controlled redistribution is meant to both encourage community inspection and protect author rights.
Practical implications for traders
For discretionary and systematic traders alike, DOE brings a few practical benefits. First, packaging SMC workflows into a visible indicator lowers the barrier to entry for newcomers who want to learn how MSS and FVG interplay on price charts. Second, an open‑source strategy allows more advanced users to backtest the approach, modify logic and integrate it into larger systems.
Users should treat the DOE scripts as starting points rather than finished systems. Key tasks before live deployment include parameter optimization across timeframes and instruments, walk‑forward testing to check robustness, and simulated execution checks to account for slippage and latency. The strategy variant for Bitcoin includes built‑in rules for entries and stops, but real market conditions often require manual oversight, especially around major macro events and low‑liquidity sessions.
Authors also emphasize verification. Because the code is open, traders can verify how the indicator defines FVGs, how it identifies structure shifts and how order blocks are constructed — details that materially affect signals and outcomes. That transparency can reduce surprise from hidden assumptions baked into black‑box tools.
Risks, next steps and community response
Open‑source visibility does not eliminate risk. Models that look robust on historical charts can fail when market regimes change. Traders should therefore use conservative sizing when first applying DOE tools, keep clear stop disciplines and combine indicator signals with broader risk management frameworks.
The initial reception in trading circles has emphasized appreciation for open code and modular design. Community members are already proposing forks, enhanced backtest harnesses and visual refinements, though reuse of code will need to follow the stated redistribution rules. For those interested in experimenting, the recommended approach is to clone the codebase locally, run it through representative historical data and iterate with strict version control.
As of Feb. 16, 2026 ET, the DOE scripts remain available for inspection and testing. Traders who adopt them should document changes, retain version histories and treat any live deployment as an experiment until consistent out‑of‑sample performance is established.
