Freqtrade kiploks integration is the bridge between "I have a backtest" and "I have a structured robustness review." People search send freqtrade results to kiploks and freqtrade backtest analysis tool because they want a repeatable pipeline, not a one-off screenshot.

Exact UI steps can change; treat this page as a checklist and follow the live product plus Freqtrade integration documentation.

Why integration matters for SEO and for truth

A standalone freqtrade sharpe ratio printout does not answer whether your strategy survives walk-forward or cost stress. Kiploks is built to align metrics with the published methodology so you can compare runs across time without re-deriving formulas.

What to freeze before export

Lock these so the report matches what you think you researched:

Strategy version (git commit or tag)
Pair list, timeframe, leverage, stake
Fee model and slippage assumptions
Data source revision (DQG)

If you change any of these after optimization, you are analyzing a different strategy.

What to export from Freqtrade

Minimum useful artifacts:

Trades list (timestamps, sides, fees, profit)
Summary metrics (profit factor, drawdown, trade count)
Config snapshot (parameters, protections, ROI tables)

If you run walk-forward slices locally, export each slice consistently so Kiploks can align windows (Freqtrade WFA setup).

Import into Kiploks (conceptual flow)

Create or open a project in the Kiploks app.
Upload or connect the exported artifacts per the integration flow.
Wait for processing: walk-forward style metrics, robustness views, and verdict bands when applicable.

How to read the result

Do not optimize one number. Read:

WFE and OOS retention together (WFE, OOS retention vs WFE)
Verdict language as triage (Verdicts)
Data-quality warnings before celebrating Sharpe (DQG)

Troubleshooting common mistakes

Mismatch in window boundaries between export and what you think you traded
Double-counting fees in the export and again in the app
Timezone offsets that shift bar alignment