edge-strategy-reviewer

You can review trading strategy drafts by parsing YAML files and applying eight weighted criteria (C1-C8) to compute an overall confidence score. This process evaluates edge plausibility, overfitting risk, sample size adequacy, and execution realism to emit structured findings.

Automated quality gating works by parsing strategy draft YAML files and applying verdict logic to emit PASS, REVISE, or REJECT outcomes. It calculates weighted C1-C8 scores and export eligibility flags to prevent exporting weak or overfit strategies to downstream pipelines.

The best way to check sample size adequacy is to use a multi-criteria review tool that evaluates strategy drafts against eight weighted criteria. It computes a confidence score and generates a review.yaml or review.json file with export eligibility flags.

Yes, the strategy review process requires Python 3.10 or higher with YAML parsing support to read strategy drafts. It processes the YAML files to compute weighted scores and generate review outputs for pipeline ingestion or manual validation.

Yes, you can optionally produce a markdown summary alongside review.yaml or review.json outputs. These files contain PASS, REVISE, or REJECT verdicts, confidence scores, and structured findings for both automated pipeline quality gating and human review.

A quality gate provides a deterministic evaluation of edge plausibility, overfitting risk, regime dependency, and invalidation quality. It ensures only robust candidates pass export eligibility checks, reducing human error during manual validation before backtesting.