backtest-comparator — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited backtest-comparator (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Use this skill when several strategy variants or parameter sets each have per-year (or per-fold) results and you need to pick the robust one, not the one with the highest average. A variant can win on the mean while quietly losing on an individual fold; this comparator ranks by mean but also reports standard deviation and the worst fold, then flags overfit and unstable variants so they can't slip through.
User input:
Three variants, four years of returns each. Tell me which is actually robust vs which just got lucky one year.Output:
variant mean std worst verdict
------------------------------------------------------
cross_only 0.188 0.027 0.150 robust
macd_filter 0.095 0.011 0.080 robust
pullback_ema21 0.075 0.205 -0.120 OVERFIT (positive mean, loses on a fold)Code:
# Copy assets/compare.py into your project, then:
from compare import compare_variants, format_table
folds = {
"cross_only": [0.18, 0.22, 0.15, 0.20],
"macd_filter": [0.10, 0.09, 0.11, 0.08],
"pullback_ema21": [0.40, -0.12, 0.05, -0.03],
}
print(format_table(compare_variants(folds)))OVERFIT when the mean is positive yet a fold is negative; flag UNSTABLE when dispersion exceeds the mean.Reference: assets/compare.py.
Distilled from production use across the author's automation projects. v1.0.0. See also: [[walk-forward-runner]], [[config-audit-checklist]].
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