Integration: regime-aware gating for your momentum indicator

[sendoeth]

hey — i built a regime signal API for the PF network that tracks semi/crypto lead-lag correlations (Granger-validated, 20/20 daily pairs at p<0.001). looking at your Custom-Crypto-Indicator and crypto_momentum_snapshot — your RSI + volume correlation scoring maps perfectly but has no market regime awareness.

the problem: during SYSTEMIC regimes, crypto AI tokens follow semi selloffs with amplified losses. your indicator can output "Strong Buy" when the underlying lead-lag relationship is hostile. from 264 days of backtesting, unfiltered signals hit 54% — regime-gated signals hit 82%.

i wrote a bespoke integration blueprint for your specific code:
https://gist.github.com/sendonanawitakeshi/bb741293de762e7ce0e792b803f28d61

tl;dr:

• regime_gated_indicator.py wraps your calculate_momentum_score() with a regime modifier
• SYSTEMIC = -5 shift (Strong Buy becomes Neutral), NEUTRAL = no shift
• if CRYPTO_LEADS filter = SUPPRESS, caps all positive scores at 0
• 78 lines, zero deps beyond the SDK (pure stdlib Python 3.10+)
• drop-in: replace 6 lines in your main() loop

your output JSON gains Regime, Regime Confidence, Score Shift, Adjusted Score, and Suppressed fields — full audit trail for every rating modification.

SDK: https://github.com/sendonanawitakeshi/post-fiat-signals

[sendoeth]

Hey — shipped a zero-setup quickstart since the original issue. You can go from git clone to first signal output in under 5 min, no live API needed:

https://github.com/sendonanawitakeshi/post-fiat-signals/blob/main/QUICKSTART.md

Just clone, python3 examples/mock_server.py &, python3 examples/full_pipeline_demo.py. Mock returns NEUTRAL regime with 2 actionable CRYPTO_LEADS signals. Would be useful to hear if anything trips you up — trying to validate the onboarding path before promoting it more widely.