New pure-compute utils/readiness.py (stdlib only, fully unit-tested) assesses
readiness from wellness history: HRV via Plews & Laursen 7-day rolling lnRMSSD vs
baseline +/- SWC, resting-HR and sleep trends, and conventional-direction
subjective inputs (soft warnings only). The get_training_readiness tool fetches
the window, normalizes the date-keyed API response, and renders a banded verdict
with the contributing signals. Verdict is withheld (not fabricated) when HRV is
sparse and fewer than two other core signals have data.
Implements #1. Completes the 0.3.0 coaching-context milestone.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01NGzHtDvJur9U7ysgRKRUTN
