Scan of every module and exported symbol, with each candidate verified by hand
rather than trusted from the scan.
Deleted outright:
frontend/src/lib/fundamentals.ts (112 lines, 12 exports) — imported by
nothing, including FundamentalsPanel, which reads backend values. It mirrors
scoring_service._compute_fundamental_score, so it is the same *kind* of
thing as lib/qualification.ts — but nothing consumes it, so it mirrored
nothing and could drift out of sync unnoticed.
Skeleton.SkeletonLine, paperTrades.getEquityCurve, regime.regimeColor
breadth_service.compute_breadth_today — self-described "thin wrapper, for
future live use"; that future did not arrive.
Kept, but unexported — used inside their own module, so the dead part was the
public surface, not the code: Button.Spinner, exitPlan.SETUP_STOP_ATR_MULTIPLIER,
client.ApiError.
Three things the scan flagged that are NOT dead, recorded so the next sweep does
not re-raise them:
RegimeChart.tsx — lazy(() => import(...)) in RegimePage, so it looks orphaned
to any importer-graph scan. Deleting it would break the risk page.
qualification.ts MIN_TARGET_PROBABILITY / liveRiskReward — that file is a live
mirror of app/services/qualification.py used in five places, and the
constant is exported to document the backend value it tracks.
ssl_bootstrap.ssl_status — called from an inline python snippet inside
scripts/run_tier1_macbook.sh, invisible to a .py-only search.
No orphaned backend modules across app/.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
The LLM-sourced capex/earnings observations carried 12+8 of 100 Warning points,
so both pegged at 100 produced a Warning of 20.0 -- below the event study's 25.3
alarm threshold and still inside the "stable" band. The reading was
arithmetically incapable of changing anything on screen, which is why refreshing
it appeared to do nothing. They are now a qualitative overlay reported beside
the scores rather than diluted into them.
Calibrated against the 408 v2 sessions to 2026-07-24, reproduced offline from
Alpaca + FRED; the harness matched the stored prod distribution exactly before
any parameter was changed.
State:
- P3 used dd_pct * 5, reaching 100 at a 20% drawdown -- the 90th percentile of
the observed distribution -- so 39/408 sessions sat at exactly 100 with no
resolution left during the part of a selloff that matters most. Replaced with
anchored breakpoints keeping headroom past the observed 36% maximum, blended
2:1 like P1/P2 instead of max(). P3's realized share of State falls from 65%
to 40%, matching its nominal weight.
- Credit level is now anchors-only. ICE capped FRED's BAMLH0A0HYM2 at a rolling
3-year window in April 2026, silently turning the 10-year percentile leg into
a 3-year one that scored 20 points of stress at an OAS of 3.5 -- the level its
own anchors call "mild". The anchors already encode the long-run distribution.
Warning:
- Added HY OAS 20-session widening (25%). The level is pinned at zero below the
3.5 anchor; its rate of change is not.
- Divergence tapers to a 0.35 floor instead of a hard price_ret >= 0 gate, which
zeroed the sensor through every decline: on 2026-07-24 the basket shed 10
points of participation in 20 sessions and Warning printed exactly 0.
- The event study and the live monitor now share one sensor definition, so they
cannot silently drift apart.
Bands are per axis (State 20/50/80, Warning 20/40/60) with quadrant dividers at
50/40; v2 Warning never exceeded 64.9 against a shared 60, leaving that half of
the quadrant unreachable. Realized shares: State 73/15/8/3%, Warning 69/20/8/3%.
Snapshots now record credit_history_days and vix_history_days -- the percentile
defect went unnoticed for months because nothing asserted the window the code
claimed.
Cutover: the first run rebuilds 400 sessions automatically; the Event Study job
must be re-run, as its cached report self-invalidates on the methodology check.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Adds a leading-by-construction candidate and the harness to measure whether it
actually leads regime breaks, before any of it earns weight in the live index.
- breadth_service: % of the stored universe above its own 200-DMA + a divergence
score (benchmark price up while breadth falls, nudged by low breadth). Genuinely
leading because it keys on divergence, not level. Not wired into the live score.
- event_study_service: detect drawdown events on the benchmark, then measure each
indicator's median lead time (event-centered) and precision/recall vs. the base
rate (signal-centered). Compares breadth-divergence against the deterministic
coincident price composite (reuses the regime price sub-scores). Price/breadth
only — reproducible, no LLM/FRED.
- Manual "Event Study" job (Admin → Jobs), GET /regime/event-study, and an
inline early-warning panel on the Regime tab with an honest small-sample caveat.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
dennisthiessenandClaude Opus 5