Consolidation only. Nothing built, wired or promoted.
NOTHING WAS RE-VERIFIED and no query was run — all 22 artifacts produced this
session plus the completion matrix were taken as KNOWN, per the order's own clause.
The verification ledger at the top of the plan lists exactly what was taken as
known and which four items remain genuinely open (sport order, board-reasoning
gating, the CLV flag, team colours) — each open because it needs a decision or a
build, not a query.
The plan captures all six tracks in one document: per-sport models (MLB's 8-layer
stack with each layer marked BUILT/PARTIAL/NOT-WIRED, plus the sport order),
design implementation (61 catalogued items), surfaces, the resolution tail, the
sport boundary, and the Chrome audit.
The through-line it makes visible: MLB's layers 2, 3, 5 and 6 are BUILT AND NOT
CONNECTED, while layer 8 (the grade ladder) is connected and meaningless
(r~0.005, inverted). MLB's fix is connection, not construction.
Phasing is by dependency: MLB model truth -> resolution tail -> surfaces/design
(parallel lane) -> sport boundary -> sport rollout (one order per sport) ->
monetization finish -> Chrome audit and hardening. ~23 orders total, ~11 unblocked
today, so "how many sessions left" now has a real answer.
DEFINITION OF DONE is explicit and countable: MLB layers 1-8 connected with a
monotone held-out-proven ladder; every listed sport finished on the same template
or explicitly abstaining with its reason recorded; all 61 design items built; every
surface reachable and honest; the resolution pipeline firing end-to-end; the sport
boundary a registry; the Chrome audit passed; and the record publishable on its own
terms with no claim outrunning its evidence.
STATE.md now points at the plan and is demoted to history.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01QJs13VsyiSKYQP6rj3NNmc
Verified three ways that nothing was promoted and no re-lettering happened:
HEAD is the no-flip commit with a clean tree, efficiencyShading is imported by
zero production files, and live grades carry 0.0% A-family (MLB {B:1,C:4},
WNBA {B:15,C:10}). Neither 92.9% nor 43.6% is a figure measured here - the
challenger's real numbers were 97.4% would-change / 79.8% up / 79.0% A, with
0 of 1250 rows actually shaded.
Takeable tags landed (1245/1250 tagged, takeable_floor on all, one floor -160;
the 5 untagged have no locked price). The model-version boundary is absent and
correctly so - there was no recalibration to mark. Not a pre-audit gap.
Matrix re-derived from live prod probes, importer counts and nav-link counts:
15 of 26 fully done. Book comparison RESOLVED (BookComparisonPanel routed to
the grade card). Grade card honesty improved by the edge_pct retirement.
ShareCard / MobileEdgeBoard / DemoScan still dead code. Seven live routes
remain orphaned with zero nav links; /system and /offseason are 404. No
LIVE-but-not-HONEST surface found.
Design is NOT complete: Live tracking, Slip reader and Newsletter are shipped
with no design artboard - design is the gap, not build. Offseason is the
reverse (designed, never built).
Chrome audit manifest assembled: 11 items with per-item session state, four
requiring an entitled Desk session that only Kev can drive.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01QJs13VsyiSKYQP6rj3NNmc
Report-only. No threshold, grade, or efficiency value changed.
VERDICT: FLAT. marketEfficiency.js does not exist (zero occurrences of
market_efficiency / efficiency_score in src/ or web/src/). The spec's
0.85/0.60/0.55 values appear in grade_thresholds.json only as PROBABILITY
BANDS - a coincidental numeric overlap, not efficiency scores.
The base edge thresholds (MLB A:5%, NBA A:7%) do not exist either: engine1.js
has zero `edge` references, so the live grade is not an edge-vs-threshold
comparison at all. The specced rule threshold = base x efficiency has no host.
DISPOSITIVE: engine1.js contains ZERO `sport` references. computeFactors
receives no sport or market, so per-market OR per-sport scaling is structurally
impossible in the live grader - not merely unwired.
Phase 2: the matched-edge test is confounded (edge is not the grading input -
the same market emits both B and C at one edge). The aggregate that
discriminates: mean grade index wnba points 4.71 at mean edge 10.2 vs mlb hits
4.58 at 69.5 vs mlb total_bases 4.32 at 84.9 - the efficient market earns the
highest grades on one-eighth the edge, the opposite of spec.
PREMISE CORRECTION (measured): this order's opening claim that full-output and
collapsed grades "agree 100%" does not hold - on 512 rows carrying both they
agree 17.8%, with 33.8% differing by 3+ tiers. The prior discrimination result
stands (champion r=0.0050 null vs probability r=0.1313; MLB 0.0686 n.s. vs
0.2356 p~0.0004). Repo unchanged between orders. The collapse was not a
phantom and the re-adjudication list stays open.
Scope: flat thresholds are a grade-CALIBRATION gap only - the projection and
the CLV edge (which measured p_win, never the letter) are untouched, so this is
not a third shadow-model alarm. But the fix is NOT independently bounded: with
no threshold step to multiply, efficiency scaling presupposes probability
grading. It is rule R4 of specs/full-output-grade-mapping.md and belongs to
that MLB-first challenger.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01QJs13VsyiSKYQP6rj3NNmc
Report-only. Nothing built, reconnected, or promoted.
Premise corrected again: the three-layer engine is BUILT but NOT WIRED and NOT
DEPLOYED (0 python refs in every grade-path file, 0 python in Dockerfile; there
is no engine1Adapter). So no posterior/CI/similarity prior exists to inventory
or diff. Measured against the collapse that actually exists instead.
THREE collapses, not one: (A) estimateProbability's components discarded at
analyzeViaEngine1:521-524; (B) THE SEVERE ONE - p_win never reaches the grade
at all (engine1.js has zero probability references), so the probability is
excluded from grading rather than collapsed into it; (C) grade_thresholds.json
(probability->grade) read backwards to manufacture confidence.
Market-efficiency scaling is never computed - a gap, not a collapse.
MEASURED on 354 settled rows carrying the served letter and the locked pre-game
p_win (forward, not lookahead). Grade->outcome point-biserial r: champion letter
0.0050 (p~0.93, null) vs probability letter 0.1313 (p~0.013). Per sport: MLB
champ 0.0686 n.s. vs prob 0.2356 (p~0.0004); WNBA champ -0.0986 vs prob -0.1258
- BOTH INVERSE. The served letter is inverted between its only two populated
tiers (B 52.4% n=168 vs C 56.9% n=174).
Verdict: costly on MLB, and un-collapsing does NOT help WNBA -> the challenger
must be MLB-FIRST. Five falsifiable mapping rules specced, incl. R2
(uncertainty grades down) stated explicitly and droppable if it fails.
Hard requirement on the next order: persist per-row n, SE and pre-adjustment p,
or R2/R4 can never be adjudicated (not stored today).
Re-adjudication list flagged incl. proj-v1.1's NOT PROVEN verdict (judged
against the collapsed champion, so not final) and ROI-by-grade (with B/C
inverted, the MLB-C +4.57% segment is likely an artifact of a meaningless
letter).
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01QJs13VsyiSKYQP6rj3NNmc
Archaeology only; nothing built, reconnected, or promoted.
The champion is two DISCONNECTED estimates: the letter is engine1's additive
factor index (zero references to p_win or any probability in engine1.js), and
p_win is probabilityEstimator's frequencyOver + 5 heuristic layers, computed
after and merely attached. The live grade path never calls the Python service.
The Python three-layer engine is NOT DEPLOYED — no python/pip in the
Dockerfile; app.js only health-checks it. So Layers 1-2 never shipped.
Layer 3 is wired BACKWARDS: grade_thresholds.json maps PROBABILITY->GRADE and
the live JS reads it in reverse to manufacture confidence from an
already-chosen letter. Per-sport market-efficiency scaling is specced-absent.
Consequence stated plainly: every metric audited to date is on the shadow
model, not the specced engine, which has never been measured.
Sport boundary TESTED not asserted: a new sport on the live path is a ~10-file
core edit with four documented silent-failure modes. Per-sport records DO
exist (sports.mlb n=526/62% vs pooled overall n=937/58%, each n>=20 gated),
but /api/accuracy ignores ?sport= and the pooled overall would absorb a new
sport. Park x weather confirmed challenger-only; xwOBA and leash absent.
Recovery map is dependency-ordered with MLB as the reference module.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01QJs13VsyiSKYQP6rj3NNmc
MLB decided overs n=296, 100% with locked_odds. ROI by locked-price bucket
shows every 95% CI containing zero; the curve is NON-MONOTONE and runs opposite
to the premise (deepest buckets positive, the -111..-160 middle most negative);
and price bucket is confounded with market (+200up = doubles/HR longshots).
Rows needed per bucket to resolve a 5-pt edge: 661-2285 vs actual 8-71 (~187
days for one bucket at current accrual). The inherited -160 is neither
confirmed nor refuted. The no-ceiling call is not supported by this data either
(+200up is the worst bucket) though it is not refuted - it stays a design
choice, not a data-backed one.
Recommends C2 proceed with -160 as an explicitly-labelled POLICY floor plus a
re-derivation trigger (any negative bucket n>=300, or end of MLB regular
season; adopt a derived floor only when a bucket CI excludes zero). Enumerates
all 9 takeable sites, incl. the live drift hazard (backend env-tunable,
frontend hardcoded) and the user-visible band copy in PriceTriplet.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01QJs13VsyiSKYQP6rj3NNmc
The anonymous live order (Brionna Jones edge 29.4 ahead of Rhyne Howard edge
42.9) is only explicable by server-side p_win ranking (.90 vs .745, both
takeable) while the payload carries no paid fields — the free caller got the
paid RANKING without the paid SIGNAL, on live data.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01QJs13VsyiSKYQP6rj3NNmc
New READ endpoint. No grade, ledger row, lock_line, or scoring write. Push
scoring untouched.
REVIEW ZERO CORRECTED THE PREMISE: the handler NEVER EXISTED in any commit
(searched git rev-list --all for a /top-graded definition in src/ — zero hits).
Not "removed" — the three axios callers (cheatsheetGenerator, gradeOfTheDay,
widget) and the Next proxy were written against a phantom endpoint, so those
three content generators have silently received [] for their entire life.
Contract recovered from the four consumers, not guessed: {props:[...]},
?sport=UPPERCASE (absent = all sports, which gradeOfTheDay relies on) + ?limit,
rows carrying player/stat/line/direction/sport/grade/confidence? plus the
player_name/stat_type aliases and game_id.
POPULATED-PATH RISK FOUND: the board's populated branch had never run in prod,
and dashboard/page.tsx:463 calls g.stat.replace(/_/g,' ') UNGUARDED (g.player
also feeds the row key, /scan URL and heading; sport must be UPPERCASE for
SportPill). toRow requires non-empty string player+stat and a finite line,
uppercases sport, and DROPS unrenderable rows — a shorter board beats a broken
one.
THE LEAK BOUNDARY (why this is server-side): the browser cannot rank on p_win
for all tiers because stripModelPrice deliberately withholds it from unentitled
tiers. Order of operations is
read cache -> RANK with p_win (every tier) -> map rows incl. model fields
-> stripModelPrice(rows, tier) -> serialize
so a free caller receives the paid RANKING without the paid VALUES. Tier comes
from resolveTierFromRequest, which FAILS CLOSED to 'free'. Cache-Control is
private under a bearer token, public otherwise (the /api/snapshot precedent).
ONE SHARED DEFINITION, no drift: new src/utils/gradeRanking.js
(takeablePWin/descNullsLast/rankGrades). heroPropService now imports
takeablePWin instead of its inline copy (behaviour unchanged — it was that
logic verbatim); the selector imports rankGrades; web/src/lib/slateAdapter
keeps its mirror (the browser cannot import src/, S25) and a test cross-checks
the two on identical fixtures (playerName.js precedent). Board is grade-first
("top GRADES"), hero is p_win-first ("top read") — they differ BY DESIGN and
agree within the leading tier.
HONEST LIMIT: the Next proxy (cachedBackendJson) sends no Authorization header
and caches under a shared key, so via the dashboard every viewer gets the
free-tier payload — correct order, no paid values. That is the SAFE behaviour;
forwarding auth into a shared cache is exactly how a paid payload leaks to
anonymous viewers. Per-tier delivery through the proxy needs a tier-keyed cache
and is not done here.
Verified on real prod snapshot data (anonymous path): MLB 8 props, WNBA 10,
0 paid-field leaks, render-contract safe on every row, sport uppercase.
Floor: 311 suites / 3882 tests green (18 new — leak test uses POPULATED p_win,
not today's nulls: entitled gets p_win and it drove the order, unentitled gets
a byte-identical order with all five MODEL_FIELDS absent and no trace in
JSON.stringify, while book/fair market facts survive). Web build exit 0.
Dashboard visual is auth-gated -> tagged for the Chrome audit, not faked.
Held: edge_pct rescale/retirement (Order B); board columns/contract unchanged;
tier-keyed proxy caching.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01QJs13VsyiSKYQP6rj3NNmc
Display ORDERING only. No grade, ledger row, lock_line, scoring, or edge_pct
scale/display change. Push scoring untouched.
Two defects removed from selectTopGrades (wrong at ANY scale, independent of
edge_pct's separate retirement):
1. edge: Math.abs(numOr(g.edge, -Infinity)) — abs() on an already-
direction-signed value ranked the model's strongest DISAGREEMENTS level
with its strongest agreements (177 public ledger rows carry a negative
edge; positive = the model AGREES with the graded side).
2. Math.abs(-Infinity) === Infinity, so a row with NO edge sorted FIRST —
absent data presented as the top pick (the Number(null) class).
New key: grade -> confidence -> takeable-gated p_win (nulls LAST) -> SIGNED
edge (nulls LAST) -> input order. Scales are never mixed in one comparator.
Takeable band = web valueState.isTakeable, asserted byte-equal to the hero's
config/valueEngine.isTakeable (-160..+200) incl. strict-null.
Alt-line ladder (analyzeViaEngine1:506) no longer sorts by edge_pct: ordered
highest-p_win-first derived analytically at zero added compute — P(stat >= k)
is monotone non-increasing in k, so p_win-desc is line-ASC for an over and
line-DESC for an under. base stays marked; no consumer depends on
alt_lines[0]; deskShowcaseService.rungsOf already re-sorted by line.
THREE PREMISE BREAKS found report-first, before code:
- /api/props/top-graded 404s in prod (absent from src/) so the dashboard
board renders receipts/empty — the edge sort orders nothing there today.
The prior order's "97.3% of rows tie" was a LEDGER measurement wrongly
extrapolated to that board. Fix is correct-in-itself and lands when the
feed is restored.
- p_win cannot be a client-side key for all tiers: snapshotGating strips it
for unentitled tiers ("shipping p_win is shipping the model price").
Verified live: prod /api/snapshot carries p_win on 0/8 MLB, 0/25 WNBA.
- Ladder rungs carry no per-rung price, so the takeable gate is inapplicable.
Verified on real data, both sports, both paths: unentitled — WNBA (n=25)
ordering CHANGED, MLB (n=8) unchanged, signed edge non-increasing in every
(grade,confidence) tie group (20 pairs, 0 violations); entitled — 40 real
ledger rows with p_win+locked_odds, p_win-descending, untakeable chalk NOT
promoted (Trea Turner .757 @-275 does not beat Rhyne Howard .745 @-120)
(36 pairs, 0 violations).
Hero consistency, stated honestly: same signal + same gate, different
precedence BY CONTRACT (board = grade-tier-first "top GRADES"; hero =
p_win-first "top read"). Identical within the leading tier (verified); across
tiers the board may lead with an A the hero doesn't pick. Not a contradiction.
Floor: 310 suites / 3864 tests green, web build exit 0. Dashboard + Desk
visuals are auth/feed-gated -> tagged for the Chrome audit, no visual faked.
Held: edge_pct rescale/display retirement (Order B); building the missing
/api/props/top-graded selector; exposing p_win to unentitled tiers.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01QJs13VsyiSKYQP6rj3NNmc
Read-only proof. N-gate passed (overlap 45). proj-v1.1 edge-CLV partial
correlation controlling for price = 0.245 (n.s.); ~half the raw 0.455 is the
shared -fair_prob_lock term (mechanical). Champion out-predicts proj on the
same rows (champ partial-CLV 0.380 sig; champ-edge->hit 0.25 vs 0.12). Unders
contaminated (CLV -9.3); WNBA proj-v1.1 doesn't run. Promotion HELD; the
under-audit is moot since proj loses to the champion first.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VsztNChZ7vEvSR61AuMhD1
closing_prob 59 -> 406 (MLB 248, WNBA 158). Root cause was attachClosingProb's
truncated read + write-once market_unavailable, not capture or the join. CLV
measured: MLB unders lag the close (mean -9.1 prob-pts, 74% lose), MLB overs
+2.0, WNBA flat -> the +4.57% MLB-C and over/under asymmetry are substantially
stale-line artifacts. Unblocks the proj-v1.1 proof order.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VsztNChZ7vEvSR61AuMhD1
NexaPay was cross-project contamination (from another venture) — never a real
VYNDR payment path. Purged; Stripe path untouched.
Removed:
- web/src/services/nexapay.ts (createPaymentLink/getTransaction/HMAC verify)
- web/src/app/api/webhook/nexapay/route.ts (the only importer; Next-registered,
reachable — now gone)
- NexaPay comments in email.ts + checkout/route.ts
- Active NexaPay entries in docs/SYSTEM-MANIFEST.md (route list, NEXAPAY_* env
table, service row) + stale claim in wiring-data-train.md
- sw.js precache entry for the deleted webhook chunk
Verified: ZERO NexaPay in code (web/src, src, tests). Full suite 3833 green
(count unchanged — nothing depended on it, confirming it was dead). Web build
exit 0. sw.js parses clean. Stripe checkout untouched (Next→Express→Stripe).
FLAGGED FOR KEV (a repo delete cannot close these):
- Coolify env: remove NEXAPAY_API_KEY / NEXAPAY_WEBHOOK_SECRET / NEXAPAY_API_URL
- Revoke the NexaPay API key + webhook secret at NexaPay's dashboard; de-register
the webhook if an account was ever configured
- DB column user_profiles.nexapay_customer_id is orphaned (no reader/writer) —
drop via a follow-up migration (migration 011 left as history)
Cross-project check: ZERO Noctem-Supabase refs; VYNDR references only its own
Supabase (zmdnczhtdxcddsxzttub). NexaPay was the sole contamination found.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VsztNChZ7vEvSR61AuMhD1
Records the six live fabrications removed/hidden, keeps media/newsletter/WIRE on
the board as real work, logs the news/line-movement signal as a future model
input, and logs the known honesty gaps (hit-rate-without-ROI, CLV starved).
Honest state: "no KNOWN live fabrications," not "provably none."
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VsztNChZ7vEvSR61AuMhD1
Read-only inventory order — no code built/wired/fixed/deployed. Maps every
user-facing surface and model component against DESIGNED·BUILT·WIRED·LIVE·HONEST,
re-derived from repo b0a51c8 + prod + design bundle (not STATE.md narrative).
15/26 surfaces fully done. Names the graveyard (BookComparison, ShareCard,
proj_ladder, arch-v1/contact-v1 ledger-only, /intelligence orphan) and the live
honesty gaps (/compare hardcoded, FAQ NexaPay/Brier, MobileEdgeBoard placeholder,
EV fields NULL on served grades). STATE.md now points to the matrix as canonical.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VsztNChZ7vEvSR61AuMhD1
Per-book prices existed only transiently (odds cache, ~1h, raw names, grade-path
input); every grade-path persistence point collapses to one book. The
/api/books feature was built+mounted but non-functional (fed FLAT rows to a
GROUPED comparator -> always empty).
Phase 1: bookPriceStore captures per-book prices from `props` BEFORE dedupeProps,
keyed nameKey|stat, into bookprices:{sport} (SNAP_TTL) in snapshotService. Fenced:
reads props, writes its own key, read by nothing on the grade path. Grade proven
byte-identical (test + no-grade-path-reference grep test).
Phase 2: scripts/measure-book-spread.js reports same-line best-vs-worst spread
(cents + implied-prob pts), per sport, never pooled. Pre-registered crown
threshold: median >=8c OR >=2pp. Runs post-deploy on real data.
Phase 3 (backend): compareProp is honest-absent (single-book/flat -> no crown)
and the crown is gated (BOOK_CROWN_ENABLED, default OFF until Phase 2 clears).
/api/books repointed to the snapshot-locked store (fallback odds cache),
nameKey-matched; `source` field is the deploy fingerprint.
HELD unchanged: dedupeProps, snapshot dedup, selector, grade, champion,
challengers, ranking, edge_pct/ev_pct. UI routing of BookComparison + crown
treatment deferred to post-measurement (gated on Phase 2). Full suite 3834 green,
web build exit 0.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VsztNChZ7vEvSR61AuMhD1
builtbykev