The env var has been set to google/gemma-4-31b-it all along and nothing ever
mapped it onto openRouter.cheapModel, so graphWorker's fallback chain silently
used the main model instead. Graph entity resolution is the highest volume llm
call in the system and its entire job is to reply with the number of a match.
Measured on the live key, same prompt:
deepseek v4 flash 7564 completion tokens, 7558 of them reasoning $0.0013708
gemma-4-31b-it 14 completion tokens, 0 reasoning $0.0000121
113x. Gemma is actually the more expensive model per token, which is why this
was worth measuring rather than reasoning about prices: the cost is not the
price of the tokens, it is a reasoning model spending seven thousand tokens
thinking about a multiple choice question.
This also explains the reasoning tokens dominating the usage dashboard, and why
the daily spend roughly doubled today rather than yesterday. Removing the token
ceiling let a trivial prompt reason without bound. The ceiling was never the
right control for that, the model choice is.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WnNxwxfXSbeNtjvtz5gayb
96% of rejected proposals name something untradable: indices (SPX, DXY, ^TNX),
fx (EURUSD, XAU/USD), futures (CL=F, BZ=F) and home listings (VOW3.DE, RHM.DE,
1211.HK, 688169.SS). The analysis behind those is usually sound, it is the ticker
that cannot be used, and nothing in the prompt ever said so. We were paying for
the call and discarding the result at validation.
The rules point the model at what the allowlist actually holds: US listings and
ADRs for foreign companies, and US listed ETFs as the tradable expression of an
index, currency, rate or commodity. Every symbol named in the rules was checked
against the live allowlist first, so VWAGY, BABA, TM, SONY, SPY, QQQ, GLD, USO,
UUP and TLT all genuinely resolve. It also forbids predicting SPY itself, which
is the benchmark and whose excess return is zero by construction.
Shared between the coordinator and replay prompts rather than written twice,
since a rule that drifts between the two lanes is worse than no rule.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WnNxwxfXSbeNtjvtz5gayb
Removing the caps rather than tuning them. Every number I picked was a number I
invented, and 6000 was already tight enough to truncate a real replay article,
which is the failure that was called out when the cap first went in.
The coordinator now sends no max_tokens at all. The 402 handler supplies one only
when openrouter says the budget cannot cover an open ended request, so the
ceiling exists exactly when it has to and never otherwise. Verified unbounded is
accepted against the live key before making this the default.
The caps on the signal, augor, consolidation and graph workers are gone too. They
were added to work around an empty account, not because any of them ever produced
too much, and unlike the coordinator none of them detect truncation, so an
invented ceiling there risked silently corrupting company facts. A budget failure
in those is at least loud.
The 220 token cap in crawlerClassifier is left alone, it predates this and bounds
a genuinely tiny classification.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WnNxwxfXSbeNtjvtz5gayb
The event outcome worker re-requested PSTG and GROQ on every poll for as long as
the process lived, because a fetch failure only logged and continued while the
prediction stayed pending. Ten requests every five minutes, indefinitely. Per
ticker backoff now doubles to an hour, so a symbol with no market data costs one
request an hour instead of one a minute. It also translates dotted tickers the
same way the autonomy worker does, which is why that helper moved into the
shared price module rather than being copied.
The gdelt loop had no pause on its error path at all, so once the api started
refusing connections it spun through failures continuously, burning cpu and
filling the log with the same stack. It has been doing that for days. Backs off
to half an hour now and resets on success.
isTransientCoordinatorFailure matched 408, 429 and 5xx but not a budget 402/403,
so the 380 jobs that dead-lettered during the exhausted quota window could never
come back on their own, including 55 live events. Budget failures are transient
in a way an ordinary auth failure is not, and a wrong key still dies permanently
because it says invalid or unauthorized rather than naming credits.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WnNxwxfXSbeNtjvtz5gayb
Six live predictions were marked unresolvable, including MSFT twice, WMT and
ITW. Re-running the calculation against yahoo resolves all six, so they were
never unresolvable, they were scored before the market data existed and then
thrown away permanently.
The due-check counted calendar days while calculateOutcome finds the exit bar by
trading days. A friday horizon-1 prediction therefore looked due on saturday,
when monday's close cannot exist. calculateOutcome returned null and the worker
treated null as permanently dead. This hit short horizons hardest, which is
exactly the cohort that produces the first live evidence.
The sql filter stays loose because it cannot know about weekends, and trading day
arithmetic now decides what is genuinely ready. A null result waits for the
horizon to be properly past before anything is retired, and says so when it
finally gives up.
Separately, at horizon 1 the entry and exit lookups could land on the same bar
and produce an excess return of exactly zero, which was recorded as a real
outcome and scored as a directional miss. ITW and WMT both did this. A horizon
that has not elapsed is no longer a measurement.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WnNxwxfXSbeNtjvtz5gayb
signal, augor and consolidation had the same unbounded request as the
coordinator, so switching to a model with a 131k output window made all three
402 on every call while the coordinator itself was fine. Found them by grepping
for the endpoint rather than waiting for each one to surface in the logs.
Sized per worker rather than one global number, since these produce more than
the coordinator's small json object.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WnNxwxfXSbeNtjvtz5gayb
Neither the coordinator nor the graph resolver set max_tokens, so openrouter
reserved the model's entire output window against the key's remaining budget and
returned 402 before running anything: 131k tokens reserved to produce a few
hundred. It never showed up with the old model because its output window is
small enough to fit under the limit.
Both are now bounded and overridable by env. The headroom is deliberate, the
newer reasoning models spend completion tokens thinking before they answer.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WnNxwxfXSbeNtjvtz5gayb
The old admin was five separate html pages, so every navigation was a full
reload and the operational picture was scattered across all of them. Worth
saying: the api was never the problem, every endpoint answers in under 200ms.
It felt slow because of the architecture, not the backend.
This is a single page console. React and htm from a cdn, no bundler and no
babel-in-the-browser, because a runtime transpiler on every load is exactly the
slowness we are trying to get rid of. Hash routing, polling that keeps the last
good payload on screen instead of flashing a spinner, and stale responses are
dropped so a slow request cannot overwrite a newer one.
/admin/api/ops/overview answers the whole dashboard in one call rather than
making the browser fan out and stitch. It carries the things that actually
matter and were not visible anywhere before: when live evidence matures, why a
cohort does or does not clear the trade gate, which stage of the pipeline has
gone quiet, and what is sitting in dead letters.
Controls, all of which change production and all of which ask twice:
- requeue dead letters, which only ever moves dead_letter back to pending
- execution mode and a kill switch, now read from autonomy_settings on every
poll instead of only from AUTONOMY_EXECUTION_MODE, so halting no longer needs
a redeploy first
- run the reaction analysis and read its output
The d3 graph is framed rather than ported. It works, and rewriting it would risk
something valuable for nothing the operator can see.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WnNxwxfXSbeNtjvtz5gayb
Three separate things had the pipeline frozen for 27 hours.
browserCrawler leaked page slots. context.newPage() sat outside the try, so a
throw or a hang there took the slot with it, and after maxConcurrentPages of
those every caller parked in acquirePageSlot forever. That is what it looked
like from outside: content workers alive, no logs, no progress, 13 chromium
renderers still up 10 hours after start. newPage is inside the try now, waiting
for a slot times out instead of blocking forever, and page.close() is raced so a
wedged renderer cant strand the slot on the way out either.
graphWorker had no backoff on quota failures. A blown OpenRouter monthly limit
returns an instant 403, so it retried as fast as the network allowed: 2356
failures in 20 minutes, drowning every other line in the log. Quota and auth
errors now pause resolution for 15 minutes and log once per window rather than
once per attempt.
The outcome worker retried unresolvable predictions forever. Yahoo writes class
shares with a dash, so BRK.B 404s every time, and a failed prediction stays open
and comes straight back on the next poll. Dots are translated to dashes, which
matters beyond this one name because the allowlist is full of dotted symbols,
and a prediction that fails five times is marked unresolvable instead of
spinning.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WnNxwxfXSbeNtjvtz5gayb
The JSON shape in both prompts used real values as placeholders, and the model
was reading them as the answer:
instrument: 'NVDA' -> 397 of 611 predictions are NVDA (65%),
second place is LMT with 8
horizon_days: 10 -> 606 of 611 are horizon 10 (99.2%), out of
seven allowed horizons
direction: 'positive|negative' -> 502 of 611 are positive (82.2%)
event_type: 'stable_enum' -> the enum was never listed, so the model
invented one label per event, 201 distinct
values across 611 predictions
replayWorker had its own copy of the same prompt with the same values, which is
why both lanes show the identical skew (replay is 147/147 horizon 10, 138/147
NVDA).
Every placeholder is now a description of the field rather than a usable value,
with an explicit line saying not to copy them. event_type is validated against
the same closed family list the cohort key uses, so a label cannot mean one
thing in the prompt and another in calibration. Off-enum labels are salvaged
through the existing mapper when they are placeable and rejected when they are
not, so 'other' does not quietly become the bin again.
This does not by itself create edge. It means the next batch of predictions
measures the model's judgement instead of its willingness to copy an example.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WnNxwxfXSbeNtjvtz5gayb
Offline evidence can no longer authorise anything. createDecisions used to
prefer a live snapshot and fall back to the pooled historical one, so once the
live lane woke up a live prediction could have drawn a BUY off backfill data.
Backfill and replay are fine evidence that the pipeline works, they are not a
live track record.
No live snapshot now means ABSTAIN. The abstain says whether offline evidence
existed for that cohort, so "we have 60 offline samples but no live ones" stays
distinguishable from "we know nothing about this cohort".
Also split the health counter. It counted qualifying cohorts across every
source, which overstated how close we are to being able to trade now that only
live cohorts can authorise. It reports qualifying_live_cohorts and
qualifying_offline_cohorts separately, and applies the concentration cap it was
previously ignoring.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WnNxwxfXSbeNtjvtz5gayb
Archive ingestion had been dead since 2026-08-02 because nothing in the
compose stack actually ran it. Everything downstream starved from there.
- add ingest + enrichment services. server.js only starts the scheduler when
DURIIN_RUN_SCHEDULER is not "false", and workers/index.js was not running at
all, so articles never got event_id/content/has_embedding and the coordinator
had nothing to lease.
- pass an explicit origin from coordinatorWorker. it was never passed, so
acceptProposal defaulted to 'live' and 464 historical backfill predictions
were recorded as live. that also meant verifyEvidence got a null cutoff and
skipped its date check entirely.
- coarsen cohortKey to event families + horizon buckets. 201 free text event
types produced 221 cohorts averaging 2.76 samples, so the n>=30 gate could
never be reached and everything abstained for the wrong reason.
- gate on cohort diversity, not just sample count. one ticker was roughly half
of all resolved outcomes, so a pure count gate was measuring one company.
unknown diversity abstains rather than passing.
- resolve the admin archive db explicitly and probe it. it relied on a
Dockerfile symlink, and without it better-sqlite3 quietly creates an empty
file and serves a phantom archive.
- clamp implausible future publication dates at ingest.
- pin the db backend to sqlite by default. compose hardcoded postgres "true",
which would have overridden the operator's own .env on the next redeploy and
pointed everything at a stale snapshot.
scripts/repair-autonomy-labels.js relabels the affected rows. it is dry run by
default and has not been applied.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WnNxwxfXSbeNtjvtz5gayb
