The probe printed one blended number per policy, so a component pinned at 0.000
across every rung was invisible. Four gates hid there for a month. It now reports
floor / best-below-oracle / oracle / ceiling for 25 components across 8
environments, and a component flat across every rung is fatal.
bot-detection GATE_SLACK = 1 — fires 5/32 on the real rollouts, was 0/32. The
max(1, reference_caught - SLACK) guard is verified by construction, not by
sampling: without it the required count reaches 0 and an EMPTY accusation list
clears the gate. Observed reference_caught is 4-6, so no amount of sampling would
have found that hole.
schema-migration GATE_MARGIN = 0.15 — fires 4/32, was 0/32. The cost is disclosed
and bounded: the naive split clears it on 5.5% of 1,000 unseen seeds, fenced by
an assert at 10%. Margin 0.10 keeps the leak at zero and fires 0/32, i.e. stays
dead. A live gradient with a bounded leak beats a clean corpse.
redaction-pressure is NOT given a margin, and that is the result rather than a
failure. The only setting that fires at all leaves half the secrets standing and
pays a four-of-seven ruleset on five seeds in six — a margin that pays for
inaction is strictly worse than a dead gate. Recall maxes at 0.852 and no rollout
ever cleared both clauses in one episode. It is genuinely hard, not miscalibrated.
⚠️ The per-component check did not catch the defect it was built for. Reverting
schema-migration's margin to 0.0 — restoring the exact dead gate — printed ok and
exited 0, because the near-oracle rung scrapes the unmargined gate on ~2 seeds in
24 and that kept best<oracle non-zero. Every assertion bounded how much a margin
may PAY; none noticed if it stopped existing. migration() now carries the mirror
of bot-detection's guard, and reverting the margin fails with "the margin is dead
and the component carries no gradient between the crude answer and the exact one".
canary-trap's oracle-minus-one rung is documented as degenerate rather than
quietly relied on: it is identical to the oracle to four decimals, so it measures
specificity and gate at the ceiling, not mid-ladder as its comment claimed.
The CI lock policy asks git instead of the disk. It was checking the working
tree, where a lock file is a normal by-product of uv sync, so it passed in a clean
checkout and failed on every machine that had run an eval.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
The 600-second per-model-call ceiling that capped the thinking-on run at n=6 is
gone: DEFAULT_TIMEOUT is read=None in all nine venvs.
There is NO verifiers 0.4.0. The `version = "0.4.0"` in the vendored tree belongs
to a [[tool.uv.dependency-metadata]] block for nemo-gym, and reading it as
verifiers' own sends you hunting a release that does not exist and concluding the
bump is blocked. The vendored checkout is v0.3.0-59-g4bcb48e5, published to PyPI
as 0.3.1.dev59, and the installed wheel diffs clean against the whole vendored
v1 tree. Pinned as an ordinary index dependency: a path source is reproducible
only on this box and a git URL pins a commit no wheel matches.
⚠️ dev59 changes the default agent runtime from subprocess to `prime`, a REMOTE
sandbox. Without an explicit runtime every eval here exits "not authenticated
with prime" before a single rollout — having already created its output directory
and a zero-line traces.jsonl, so it reads as a failed eval rather than an
unauthenticated one. All nine configs now say subprocess. Nothing here needs a
sandbox: the reward is a pure function of the trace and the harness is null.
Output layout is flat now — <env>--<model>--<harness>--<hex8>/ with configs/,
traces.jsonl and a logs/eval.log that 0.3.0 never wrote. `-o` is the output_dir,
not the run dir; `--run.dir` pins the leaf.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
canary-trap, fault-localisation and schema-migration, in the three domains the
Environments Hub has nothing in: contamination, operations, data engineering.
None is a port. Each is graded on a slice the model never read.
canary-trap runs a probe set against a model that memorised the corpus AND one
that learned the same facts from a reworded copy with every identifier
regenerated. The obvious probe -- plant a GUID, ask for it back -- is sound and
caps at 0.525 because it cannot see the paraphrase. It scored higher than that
at first: facts with no distinct rewording had the paraphrase restating the
corpus verbatim, so GUID probes caught it by accident. Every fact now carries a
"core" token present in both wordings and in no public one, asserted at import,
which is also what makes the ceiling reachable.
fault-localisation puts the fault upstream and the noise downstream, the way
incidents actually present. The broken service logs one line and goes quiet
while its dependents log a dozen timeouts, so ranking by error volume answers
the victim -- 0/64 incidents have the loudest service as the root, and probe.py
asserts it rather than trusting the generator to stay that way.
schema-migration executes the model's SQL against forty held-out rows carrying
thousands separators, negatives, a unit with a slash in it and a value with no
unit. Row preservation started as a reward beside fidelity and paid 0.15 for
adding two empty columns and touching nothing; it is a multiplier now, so
losing rows still zeroes a perfect migration and keeping them earns nothing on
its own.
probe.py is house rule 3 as an exit code: 0.000 for inaction and 1.000 for an
oracle, or it returns 1. It loads the leaf modules through a namespace shim
rather than the packages, so it runs without verifiers installed -- a self-check
that needs the training stack is a self-check nobody runs.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
An environment is an eval you take the gradient of, so it carries obligations a
benchmark does not: a held-out slice, a counterweighted reward, and a demonstrated
0.0 floor and 1.0 ceiling. README states the three as house rules.
redaction-pressure is Forge's redact stage as a task. The first reward design scored
survivors — secrets caught, decoys kept, prose kept — and an empty ruleset tied the
best real attempt at 0.500, because destroying nothing keeps everything. Counting
removals instead puts inaction at 0.000, shredding at 0.380, and an oracle at 1.000.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
karti
