Quick mode has rules only for c/cpp, groovy, java, javascript/typescript and
python, so every PHP case's "0 alerts" read as clean. The `alerts` task now
records per language of the files read whether quick mode covers it
(derived from the bundled ruleset, not a list): coverage quick | none, with
file counts per pin, and `uncovered`. `remember` turns that into `coverage`
memory rows (a new kind; the Run passes the alerts summary.json as input),
loop-measure reports coverage per language, and improve/memory.py's M1/M2
skip a repository+pin whose coverage for the rule's language is only
`none` (counted under `coverage_none` in the proposal's excluded).
`ousast plane alerts-engine <Run.yaml> --source <frozen export>`
(plane/engine_alerts.py) does the alerts task on the host for cases whose
files include a language the engine covers but quick mode does not (PHP):
exports both pins from the case cache, runs the quick scan and the
openultrasast:dev engine container (finding_dump.py, --network none,
--memory 3g, one at a time, per-pin deadline), writes engine findings in
the alerts.jsonl row shape (rule_id engine:<family>, source engine,
in_fix_range from case.json) with a summary (files read, questions,
completed, seconds, degradations per pin), and marks the task done via
reconciler.mark_done. No result, no files read, or questions == 0 fails
loudly and leaves the run untouched. Refuses a git checkout as source.
Runner image rebuilt and re-pinned (sha256:ebb40a9a...); validation-46
regenerated (digest only). Live, recorded in
benchmarks/measurements/2026-09-30-php-engine-alerts/: froxlor 366 files,
130/130 questions per pin, 6 alerts per pin, 0 in the fix range; wp-gopay
19 files, 101/101 questions, 0 alerts. The loop: 32 run rows (coverage 8,
php=engine), 0 proposals, gate no_proposals, $0.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
`ousast plane workspaces --validation-set ... --loop` appends the loop to a Run:
per case `alerts` (plane/tasks/alerts.py: the quick-mode scan on the vulnerable
and the fixed pin, a fixed-pin Workspace per case, alerts attributed to their
enclosing function by the repo-facts patterns, `in_fix_range` from the fix's
old-side and new-side ranges, failing on an unread tree) feeding `remember`,
then `memory-snapshot` -> `loop-measure` -> `loop-propose` -> `loop-improve`
(plane/tasks/loop.py). Every new task binds no Model and has budget
{usd: 0, calls: 0}. The snapshot is the store's rows after the train-on-test
guard, written on the host by memory.seed (a sandboxed run of it fails loudly);
propose runs M1/M2 against this repository at the commit under test; improve
runs one unchanged evolve.run_round and delivers gate.json, journal.json, the
sidecar, rule_policy.json only when accepted, and proposal_outcome rows that
the host ingests. Adoption stays a maintainer commit.
`remember` is now a Run entry per case (the image contains it), with the facts
row keyed by the image the facts were computed on (repo-facts records it in
its summary; unknown -> the row is omitted, never guessed). Alert rows carry
their own pin; improve/memory.py counts a repeated alert once.
Runner image rebuilt (+0.39 MB: only the new modules; the quick scan needs no
extra and the rulesets were already in the package), pushed, plane/ re-pinned
and regenerated (validation-46: 105 entries). Fixture test runs the whole loop
graph through the fake ax, whose new `exec` mode runs the real task modules.
Live: one loop Run over three validation-46 cases on the local ax, recorded in
benchmarks/measurements/2026-09-30-harnessx-removal-loop/ (all done, $0 new
spend, 0 proposals, gate verdict no_proposals).
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
On the live cluster the case clone ran at boot: the golden boot had no egress
policy, and the real actor was still being restored, so both TLS handshakes to
GitHub were cut. After the start the actor is RUNNING under its policy (the
delivery the same minute went through). Adds the one-case check Run (a subset
of validation-46) and re-pins the task manifests to the current runner digest.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
agree matched declared sites through benchmarks/independent/evaluate.py,
which the runner image does not carry, so site matching would have been
"not assessed". The generator now resolves the fix's old-side ranges
(evaluate.hunks, line for line) into case.json, with the declared sites in
the set and the reference's cost, and agree.matches_declared reproduces
matches_v2; a parity test runs both over the recorded outputs of the 15
validation cases (200 probes, identical verdicts) and agree on those outputs
returns the reference's 16 of 20 and $0.022.
agree reports cost_per_candidate (plane spend) and
cost_per_candidate_with_recorded_triage; Requirement 6.2 is judged on the
latter (design.md). --runner-image re-pins the templates from ops/ax/up.sh's
pin file; the committed manifests are regenerated at the current digest.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Model deepseek-flash (declared provider extension, endpoint prices in
parameters, secretKey naming the DEEPSEEK_API_KEY secret), digest-pinned
Task templates repo-facts / verify / agree, and a generator
(plane/generate.py, `ousast plane workspaces --validation-set ...`) that
emits per case the vulnerable-pin Workspace, a files-only inputs Workspace
(recorded candidates after the recorded triage, declared sites, triage),
per-case Tasks and one Run validation-46: facts -> verify a, verify b ->
agree for the 15 cases, 46 candidates (43 kept), budgets 1.5x the recorded
per-pass share. A Run entry cannot add a binding or env, and Run.inputs
names only task artifacts, so the case is fixed by per-case Tasks.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
