Off every active line (PATHFINDER-2026-10-13/03-unified-proposal.md, cuts).
Deleted: src/openultrasast/regress/ and the deep-mode REGRESS branch (deep
now records a regress_retired degradation and equals standard; proof is the
search-with-proof arm's job), the sandbox docker runner and probe that only
regress used, --fail-on worth-fixing, RegressConfig, the two ledger helpers
only regress called; skills.py and index.py with the hunter pool's skill
routing; model/audit.py; cpg/queries/vocabulary.sc with
benchmarks/push/ontology_gap.py. Docs and the scan skill describe the
retirement. Net: 3,895 lines deleted, 86 added. Targeted tests: 180 passed,
28 skipped; 3,331 tests collect.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
The standard scan now runs run_hunter_pool, verify_findings and the
deterministic fuse_findings directly; the HarnessX hunter orchestrator,
the LLM judge dispatcher (verify_judge.py, deleted with its test) and the
LLM fusion panels are gone, and so are their extra-absent degradations.
host_under_harnessx is dropped from stage_processors.
config: [models] verifier and [fusion] panel_model/decider_model raise
RetiredConfigError naming the plane replacement (the CLI prints it and
exits 2); a [harnessx] section loads with one warning and is otherwise
ignored. harness.json keeps "verifier": null. Tests that asserted the
fallback are renamed to the behaviour they assert; the module-audit
manifest drops verify_judge. Nothing outside the two modules deleted in
task 6 imports harness_ext or hunter_harness.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Token efficiency, measured on 180 verified pgAdmin candidates: stage 2 costs
$0.0139 per candidate, 90% of the spend, because the conversation is re-sent on
every turn and grows with each tool result.
- Context files now precede the question in the hunter's first message. DeepSeek
bills a cached prefix at 1/30 of a fresh one, by prefix; with the question first,
every candidate asked about the same file (about 5 per file) broke the prefix on
its first line and paid for the file again. A test pins the order.
- The verifier runs each candidate at 3 steps and repeats it once at 6 only when
the hunt spent every step on tool calls without a verdict. On the seven declared
v2 sites, 3 steps found 5 and 8 steps found 6; most candidates conclude in 3.
- Per-candidate token usage (prompt, cached, completion, calls) and escalation
are recorded, and each case reports its cache share, so the next efficiency
decision is made on numbers.
Validation on the 180 pgAdmin candidates plus the 22 known sites (about $1)
waits for account credit: DeepSeek returns 402 at the moment.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
The final-answer turn requested the provider's JSON mode with the tools still
attached. DeepSeek (deepseek-flash) then answered with the format itself
(`{"type": "json_object"}`), wrapped the array (`{"type": "json_object",
"value": [...]}`), or emitted its tool-call markup as text. A hunt that had found
the vulnerability reported nothing.
Measured on the v2 sink verifier with the declared vulnerable functions: 0 of 7
confirmed in JSON mode, 5 of 7 asked plainly (6 of 7 at 8 steps). The model named
Medplum's actual redirect-URI prefix-match bug, LMDeploy's redirect bypass of
_is_safe_url, and ContextForge's unsandboxed Jinja2.
The final turn is now plain text without tools. The parser also reads a
`{"value": [...]}` wrapper. Two tests that pinned JSON mode now pin the plain
turn, and a new test reproduces the wrapped answer.
Invalidates as measurements: the hunter experiment on v2 (c4a0bd8) and the first
sink-verifier run. Both used this turn.
Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Measured live against DeepSeek on one pair: the model spends its step budget
on tools and then answers in a paragraph that names the sink, the argument
and the line -- which parses as nothing. A detector that found the bug and
reported zero is indistinguishable from one that found nothing, and every
family in round zero would have baselined at zero for this reason alone.
The loop now takes one more turn when the hunt ends in prose or runs out of
steps, asking the provider for JSON and handing back the reasoning the model
already produced. It formats an answer that was reached; it never asks for a
new one, and a hunt that called no tool never gets there.
Same pair, same model, before and after: recall 0.00 -> 1.00, Youden 0.00 ->
1.00 over three runs per side.
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
