Closes#000027. Closes#000028 (cache-leg wired).
#000027 — canonical projections persist to providence_cache
============================================================
Math/logic π* answers (arithmetic@v1, logic-kernel@v1,
time-series-quantized@v1, …) are now first-class providence rows.
Pre-fix: question → kernel → answer → return. No cache, no audit
event, no run_dag, no inspect/burn/replay surface.
Post-fix: question → cache_key (8-dim, synthetic for the three
RAG-shaped dims) → lookup → on miss persist (providence_cache row +
providence_canonical audit event + canonical run_dag) → return.
Synthetic cache_key dimensions for canonical rows (per ticket §2.2):
- source_root = sha256("pi_star_source:" + pi_star_ref)
- model_profile_hash = sha256("pi_star_model:" + pi_star_ref)
- conversation_hash = sha256("pi_star_conv:" + canonical_q + ":" + ref)
- chunking_version = literal "n/a-canonical" — chunker bumps on
wikipedia path don't stale math answers.
The other dims (question_hash, governance_policy_hash, schema_version,
canonicalization_version) are real and shared with the RAG path.
Schema: audit_mode CHECK widened to admit 'CANONICAL_PROJECTION';
verifier_method CHECK widened to admit 'canonical_projection'. New
_rebuild_providence_cache_canonical_projection migration helper
follows the existing _rebuild_providence_cache_* pattern (temp-table
dance, additive value-space, fully idempotent). Wired into connect()
migration block alongside the prior CHECK extensions.
Cache-hit policy: trust the row. Kernel-version drift is handled by
pi_star_ref bumping (synthetic source_root changes → fresh row,
prior row stays in DB but unreachable via the live cache_key).
Re-running on every hit would defeat the optimization without
adding audit value the version-pin doesn't already provide.
Policy gate: canonical_projection_preflight_persist (default True).
Operators who want the legacy transient render-only behavior set it
to False — keeps the existing canon-CLI experience for tests /
probes / scripts that don't want audit-chain entries for math
questions.
CLI render: `CANONICAL · via canonical_projection` for persisted
rows. Works through the existing cache_hit / cache_miss_then_written
render path; no new render branch needed.
`arborist canon <key> "<input>"` stays transient — direct one-shot
probe, never persists. Boundary preserved per ticket §2.6.
#000028 — multi-modality witness cache-leg
==========================================
Pre-#000027 the witness cache-leg closure always returned None;
STRICT-WITNESSED (3-of-3 byte-equal) was structurally unreachable.
Post-#000027 the closure now returns the persisted answer bytes
when a prior canonical row exists. Three-way agreement
(kernel == cache == canonicalize(LLM)) is now reachable on the
second canonical-witness call.
New test test_query_canonical_witness_reaches_strict_after_persist
covers it end-to-end: first call writes the row + KERNEL-LLM-AGREE;
second call hits cache + STRICT-WITNESSED.
Tests
=====
- tests/test_canonical_cache.py: 16 new tests covering ticket §7
acceptance criteria (cache_key shape, persist round-trip, audit
event, hit-count increments, chain integrity, pi_star version
bump orphans old row, distinct refs namespace separately,
chunking_version sentinel, governance policy invalidates lookup,
canon stays transient, synthetic source_root encodes ref).
- tests/test_canonical_projection.py: assertions updated — status
is now cache_miss_then_written / cache_hit instead of
canonical_projection. Added a transient-mode test pinning the
policy gate.
- tests/test_witness.py: status assertions updated to reflect
persistence; new STRICT-WITNESSED test.
- tests/test_directives.py: D7 audit_mode enum test now admits
CANONICAL_PROJECTION (governance event — admissibility class
added).
Full suite: 1367 passed, 36 skipped (was 1306; +61 new).
Real-shard smoke
================
$ make query Q="0.1 + 0.2" BURN=1
→ cache_miss_then_written, ~300ms wall, row written
$ make query Q="0.1 + 0.2"
→ cache_hit, ~40ms wall, hit_count++
$ make chain-check-shards
→ 0 breaks per shard
`connect()` used to run executescript(SCHEMA_SQL) + 7 forward-
migration probes on every open. Profile of `who wrote virt-back?`
on 38 GB of real shards (warm cache) showed 588 connect() calls
per query, each running the full probe sequence — 10,623 total
SQLite executes. Migrations are forward-only and idempotent within
a code version, so once we've run them on a path in this process
there's no work to do on subsequent opens.
Cache shape: `set[str]` keyed by `str(Path(p).resolve())`.
Migration block runs once per (path, process); subsequent calls on
the same shard skip it entirely. Per-connection PRAGMAs
(foreign_keys=ON, synchronous=NORMAL, cache_size, temp_store,
mmap_size) still run every time — SQLite scopes foreign_keys
per-connection and our schema's FK CASCADE behavior depends on it.
That's why `PRAGMA foreign_keys = ON` moved out of the cached
SCHEMA_SQL block into the always-run pragma section.
Cache invalidation: explicit only.
`store.invalidate_migration_cache(path)` for callers who replace a
shard at the same path (snapshot-restore flows). `_clear_migration_
cache()` for tests. We don't auto-detect file replacement —
(dev, inode) is unreliable under tmpfs inode reuse, and (mtime,
size) drifts naturally as SQLite operates on the file (WAL
checkpoints, page growth). Path-only with explicit invalidation
is the honest contract.
Re-profile (same query, same shards, warm cache):
metric before after
_migrate_* (each function) 586 7 ← per shard
executescript 586 7
SQLite executes 10,623 3,687 (-65%)
wall (warm) 14.5 s 13.4 s
The warm-cache wall delta is small because the probes were many-
but-cheap; residual cost lives in FTS5 search (6.7 s) and
synonym_expand (2.8 s, both separate concerns). The 65% execute
drop is the cold-cache win — each redundant executescript() had
been triggering disk reads at the 75 s scale the reviewer reported.
Tests (6, all green): first connect runs all 7 probes, second
connect runs zero, schema integrity preserved across re-opens,
explicit invalidation re-probes, distinct paths each get one probe,
clear-cache helper works.
Full suite: 1306 passed, 36 skipped. Found and fixed an FK CASCADE
regression mid-implementation: PRAGMA foreign_keys = ON was inside
SCHEMA_SQL, so memoization was silently turning it off on subsequent
opens. test_burn_doc.py caught it. Moved to the per-connection
pragma block.
Ticket #000026 status: Phase 1 landed; Phase 2 (baseline artifact)
and Phase 3 (warrant-quality finding) queued.
`make query Q="0.1 + 0.2"` used to return `no_sources` because
arithmetic-shaped input has no FTS5 hits in any text shard. Two
surfaces close that gap.
**`arborist canon <key> "<input>"`** — direct π* call, no shards,
no LLM, no audit chain. Pure projection:
$ arborist canon arithmetic@v1 "0.1 + 0.2" → 3/10
$ arborist canon logic-kernel@v1 "A IMPL B" → (NOT A OR B)
$ arborist canon --list → registry contents
$ arborist canon --json arithmetic@v1 "0.1+0.2" → SHA-256 envelope
**Math/logic preflight in `arborist query`** — pure-arithmetic and
pure-propositional questions short-circuit RAG and answer through
arithmetic@v1 / logic-kernel@v1 directly. Synthetic
`audit_mode=CANONICAL_PROJECTION`, renders as
`CANONICAL · via <pi_star_ref>`:
$ arborist query "0.1 + 0.2"
0.1 + 0.2
CANONICAL · via arithmetic@v1 0.0s (projected)
3/10
$ arborist query "(NOT B) IMPL (NOT A)"
(NOT B) IMPL (NOT A)
CANONICAL · via logic-kernel@v1 0.0s (projected)
(NOT A OR B)
Sniff is conservative: pure-arithmetic shape (digits + ops, no
letters) or pure-propositional shape (uppercase atoms + reserved
keywords only). Natural-language wrapping ("what is 0.1+0.2?")
falls through to RAG. PiStarError on a shape match also falls
through — preflight is best-effort, never blocking.
Disable per-call: `--no-canonical-preflight` flag,
`policy["canonical_projection_preflight"]=False`.
No schema changes: CANONICAL_PROJECTION is a render-layer audit_mode
token. No providence_cache writes, no audit_events, no
governance_policy_hash bump. The canonical bytes ARE the answer;
SHA-256 of the bytes is the equivalence-class identity (already
committed via the π* registry).
Side housekeeping: arborist/pi_star/__init__.py docstring caught up
with reality — six concrete π*'s ship today, only tabular-pinned@v1
remains as a stub.
31 new tests (preflight sniff + dispatch, query short-circuit,
contrapositive equivalence-class collapse, CLI subcommand exit codes
and JSON envelope, --no-canonical-preflight policy gate). Full
suite: 1300 passed, 36 skipped.
Closes the math half of fox's 2026-05-08 roadmap question ("did we
implement the math and logic stuff?"). Until now arborist had logic
KERNELS (Syllogism, Truthtables, Transitivity sub-batteries with
deterministic evaluators) but no math π*'s. SQD whitepaper §14
framed math as "operations over π*-canonical invariant objects:
integers, algebraic expressions, proof states, constraint graphs"
— that framing is now actually implementable.
arithmetic@v1 — exact rational arithmetic (SQD §14.1)
-----------------------------------------------------
Parse arithmetic expression → fractions.Fraction → canonical
"<num>/<den>" in lowest terms. Decimals via Decimal(str(...)) for
exact rational interpretation:
"0.1" → "1/10" (not 0.1±ε)
"0.1+0.2" → "3/10" (the SQD-canonical floating-point question)
"1+2" → "3/1"
"(1+2)*3" → "9/1"
"6/4" → "3/2" (lowest terms via Fraction invariant)
"2**3" → "8/1"
"-(1+2)" → "-3/1"
Rejects: identifiers, function calls, division by zero, non-integer
exponents, boolean literals. PiStarError with explanatory message.
logic-kernel@v1 — propositional CNF canonicalizer (SQD §14.3)
-------------------------------------------------------------
Parse Boolean expression (AND/OR/NOT/XOR/IMPL/IFF + named atoms +
parens) → eliminate IMPL/IFF/XOR → push NOT inward (NNF) →
distribute OR over AND (CNF) → dedupe + sort literals + sort
clauses + drop tautological clauses → serialize.
Equivalence classes preserved:
A AND B ≡ B AND A (commutativity)
(A AND B) AND C ≡ A AND (B AND C) (associativity)
A IMPL B ≡ NOT A OR B (IMPL rewrite)
A IMPL B ≡ NOT B IMPL NOT A (contrapositive)
NOT (A AND B) ≡ NOT A OR NOT B (De Morgan)
NOT NOT A ≡ A (double negation)
A OR (B AND C) ≡ (A OR B) AND (A OR C) (distribution)
A OR NOT A → TRUE (tautology)
A AND A ≡ A (idempotence)
Atom cap: N=8 (256 max clauses). Larger inputs raise PiStarError;
CNF blow-up is exponential in atom count, the cap keeps
canonicalization deterministic in bounded time.
Surface
-------
- arborist/pi_star/arithmetic.py — full implementation (new file)
- arborist/pi_star/logic.py — full implementation (graduates from
stub; preserves the LogicKernelV1 dataclass shape so the registry
key arithmetic@v1 / logic-kernel@v1 stays stable)
- arborist/pi_star/__init__.py — imports arithmetic to auto-register
- bench/batteries/base.py — PHASE_1_CARRIERS adds "arithmetic" + "logic"
- bench/fixtures/5s/syntax-arithmetic-v1.jsonl (12 fixtures)
- bench/fixtures/5s/semantics-arithmetic-v1.jsonl (15 fixtures)
- bench/fixtures/5s/syntax-logic-v1.jsonl (12 fixtures)
- bench/fixtures/5s/semantics-logic-v1.jsonl (18 fixtures)
- Makefile: bench-5s-arithmetic, bench-5s-logic-kernel,
bench-5s-math aggregate
- tests/test_pi_star.py: 30 new tests
- 13 for arithmetic@v1 (decimals, equivalence, rejects, idempotency,
integer exponents, negative results, the SQD 0.1+0.2 case)
- 17 for logic-kernel@v1 (commutativity, associativity, all rewrite
rules, De Morgan, double-neg, distribution, tautology, idempotence,
contrapositive, atom cap, syntax errors, idempotency)
Cross-modality discipline now spans:
text + claim_lattice + memory + code + arithmetic + logic
— six carrier domains, all with real π* implementations.
Two stubs remain (time-series-quantized@v1, tabular-pinned@v1);
neither is needed for math/logic coverage.
Full suite: 1256 passed, 36 skipped (+30 tests, +57 fixtures).
Completes the bridge: every 5F sub-battery now has an embedded
(Phase 1a) AND a live (Phase 1b.2) path. Per-task detail.source
distinguishes synthetic from live signal.
| Sub-battery | Live surface | Live fixtures |
|---|---|---|
| Formulate | qa.parse_claims.parse_pointer_claims | 15 (prior) |
| Feedback Loop | store.append_audit + memory.snapshot (temp shard) | 12 (prior) |
| Function | parse_pointer_claims + shape evaluators | 12 |
| Finetuning | selfmodel.store_snapshot + claims_for round-trip | 10 |
| Falsification | qa.verify.verify_quotes (real verifier) | 12 |
Function live: input_text routes through real parse_pointer_claims;
the same Phase-1a shape evaluators (shape_match / pointer_set_match
/ threshold_on_metric) run on the live-parsed output. Tests
parser→shape pipeline against actual organism behavior.
Finetuning live: gated via fixture's "live": true flag. Runner
writes parent + child SelfModel + capability_claim to a fresh temp
shard via real arborist.selfmodel.store_snapshot, reads back via
claims_for, runs the same improvement check. Tests the SelfModel
persistence + claim-attach surface, not just static fixture data.
Falsification live: answer_text + context routes through real
arborist.qa.verify.verify_quotes. Live signals translate the
verifier's audit_mode + verifier_method + unverified_quotes into
flat tags (UNGROUNDED, STRICT_<method>, HYBRID_<method>,
UNVERIFIED_QUOTE) the runner matches against expected_reason. One
fixture (5f-fal-live-003) deliberately documents a known soft-
signal gap — the entity strategy treats Insulin/Penicillin claims
as equivalent because both share "Alexander Fleming". Production
catches it via title-relevance + claim-lattice verifier; the
fixture pins the soft-path limit so future verifier changes
re-trigger review.
Surface:
- bench/batteries/b_5f.py — _live_function_produced,
_live_finetuning_measure, _live_falsification_violations
helpers + two-mode dispatch in run_function / run_finetuning /
run_falsification.
- bench/fixtures/5f/{function,finetuning,falsification}-live-v1.jsonl
(12 + 10 + 12 fixtures).
- Makefile: bench-5f-{function,finetuning,falsification}-live
targets; bench-5f-live aggregate now covers all five sub-batteries.
- Tests: 9 new in tests/test_bench_batteries.py
- live + embedded paths for each sub-battery (6 tests)
- direct helper tests verifying the real arborist surfaces are
invoked, not stubs (3 tests)
Phase 1a fixture digests unchanged. _DEFAULT_FIXTURES still points
at synthetic Phase-1a fixtures so `runner --all` behavior is
identical and deterministic; live mode invoked via explicit
--fixtures path or make targets.
Full suite: 1210 passed, 36 skipped.
5F battery is now the first to bridge synthetic→live across every
sub-battery. The pattern + live fixture format are reusable for
5R Phase 1b.2 (when SelfModel-backed workspace ops want live
verification).
Second live wire-up (after Formulate). run_feedback_loop now supports
both modes:
- Embedded (Phase 1a): chain of (operation, observation) string pairs;
runner aggregates observations and string-matches expected_delta.
- Live (Phase 1b.2): live_chain of typed ops applied to a fresh temp
arborist shard via real append_audit + memory.snapshot +
selfmodel.snapshot. expected_delta is a dict of predicates against
the resulting audit_events / memory_branch_summaries.
The live helper _live_feedback_chain creates a tempfile-backed shard,
runs the chain through real arborist surfaces, and queries the final
state. Every audit event chains via the production append_audit, so
the audit chain is re-verifiable after live execution (see new test
test_5f_live_feedback_chain_audit_chain_intact).
Three predicate types in expected_delta:
- audit_event_type_present: named event_type appears in audit chain
- memory_branch_present: named branch_id in memory_branch_summaries
- body_substring_present: substring appears in any audit body JSON
Surface:
- bench/batteries/b_5f.py — _live_feedback_chain helper +
_live_delta_satisfied predicate checker; two-mode dispatch in
run_feedback_loop
- bench/fixtures/5f/feedback-loop-live-v1.jsonl — 12 live fixtures
exercising providence_write, providence_repair, memory_snapshot,
selfmodel_snapshot ops. Includes 2 negative fixtures testing the
predicate checker (expected_delta absent → expected:fail).
- Makefile: bench-5f-feedback-loop-live + bench-5f-live aggregate
for all 5F Phase-1b.2 live wire-ups.
- Tests: 5 new in tests/test_bench_batteries.py
- live path runs all 12 fixtures
- embedded path still works (10 Phase-1a fixtures)
- helper directly tests audit-event write
- rejects unknown live op type
- audit chain re-verifies after live ops
Two of the five 5F sub-batteries now bridge synthetic → live
(Formulate + Feedback Loop). Function/Finetuning/Falsification
follow in subsequent commits.
Full suite: 1201 passed, 36 skipped.
First sub-battery to bridge from synthetic gold output to actual
organism behavior. run_formulate now supports two fixture modes
selected per-task:
- Embedded (Phase 1a): produced_lattice in the fixture. 10 seed
fixtures continue to pass via this path.
- Live (Phase 1b.2): only input_text in the fixture; runner calls
arborist.qa.parse_claims.parse_pointer_claims(input_text) and
matches the live output against expected_lattice.
Embedded takes precedence if both fields are present. Per-task
detail.source ("embedded" | "live") surfaces in bench output so
synthetic vs live signal is distinguishable.
Surface:
- bench/batteries/b_5f.py — _live_produced_lattice helper +
two-mode dispatch in run_formulate
- bench/fixtures/5f/formulate-live-v1.jsonl — 15 live-mode fixtures
with input_text + expected_lattice (no produced_lattice)
- Makefile: bench-5f-formulate-live target
- Tests: 4 new in tests/test_bench_batteries.py
- live path routes through real parser, all 15 pass
- embedded path still works (10 Phase-1a fixtures)
- _live_produced_lattice helper directly verifies parse output
- fixture missing both fields fails cleanly with explanatory reason
Phase 1a fixture digests unchanged. _DEFAULT_FIXTURES still points
at formulate-v1.jsonl so `runner --all` behavior is identical;
live-mode fixtures invoked via explicit --fixtures path.
Full suite: 1196 passed, 36 skipped.
Pattern set. Function/Finetuning/Falsification/Feedback Loop
follow in subsequent commits.
Phase 2 of #000021. React/Rearrange/Restore/Replicate/Resonate over
the workspace surface — selfmodel_records (#000014) + memory_records
(#000017), both landed earlier today. Closes the gap that gated 5R
since the substrate work shipped.
Sub-battery semantics (per SQD whitepaper §9.3 + ticket #000021 §4.2):
- React: incorporate new fact/constraint. Workspace = (snapshot_t0,
snapshot_t1, expected_delta). Pass = added_facts present + removed_facts
absent in t+1.
- Rearrange: restructure without semantic shift. Re-canonicalize
different surface forms through a named π*; pass = bytes match
expected_equivalent flag. Tests the order-invariance contracts in
SelfModel (capability_claim_hashes sorted) and Memory (branches
sorted by branch_id).
- Restore: retrieve prior fact. Workspace = (history[], current_facts[]).
Pass = fact in current OR any historical snapshot.
- Replicate: independent canonical encodings via π*. Same input run
N times must yield byte-equal output. Tests determinism contract.
- Resonate: variance across N runs. Deterministic π*'s yield
distinct=1; expected_max_distinct=1 enforces zero-variance contract.
Surface:
- bench/batteries/b_5r.py (5 deterministic runners; no LLM-as-judge)
- bench/fixtures/5r/{react,rearrange,restore,replicate,resonate}-v1.jsonl
(30 each = 150 new fixtures)
- runner.py registers 5r in _BATTERIES + _DEFAULT_FIXTURES
- Makefile: bench-5r + bench-suite (5S+5T+5F+5R aggregate)
Final tally:
5S syntax/semantics/syllogism/synthesis/semiotics 108
5T transfer/transfer-learning/triangulation/... 154
5F function/finetuning/falsification/... 50
5R react/rearrange/restore/replicate/resonate 150
TOTAL: 462 fixtures across 21 sub-batteries — 100% pass.
Tests: 6 new in tests/test_bench_batteries.py + adjustment to
test_session_integration.py for the 312→462 count + 5R sub-battery
presence assertion. Full suite: 1192 passed, 36 skipped.
Closes#000021. Phase 3 (external-corpus expansion) remains open
under the ticket but does not gate closure — the complete
Dav1DPrometheus surface is now executable infrastructure.
Per fox's 2026-05-08 review of fbd99a8: implement adaptation_efficiency
and feedback_efficiency in run_finetuning + run_feedback_loop with
explicit sentinels — not Python floating-point accidents.
_efficiency(gain, cost) helper:
- cost > 0: standard ratio
- cost == 0, gain > 0: EFFICIENCY_INFINITE (free improvement)
- cost == 0, gain == 0: EFFICIENCY_UNDEFINED (= 0.0; no signal)
- cost == 0, gain < 0: -EFFICIENCY_INFINITE (free regression)
Battery-level metrics report mean_finite (computed over finite
values only) + infinite_count + neg_infinite_count so the mean
stays dimensionally truthful and consumers can pivot on the special
buckets separately.
Phase 1a cost proxies:
- run_finetuning: _capital_cost_delta sums resource_budget
(max_compute_ms_delta * 1e-3 + max_storage_delta_bytes / 1e6).
Phase 1b.2 will replace with real capital_ledger reads.
- run_feedback_loop: chain length = cost. Phase 1b.2 capital_ledger
integration replaces it.
Tests added (7):
- _efficiency over four boundary cases
- 5F finetuning + feedback_loop emit the new metrics keys
- Synthetic zero-cost finetuning fixture verifies +inf path
Full suite: 1110 passed, 36 skipped.
Closes the one actionable from the fbd99a8 review.
Per fox's "partial punt on larger ones" — ships the bench/ skeleton +
small seed fixture sets so future v8/v7-W/SelfModel work can cite a
real fitness target. Full Phase 1 (50-200 fixtures per sub-battery)
and Phases 2-3 stay open in the ticket.
Phase 1a delivers:
- bench/batteries/{base,b_5s,b_5t,runner}.py — Battery protocol,
BatteryResult, fixture-digest helpers, CLI runner.
- Seed fixtures:
- bench/fixtures/5s/syntax-v1.jsonl — 10 tasks against
wikitext-base@v1 and claim-lattice@v1
- bench/fixtures/5s/semantics-v1.jsonl — 8 equivalence tasks
- bench/fixtures/5t/transfer-v1.jsonl — 4 paraphrase-invariance
tasks
- Runners for 5S Syntax, 5S Semantics, 5T Transfer. Other 5S/5T
sub-batteries are stubs returning zero-task results.
- Makefile targets: bench-5s, bench-5t, bench-5s5t.
- runtime_digest field captures the active π* registry fingerprint
so a registry change surfaces in bench results.
Tests: tests/test_bench_batteries.py (17 cases). Full suite:
1076 passed, 36 skipped. `make bench-5s5t` runs end-to-end and
emits JSON results.
Ticket #000021 status: in progress · Phase 1a landed; Phase 1b/2/3
remain open.
New arborist.pi_star/ namespace centralizes canonical projections
under a name@version registry. Two existing canonicalizers re-homed
as registered π*'s:
- wikitext-base@v1 wraps arborist.wikitext.to_base
- claim-lattice@v1 wraps arborist.qa.parse_claims.parse_pointer_claims
Four stubs registered for follow-up modality tickets:
code-py-ast@v1, logic-kernel@v1, time-series-quantized@v1,
tabular-pinned@v1 — each raises NotImplementedError with a pointer
to ticket #000015.
Composition algebra in compose.py: PiStarComposition exposes
outer ∘ inner as a first-class π* with its own registry key
(default "<inner-name>-then-<outer-name>@v1"). canonical_composition_id
returns a SHA-256 fingerprint suitable for governance hash inclusion.
Order-sensitive: a∘b ≠ b∘a → different fingerprints.
Documentation: docs/pi-star-composition.md covers the rule (type-
compatible, deterministic, equivalence-class preserving), lossy vs
invertible compositions, worked text→claim-lattice example,
cross-domain anchor projections (future), authoring checklist.
Re-home is non-breaking: arborist.wikitext.to_base remains importable.
Tests: tests/test_pi_star.py (19 cases). Full suite: 1059 passed,
36 skipped.
CapitalProfile (8 forms: living, material, financial, intellectual,
experiential, social, cultural, spiritual) attached per state-changing
op as a sibling-table row in capital_ledger. Sibling semantics: ledger
rows reference an audit_event_hash but do NOT enter the audit-event
preimage, so retroactive cost re-estimation cannot break the chain.
Surface:
- arborist.capital.{profile,store}
- profile_for_op dispatch with per-op estimators (ingest/qa/distill)
- record/summary/op_cost/top_by_form
- CLI: arborist capital summary|op-cost|top
Wire-up at three op sites:
- ingest.py — one row per batch (doc_count + total_bytes)
- qa/runner.py — one row per cache-miss (answer_chars + llm_seconds)
- distill/runner.py — one row per derivation (positive intellectual)
Estimator constants are heuristic v1 (ESTIMATOR_VERSION pin in the
schema). Re-estimation is supported by re-running estimators against
the recorded inputs_blob and writing a new row with a bumped version
pin; old rows stay queryable.
Tests: tests/test_capital.py (13 cases). Sibling-table invariant
verified: audit chain stays intact across capital writes.
Full suite: 1025 passed, 36 skipped.
SelfModel binds an arborist agent's identity to bytes a verifier can
recompute: model_profile_hash, verifier_method_root, governance hash,
canonicalization/chunking versions, optional patch + memory roots,
sorted capability-claim hashes. Hard-hash committed; no soft state in
preimage. State transitions live on the row, not the body, so the
selfmodel_root stays stable across live → stale → falsified.
Surface:
- arborist.selfmodel.{canonical,snapshot,store,falsify}
- CLI: arborist selfmodel snapshot|show|falsify|list
- Schema: selfmodel_records + selfmodel_capability_claims (additive)
- Audit events: selfmodel_snapshot_landed,
selfmodel_capability_claim_added, selfmodel_falsified,
selfmodel_marked_stale (all chain via existing append_audit)
Also folds in:
- CLAUDE.md operational rule: arborist stays Python-only; non-Python
toolchains live in sibling repos. Forks/clients/servers in any
language follow our schemas + canonical encodings.
- Ticket #000016 update: ZK lives in sibling repo arborist-zk-bench;
arborist gains at most a wire-format consumer, never a Rust dep.
- Schema migrations also stub capital_ledger and memory_records
tables for tickets #000020 and #000017 respectively (additive,
empty until those modules land).
Tests: tests/test_selfmodel.py (14 cases; canonical-JSON stability,
root order-invariance, snapshot determinism, store idempotency,
audit events, falsify/mark_stale semantics, audit-chain integrity).
Full suite: 1012 passed, 36 skipped.
Big batch — closes 4 of the 5 deferred items from the prior status
report plus opens & implements a previously-deferred design ticket
(#000011) zero-shot.
#000025 — Metacog test fixture expansion:
bench/qa_questions_metacog_subset.txt grows from 6 → 28 questions
covering edge cases per detector kind: temporal (4 cases),
contradiction (4), false-premise (5), out-of-corpus (3), multi-
trigger (2), well-formed controls (5). Documents two known
detector ceilings: Q11 over-fires on past-tense factoid
("who was the first president"); Q16/Q17/Q19 (Edison/Australia/
NASA-fake) miss false premises that lack a presupposition
pattern match. Fixture now serves as long-term regression suite.
#000026 — --show-preflight full clause render:
build_run_dag() and build_reject_run_dag() gain optional
preflight_payload kwarg. When supplied, the canonical 5-clause
CTI payload (classifier / answer_contract / prompt_contract /
evidence_contract / policy_refs + question_state + node_version)
persists alongside the leaf hash in run_dag_blob.
aborist providence --show-preflight CACHE_KEY now renders the
full payload + verifies the persisted hash matches the
recomputed canonical hash (audit-replay tamper detection).
Legacy rows fall through cleanly: payload_hash_check reports
"unavailable: legacy row predates preflight_payload persistence".
#000027 — Latency profile:
Microbenched preflight: 0.46ms/question (negligible). Single
fresh call breakdown: search 2.4s, llm 2.8s, total 5.4s — the
33-35s in Addendum 3 was vLLM concurrency contention at c=4
(per qa-modes-bench.md saturation note), not substrate
overhead. Added preflight_ms + soft_preflight_ms to timings
dict for explicit confirmation in future cycles.
#000028 — Auto-quality-check sweep revival:
scripts/bench_emergent.py running with EMERGENT_N=100 in
background (PID 125680). Will accumulate cycles into
bench/emergent_log.jsonl for #000006 rolling log re-aggregation.
Async — not blocking on completion.
#000029 — #000011 SOFT_PREFLIGHT_HINT implementation:
aborist/qa/soft_preflight.py — new module. SoftPreflightHint
dataclass + soft_preflight_question() pure function. 9
canonical labels mapping to soft analogues of #000010 hard
detectors plus 2 stub states (SOFT_DISABLED, SOFT_PARSE_FAIL).
Constrained-generation prompt (max_tokens=128, temp=0.0) asks
the model to pick ONE label + one-line rationale.
Fail-closed across every parse path:
- chat_client raises → SOFT_PARSE_FAIL
- response unparseable → SOFT_PARSE_FAIL
- label outside enum → SOFT_PARSE_FAIL
Sidecar enforces SOFT_ prefix at the normalize step so a
model that drops the prefix still gets caught.
Wired into query() between preflight & retrieval. Default
OFF (`soft_preflight_enabled: False`). NOT folded into
_VERIFIER_POLICY_FIELDS — soft hints don't gate cache
identity (#000011 §4). Audit-line tail renders as
"· soft: <label>" (e.g. "· soft: time sensitive") so the
signal is visually distinct from hard tails.
--soft-preflight CLI flag opts in per-call. End-to-end
live-verified on "When did Mr. Burns become Homer's biological
father?" — produces:
EVIDENCE-WARRANTED · via claim_lattice
· false premise · soft: time sensitive
1/1 16.4s
Hard `· false premise` (from #000010 deterministic detector)
composed with soft `· soft: time sensitive` (from #000011
sidecar). The model classified a different shape than the hard
detector — by design; soft hints are independent advisory
signals, not redundant with the hard layer.
25 new tests pin: default-OFF behavior, parse-failure modes,
label normalization (SOFT_ prefix enforced), all 8 actionable
labels round-trip, fail-closed on client exceptions, dataclass
JSON round-trip, rationale-length cap.
Other:
- #000010 §13.3 documents 2/5 metacog-trigger questions return
STRICT despite hard-detector warning — direct empirical
motivation for #000011 design.
- tests/test_dag.py extends with 3 _extract_preflight_hash_*
helper tests (cleaning #000009 §7.2 unfinished state).
- bench/emergent_log.jsonl adds new cycles from background run.
#000011 status: closed. Hard rule (D1) preserved across all
1021 tests (up from 996, +25 new). Soft preflight is purely
advisory; the verifier proof path is unchanged.
Fan-out execution of the deferred-but-not-blocking pile from
prior status reports.
#000009 §7.2 — bench harness preflight_hash field:
- aborist/qa/query.py surfaces `preflight_hash` on result dict
(miss path, reject path, and cache-hit path via new helper
`_extract_preflight_hash_from_blob` that pulls the stage hash
out of persisted run_dag_blob).
- bench/qa_sweep.py adds 12-char preflight_hash prefix to bench
rows. Mirrors cache_key truncation pattern. Operators can
grep / SQL-filter bench JSONL by preflight policy state.
- 3 new tests in tests/test_dag.py for the extract helper.
#000009 §7.2 — `aborist providence --show-preflight CACHE_KEY_PREFIX`:
- New CLI flag pulls the preflight stage payload from a row's
run_dag_blob. Match by 12-char prefix. Renders preflight stage
hash + run-DAG stage list. Operator tool for inspecting which
policy state governed a cached row.
- Live verified on a real cache row (8a212fecb2a9 — current CEO
of OpenAI question, 10-stage CTI shape with preflight at idx 1).
- Legacy rows (predating #000009) report a clean fall-through
message: "run_dag has no preflight stage (predates #000009)".
#000010 §12.6 — reference-frame plumbing into QuestionState:
- Pre-retrieval preflight runs with reference_frames=()
(frame_detection needs source titles, not available yet).
Post-retrieval, query.py re-runs preflight_question() with
the detected frames so the result-dict + run-DAG QuestionState
carry frame-aware logical_statuses (specifically
`reference_frame_ambiguous` when 2+ frames match).
- Live verified on Orwell-style question; logical_statuses now
correctly includes `reference_frame_ambiguous` in the result.
Metacog-trigger bench fixture (#000010 §13.3):
- bench/qa_questions_metacog_subset.txt — 6 questions, one per
detector kind plus a well-formed control.
- Bench artifact 2026-05-04T02-18-42Z. Detector accuracy 6/6
on fixture; 2 of 5 trigger questions return STRICT on lattice
mode despite metacog warning (JSON STRICT on
George-Washington-stop-being-president-of-France false-premise
+ uploaded-contract out-of-corpus questions). Audit-line tails
correctly surface the warnings.
- qa-modes-bench.md Addendum 4 captures the per-question matrix
+ interpretation. #000010 §13.3 cross-references with bench
artifact stamp.
#000011 SOFT_PREFLIGHT_HINT design ticket opened:
- docs/tickets/ticket-000011-soft-preflight-hint-sidecar.md
captures the design proposal per #000010 §18 / source doc.
Implementation deferred — design only.
- Sidecar would add model-assisted preflight as a soft signal
(`SOFT_FALSE_PREMISE_SUSPECTED` etc.) that NEVER enters the
verifier hard path. Strict guardrail: cannot create
PREFLIGHT_OK or PREFLIGHT_BLOCKED without deterministic
support.
- Validated by §13.3 finding: deterministic detectors flag
correctly; corpus-accidental grounding produces 2/5 STRICT
on trigger questions; soft sidecar would add independent
semantic skepticism.
- TICKETS.md index row added; Next ID bumped to 000012.
996 tests passing (3 new for the extract helper).
Cross-doc consistency:
- qa-modes-bench.md Addenda 1+2+3+4 chronological
- #000010 §13.1 (broad subset) + §13.2 (full bench) + §13.3
(metacog trigger subset)
- #000011 design captured but not implemented
Architectural feedback at ~/Downloads/RESPONSE-ticket-000009-... .txt
(2026-05-04) flagged five gaps in the c36e85c landing. Most
critical: reject-broad early-return path emitted no run_dag_blob,
so audit replay couldn't see that a rejection happened (let alone
under what policy state).
A — reject-path DAG (the critical gap):
aborist/qa/dag.py: build_reject_run_dag() — 3-stage minimal DAG
question → preflight → final_label. final_label payload carries
rejection_reason + answer_text_hash so two rejections under
different policy state produce different roots.
query.py reject path now wires it: returns run_dag_root +
run_dag_blob on the rejection result dict. Live-verified end-
to-end on `make query Q="winners of all major sports?"
REJECT_BROAD=1 BURN=1`.
Audit replay rule: 3 stages always means reject path. Operators
can read the stage list and tell instantly without parsing the
payload.
B — nested CTI clauses:
preflight_node_hash() payload restructured from flat 3-key to
nested 5-clause:
classifier — quantifier classifier output (#000008)
answer_contract — guard / cap / reject / metacog state (per-run)
prompt_contract — reminder enabled / injected / template_id
evidence_contract — exposure budget, line discipline
policy_refs — governance_policy_hash, model_profile_hash,
answer_mode (reference, not raw policy)
Plus question_state (metacog) as its own clause and top-level
stage + node_version. Single DAG stage; nested clauses inside
for diff legibility (feedback §3).
C — node_version field:
PREFLIGHT_NODE_VERSION = "preflight-node-v1" pinned in the
payload so legacy runs without the node can be unambiguously
labeled `unavailable_legacy_run` by audit tools (feedback §9).
D — reference hashes only:
policy_refs uses governance_policy_hash + model_profile_hash
rather than bundling raw policy booleans. Avoids
double-committing already-hashed state (feedback §4).
E — reminder_template_id:
prompt_contract.reminder_template_id = "broad-quantifier-bounded-v1"
or "broad-quantifier-unbounded-v1" depending on scope_bound_hint,
populated only when reminder actually fires.
F — stage name kept as `preflight` (not `quantifier_preflight`):
Node carries both #000008 quantifier AND #000010 metacognition
payloads. node_version disambiguates schema for audit tools.
G — docs/cti-architecture.md update deferred to a small follow-up.
Bug fixes:
- free-variable shadowing on verifier_policy_hash /
model_profile_hash / question_hash — local re-imports inside
the reject branch shadowed module-top imports used elsewhere
in query() / runner(); now use the module-top names.
- reject path question_hash signature: takes `mode=` not
`dedup_mode=` — fixed in the reject DAG builder caller.
Hash compatibility:
Rows written between c36e85c and this commit have hash payloads
matching the OLD flat 3-key shape. The persisted run_dag_blob
captures the actual payload that was hashed, so those rows
still verify via verify_run_dag(). New rows use the nested
5-clause shape.
7 new tests in tests/test_dag.py:
- hash sensitivity to answer_contract / prompt_contract /
policy_refs flips (audit-replay payoff demonstrations)
- PREFLIGHT_NODE_VERSION pinning
- reject DAG: 3-stage shape, root changes with preflight hash,
round-trips through verify_run_dag
993 tests passing (6 net new); 36 skipped.
Live verification:
make query Q="winners of all major sports?" REJECT_BROAD=1 BURN=1
→ status=broad_quantifier_rejected, run_dag_root populated,
blob carries 3-stage shape.
make query Q="winners of all major sports?" BURN=1
→ 10-stage shape preserved (question → preflight → retrieval
→ ... → final_label).
Ticket #000009 status: closed · re-landed 2026-05-04 with §8
corrections.
Closes ticket #000009 zero-shot. Scope expanded to cover BOTH
ticket #000008 (broad-quantifier) AND ticket #000010
(meta-cognition) preflight contracts in a single combined node —
both share the same audit-replay gap and inserting two separate
nodes between question and retrieval was operationally awkward.
aborist/qa/dag.py:
+ preflight_node_hash() — combines QuestionState +
quantifier classifier output + behavioral policy_state into
one canonical SHA-256 hex.
+ build_run_dag() gains optional preflight_hash parameter.
When supplied, inserts {"stage": "preflight", "hash": ...}
at position 1 (between question and retrieval).
Backward-compat: None → original 7/9-stage shapes preserved
for legacy run_dag_root re-validation.
Quote-mode: 7 → 8 stages with preflight.
Pointer-mode CTI: 9 → 10 stages with preflight.
aborist/qa/query.py + runner.py:
Both build the preflight payload from question_state +
quantifier dict + 10-field policy_state (guard_enabled,
guard_apply_caps, guard_apply_caps_mode_gated,
claim_cap_resolved, claim_cap_actually_applied,
reminder_enabled, reminder_eligible, reject_broad_active,
metacognition_enabled, block_on_contradiction).
This means two cache rows that share the same question + same
model output + same verifier verdict but DIFFERENT preflight
policy state now produce different run_dag_root values. Audit
replay can pin the policy decision per row.
9 new tests in tests/test_dag.py:
- preflight_node_hash determinism
- hash bumps on question_state change
- hash bumps on policy_state change (the audit-replay payoff)
- all-None defensive shape
- 7→8 stage transition (quote mode)
- 9→10 stage transition (pointer mode), preflight at index 1
- run_dag_root bumps when preflight_hash bumps
- verify_run_dag round-trips through preflight stage
Live verification: latest providence_cache row carries
['question', 'preflight', 'retrieval', 'evidence_map', 'prompt',
'raw_answer', 'parsed_claim_lattice', 'verify', 'render',
'final_label'] — preflight stage living in the persisted DAG.
987 tests passing (9 new); 36 skipped.
Tickets:
#000009 status: closed · landed 2026-05-03 (zero-shot)
#000010 cross-ref updated: "DAG binding shipped via #000009"
What's NOT in this ticket (logged in §7.2):
- CLI flag for inspecting preflight node from cache_key
- Bench harness preflight_hash field for cross-row comparison
- SOFT_PREFLIGHT_HINT (model-assisted preflight sidecar)
Closes ticket #000010 (Meta-Cognition Preflight Guard). Mechanism
complete; defaults preserve the dry-run discipline pattern from
#000008.
Phase 2 — wire preflight into query() and runner.ask():
- preflight_question() runs after policy resolution + quantifier
classification, before retrieval.
- QuestionState surfaces on miss path, cache-hit path, AND
reject-broad early-return path of query() — schema column-
aligned across all four returns.
- runner.ask() carries the same fields for `aborist ask` parity.
Phase 3 — policy fields + governance hash + CLI flags:
- 6 new policy fields, all default-on except
metacognition_block_on_contradiction (default False — label-
only by default; opt-in via --block-on-contradiction).
- All 6 folded into _VERIFIER_POLICY_FIELDS so flipping any
invalidates prior cache records on lookup.
- 2 new CLI flags on `aborist query`:
--no-preflight Level 2 master kill
--block-on-contradiction strict mode (hard-block on
lexical contradictions)
Phase 4 — audit-line labels + bench fields + tests:
- _render_warrant_tail extended with 5 metacog tail tokens:
· false premise
· contradictory
· stale risk
· out of corpus
· frame ambiguous
- Bench rows in qa_sweep.py gain 7 new bounded-size projection
fields (logical_statuses, question_shape, preflight_result,
temporal_sensitivity, has_false_premise, has_contradiction,
corpus_requirement). Full QuestionState stays on result dict
for CLI render only.
- tests/test_metacognition.py grew from 42 → 68 tests
(16 new: 6 governance + 6 audit-line tail + 4 default-policy
pinning).
Live verified end-to-end:
$ make query-dry Q="Who is the current CEO of OpenAI?" BURN=1
UNGROUNDED · via claim_lattice · stale risk
$ make query-dry Q="When did Mr. Burns become Homer's biological
father?" BURN=1
UNGROUNDED · via claim_lattice · false premise
978 tests passing; 36 skipped.
What's NOT shipped (deferred):
- Run-DAG node binding for metacognition_preflight stage —
joins ticket #000009 Phase 5 (same audit-replay gap; both
nodes can land together).
- Reference-frame plumbing — frame_detection runs post-retrieval,
preflight here is pre-retrieval; deferred until two-pass
or post-classification update lands.
- SOFT_PREFLIGHT_HINT (model-assisted sidecar) — source doc §18
reserves this label; hard rule preserved (no LLM in preflight
hard path).
- Bench A/B measuring preflight on vs off — quick to run once
stack settles.
Ticket #000010 status: closed · landed 2026-05-03.
Implements the Meta-Cognition Preflight Guard (M0 / MCTL) per
fox's directive at ~/Downloads/meta-cognition_for_hermes(1).txt
(2026-05-03).
aborist/qa/metacognition.py:
- QuestionState dataclass (frozen, JSON-serializable via to_dict)
- preflight_question() pure function: classifies a question
deterministically into a QuestionState before generation
- 4 new detectors:
detect_temporal_sensitivity() — current/latest/today/CEO/etc.
detect_contradiction() — lexical pairs (unmarried+spouse,
always+never, alive+dead, etc.)
detect_false_premise() — presupposition patterns:
when did X stop/become Y,
why did X cause Y,
how did X become Y
detect_out_of_corpus() — my-uploaded-X / file-I-sent shapes
- Reuses #000008 quantifier classifier (no duplication)
- Composes 8 LogicalStatus values:
well_formed, under_specified, false_premise_suspected,
contradictory_question, out_of_corpus_risk, stale_risk,
reference_frame_ambiguous, broad_quantifier_unbounded
- Three preflight results: PREFLIGHT_OK / _PARTIAL / _BLOCKED
- Per-detector enable switches in policy:
metacognition_enabled (master kill)
metacognition_temporal_check
metacognition_contradiction_check
metacognition_false_premise_check
metacognition_out_of_corpus_check
metacognition_block_on_contradiction (default False — label
only by default; opt-in
to hard-block)
- preflight_policy_hash for governance binding (Phase 3)
- PREFLIGHT_VERSION = "metacognition-v0.1"
Hard rule (D1): no LLM in this hard path. Pure regex + lexical
matching. Model-assisted preflight, if added later, labels itself
SOFT_PREFLIGHT_HINT (not implemented in this phase).
42 new tests cover the seven test cases from source doc §14
(false-premise, contradictory, broad-quantifier, reference-frame,
time-sensitive, out-of-corpus, model-cutoff) plus per-detector
unit tests, gating (master kill, per-detector disable,
block-on-contradiction opt-in), determinism (question_hash
stable, policy_hash bumps on flip), and serialization.
Ticket #000010 opened with status `open · in progress
(zero-shot 2026-05-03)`. TICKETS.md index updated; Next ID bumped
to 000011.
Phases 2-4 still queued (wire into query/runner, policy fields +
governance, audit-line labels + bench fields).
962 tests passing (42 new); 36 skipped.
n=5 verification of cap+reminder cell (135 runs):
Metric | n=3 | n=5
--------------------+-----------+------------
JSON SR | 0.30 | 0.33 ← matches cap-only
JSON UNGROUNDED rate| 1/27 (4%) | 2/45 (4%) ← matches reminder-only
pointer SR | 0/27 | 0/45 ← unchanged across all cells
The §12.8 0.30 was Hermes nondeterminism. n=5 confirms cap+reminder
delivers cap-only's STRICT-rate AND reminder-only's UNGROUNDED-rescue.
§10.8 strict gate met at n=5:
vs reminder-only on JSON SR: +11pp (clears floor)
vs cap-only on JSON UNGROUNDED: -18pp (clears floor)
vs cap-only on ptr mean ratio: +12pp (clears floor)
Defaults flipped — Option A landing (per-mode tailored):
quantifier_reminder_enabled False → True
(load-bearing on both lattice modes)
NEW field: quantifier_apply_caps_modes = ["claim_lattice"]
(allowlist for which modes apply caps
when apply_caps=True; JSON-only since
cap-on-pointer is wasted noise per
§12.10 0/45 STRICT data)
quantifier_guard_apply_caps False → False (UNCHANGED)
(operator opts in via
--apply-quantifier-caps; preserves
§10.11.3 dry-run discipline)
Cap-application gate now reads:
if apply_caps AND mode in apply_caps_modes AND cap is not None:
effective_max_claims = looked_up_cap
quantifier_apply_caps_modes folded into _VERIFIER_POLICY_FIELDS so
flipping the allowlist invalidates prior cache records.
5 new tests pin: reminder default ON for both runner.DEFAULT_POLICY
and query.DEFAULT_QUERY_POLICY; apply_caps_modes default
["claim_lattice"]; governance-hash invalidation on allowlist flip;
apply_caps default still False (dry-run preserved).
920 tests passing (5 new); 36 skipped.
Operator behavior:
$ aborist query "winners of all major sports?"
→ reminder ON, cap OFF (default after this commit)
$ aborist query --apply-quantifier-caps "..."
→ cap applies on claim_lattice (JSON) only
$ aborist query --apply-quantifier-caps \
--policy quantifier_apply_caps_modes='["claim_lattice","claim_lattice_pointer"]' "..."
→ Option D for one call
Phase 5 (run-DAG node binding for quantifier_preflight) and
cross-model Qwen/GPT-4 verification remain as follow-ups per §11.11.
Caught by the 2026-05-03 dry-run distribution review across the
73-question bench set (§10.11.3 step 2):
intensity pre-fix post-fix
SINGULAR 61 (84%) 65 (89%)
MANY 4 ( 5%) 0 ( 0%) ← all 4 were `how many X?`
ALL 1 ( 1%) 1 ( 1%)
COMPREHENSIVE 1 ( 1%) 1 ( 1%)
OPEN_REQUEST 5 ( 7%) 5 ( 7%)
SMALL_NUM 1 ( 1%) 1 ( 1%)
Defect: `how many states are there?` matched the bare `\bmany\b`
pattern in MANY rung — wrong. `how many X?` is a count-question
SHAPE, asking for ONE numeric answer ("50"), not enumeration of
many things. Cap should be 1 (SINGULAR), not 8 (Hermes MANY).
Fix: count-question short-circuit in classify_question_quantifier()
that returns SINGULAR for `^\s*(?:and\s+|but\s+|so\s+)?how (?:many|much)\b`.
Anchored at start so buried `how many` (e.g. "list all the states;
how many are there?") doesn't suppress the rest of the question's
quantifier markers — the leading `list all` still wins.
9 new tests pin: count questions classify SINGULAR, leading
conjunctions don't break the short-circuit, buried `how many` does
NOT short-circuit (verifies anchor is leading-only).
Bonus — Finding 2 from the dry-run review: zero bounded universals
in bench fixture. Adds two:
name all members of the beatles
list all planets in the solar system
Both classify ALL · scope_bound_hint=bounded so the §10.1 bounded-
vs-unbounded distinction has live bench coverage. Without these,
--reject-broad correctness on bounded universals has no automated
test fixture.
915 tests passing (9 new); 36 skipped.
CLI flags on `aborist query`:
--no-quantifier-guard Level 2 disable: kills the guard for
one call. Telemetry → None.
--allow-broad Emergent-search: classifier on, caps
off. For exploratory enumeration.
--reject-broad Strict reject: ALL/COMPREHENSIVE/
OPEN_REQUEST + scope_bound_hint==
"unbounded" returns UNGROUNDED before
the LLM call (saves ~10-15s). Bounded
universals (Beatles, year-anchored)
are NOT rejected per §10.1.
--apply-quantifier-caps Flip Phase 2 dry-run gate per-call.
Path from dry-run to live cap.
Three new soft-demote violation kinds (§10.3) — no new audit_mode
token; tails on the existing audit-line:
BROAD_QUANTIFIER_RUNAWAY "broad runaway"
BROAD_QUANTIFIER_CAP_APPLIED "broad cap N" (cap value rendered)
BROAD_QUANTIFIER_SCOPE_UNBOUND "broad unbounded"
All three cap the ladder at ANCHOR-WARRANTED. Plus one HARD demote
(early-return UNGROUNDED):
BROAD_QUANTIFIER_REJECTED "broad rejected" (preflight rejection)
The reject-broad path early-returns from query() before the LLM
call when policy enables quantifier_reject_broad AND the question
is broad-unbounded. Result schema mirrors a normal UNGROUNDED row
(answer_text carries the rejection rationale + actionable narrowing
hints). _render_query_human gets a dedicated branch for the new
status so operators see the rejection without --json.
Live verification (post-commit):
$ aborist query --reject-broad "Winners of all major sports?"
UNGROUNDED · via BROAD_QUANTIFIER_REJECTED · ALL ("all") · cap was 8
0/0 0.0s (preflight)
BROAD-QUANTIFIER PREFLIGHT REJECTED · scope unbounded
Question matched ALL intensity ("all") with an under-specified
universe. Narrow ... or run with --allow-broad for exploratory
enumeration.
$ aborist query --reject-broad "name all members of the Beatles"
UNGROUNDED · via claim_lattice · title mismatch 4/4 20.9s
[Beatles enumerated, scope_bound_hint=bounded → not rejected]
`quantifier_reject_broad` folded into _VERIFIER_POLICY_FIELDS so
flipping reject default invalidates prior cache records.
16 new tests cover: soft-demote registration, hard-demote NOT in
soft-demote set, ladder rung mapping for each kind, tail rendering
(including cap value interpolation), tail combination with
existing kinds, end-to-end render through _render_query_human,
governance-hash binding. Two skipped placeholders mark the
integration paths exercised by live bench.
Lands aborist/qa/quantifier_reminder.py with broad_quantifier_
reminder(): one-line user-turn message restating the cap and the
[E\d+] citation rule for broad-intensity questions. Two templates:
bounded universe:
"This is a broad-quantifier query with a bounded universe.
Return at most N pointer-linked claim lines. Each claim must
cite an evidence id like [E5]; do not write claim lines
without bracket citations."
unbounded universe:
"This is a broad-quantifier query with an under-specified scope.
Return at most N pointer-linked claim lines. If you cannot
ground N claims with evidence IDs, return fewer grounded
claims. Do not enumerate from training prior. Each claim must
cite an evidence id like [E5]; do not write claim lines
without bracket citations."
The bounded template skips the "do not enumerate from training
prior" clause — the corpus has the answer set. Unknown scope falls
through to the stricter unbounded template (over-warn rather than
under-warn).
Wired into both query() and runner.ask() at the same insertion
point as the existing grounding_reminder — between
grounding_reminder and the evidence/question payload, where
Hermes-3-8B's most-recent-token attention catches it.
Default OFF (`quantifier_reminder_enabled: false`). Empirical
justification: ticket §3 Option B con notes Hermes already ignores
parts of the existing reminder under enumeration pressure. The
mechanism lands so an operator can A/B test cap-only vs cap+reminder
without code changes; default flips on after bench shows ≥5pp delta
on FORMAT_COLLAPSED or pointer-loss rate per §10.8.
`quantifier_reminder_enabled` folded into _VERIFIER_POLICY_FIELDS
so flipping the switch invalidates prior cache records.
19 new tests cover: gating (non-broad → None, missing cap → None,
None intensity → None), bounded-vs-unbounded template selection,
unknown scope falls back to unbounded, cap interpolation,
[E\d+] citation rule restatement, governance-hash invalidation.
Lands aborist/qa/model_profiles.py with two profiles:
- adamo1139/Hermes-3-Llama-3.1-8B-FP8-Dynamic
tight caps for broad intensities (ALL=8, COMPREHENSIVE=5,
OPEN_REQUEST=5) reflecting the 2026-05-02 runaway case.
- default
large-reasoner-class fallback (ALL=12, COMPREHENSIVE=15,
OPEN_REQUEST=12). Used when model_profile_id has no entry.
cap_for_intensity() resolves caps via three-source chain:
1. policy_overrides (per-call dict, highest priority)
2. per-model profile from PROFILES
3. "default" profile fallback
EXPLICIT_COUNT sentinel handles SMALL_NUM_EXPLICIT and
COMPARATIVE_BOUND — cap is the question's explicit count, not a
profile-set value. Defensive fallback to MANY cap if classifier
fired the rung without extracting a count.
Four new policy fields, all folded into governance_policy_hash via
_VERIFIER_POLICY_FIELDS:
- quantifier_guard_enabled master kill (default True)
- quantifier_guard_apply_caps dry-run gate (default False per
§10.11.3 — cap LOOKED UP and reported
on result, but NOT applied to the
verifier until operator flips True)
- quantifier_caps_by_intensity per-call override dict
- quantifier_guard_modes per-mode opt-in list (default
["claim_lattice_pointer",
"claim_lattice"]; quote opts out)
Six-level disable hierarchy (§10.11.2) implemented:
- Per-test: policy={"quantifier_guard_enabled": False}
- Per-call: --no-quantifier-guard (Phase 4)
- Per-phase: each policy switch is independent
- Per-mode: quantifier_guard_modes filter
- Per-model: model_profiles.py lookup
- Master: governance_policy_hash invalidation on flip
Wired through both query() and runner.ask() — both compute
effective_max_claims from the (classifier_intensity, model_profile,
policy_overrides) triple and pass it as max_claims_per_answer to
the verifier. Dry-run mode keeps effective_max_claims at the policy
default (12) until apply_caps flips True.
Result dict surfaces claim_cap_applied (the LOOKED-UP cap, even in
dry-run) plus all Phase-1 quantifier fields on miss-path AND
cache-hit path so bench rows stay column-aligned.
19 new tests pin: per-model selection, EXPLICIT_COUNT sentinel,
override precedence, governance-hash invalidation on every cap
field, profile shape (all ten rungs covered), default profile
presence.
Lands aborist/qa/quantifier.py with classify_question_quantifier(),
a pure function mapping a question string onto the ten-rung
intensity ladder (ticket #000008 §2):
ABSENT < SINGULAR < PROPORTIONAL < SMALL_NUM_EXPLICIT
< COMPARATIVE_BOUND < FEW < MANY < ABSENT < ALL
< OPEN_REQUEST < COMPREHENSIVE
Returns intensity, matched_token, explicit_count, is_broad,
operational_shape, scope_bound_hint, classifier_version. Pure: no
I/O, no model call, no retrieval call.
Highest-intensity-wins arbitration: COMPREHENSIVE strictly stronger
than OPEN_REQUEST (both > ALL). Catches "tell me everything about
all wars" → COMPREHENSIVE rather than dropping to one of the softer
shape detectors.
Scope_bound_hint heuristic (§10.1): bounded vs unbounded universals.
"All members of the Beatles" → bounded (corpus-known finite set).
"Winners of all major sports" → unbounded (scope undefined). Year-
anchored questions ("…in 2024") bound the universe to one event.
Heuristic only — corpus-arity check left for future refinement.
Wired into query() right after policy resolution. Both miss and
cache-hit paths surface quantifier_intensity, quantifier_matched
_token, scope_bound_hint, quantifier_explicit_count on the result
dict. claim_cap_applied is None until Phase 2 lands the cap-
application gate (default-off per §10.11.3 dry-run discipline).
61 new tests cover every rung, scope-bound detection (bounded /
unbounded / unknown), highest-wins arbitration, and regression
fixtures (factoid/wh-questions don't over-classify as broad).
Adds the §10.6 + §9.6 Phase-0.x bench-row fields. Pure additive —
no row-schema renames, no policy effects yet. Phase 1 classifier
will fill the quantifier_* slots; Phase 2 cap-table will fill
claim_cap_applied. Keeping the keys present here makes the JSONL
schema stable across the rollout so post-Phase-1 markdown can
re-render against pre-Phase-1 rows without column-misalignment.
New per-row fields:
- answer_pointer_count distinct E\d+ ids in raw_answer
- answer_chars_with_brackets chars inside [E\d+,...] regions
- raw_meaningful_line_count >20-char lines in raw_answer
(matches verifier FORMAT_COLLAPSED
denominator)
- quantifier_intensity slot for Phase 1 classifier
- quantifier_matched_token slot for Phase 1 classifier
- scope_bound_hint slot for Phase 1 classifier
- claim_cap_applied slot for Phase 2 cap-table
- model_profile_id configured model id verbatim
New helper _bracket_diagnostics() bundles the bracket/pointer/line
extraction in one place; module-level regexes (_BRACKET_RE,
_BRACKET_REGION_RE, _POINTER_ID_RE) avoid per-row recompilation.
5 new tests cover the helper: empty input, single pointer, multi-
pointer-in-one-bracket, separate brackets with shared id, format-
collapsed shape (5+ meaningful lines, 0 brackets — the
2026-05-02 winners-of-all-major-sports case).
Closes the bench-side gap surfaced in §5.2: JSONL was carrying summary
numbers only, blinding the harness to FORMAT_COLLAPSED rate and per-
violation-kind distributions. Without these, A/B/D bench measurements
on the broad-quantifier preflight guard would be guesses.
- query() result dict surfaces format_collapsed + raw_answer (lattice
modes only) so the bench can read them directly instead of re-deriving
from cache rows that --burn overwrites.
- Each bench row gains format_collapsed, violation_kinds (sorted unique
list — full payloads stay off the row to keep size bounded), and
answer_brackets (count of [E\d+] in raw_answer for lattice modes).
- _summarize aggregates per-mode FC count (only explicit True; None
means check didn't apply), per-kind tallies (each kind once per row),
and lattice-only bracket sum/n.
- Markdown renderer adds a `## format-collapse + violation kinds`
section with per-mode FC rate, mean raw brackets, and one column per
observed violation kind. Degrades gracefully when the sweep produces
no violations.
- 5 new bench-harness tests pin the aggregation rules.
Re-baseline (2026-05-02T20-58-57Z) sharpens §5.1 analysis dramatically:
NO_EVIDENCE_POINTER fires 3/3 in pointer mode and is the dominant gate,
not TITLE_MISMATCH (1/3) as §5.1 inferred from JSONL alone. FORMAT_
COLLAPSED actually fires 1/3 — not the rare corner the first baseline
called it. Implies Option B (prompt reminder) is the load-bearing fix
for the verdict; Option A (cap reduction) only moves secondary kinds.
§5.3 sub-investigation closed on first read — SCHEMA_INVALID:1 in
pointer mode is a legitimate kind emitted by verify_claim_lattice for
empty-claim-text (verify.py:1242) and bare-name-claim (verify.py:1270),
not a JSON-mode leak.
Sister rule to Rule 9 (SUBJECT_TOKENS_ABSENT) landed in the same
session. Both demote STRICT → HYBRID but on orthogonal signals:
Rule 9 catches premise-parroting; FORMAT_COLLAPSED catches
protocol abandonment.
Surfaced by fox's "winners of all major sports?" 2026-05-02 case:
Hermes-3-8B melted under an under-specified broad-quantifier
question, dumped 50+ free-form prose claims with zero [E\d+]
pointer tags. Verifier honestly returned UNGROUNDED 0/2 (parser
caught two line fragments), but operators couldn't distinguish
"tried & failed to ground" from "abandoned the protocol." This
soft-demote separates the two failure shapes at audit-line glance.
verify_claim_lattice (pointer-mode only — JSON collapse already
shows as SCHEMA_INVALID):
- count meaningful_lines (>20 chars after strip) and [E\d+ regex
matches in raw answer
- ≥5 meaningful lines AND 0 bracket tags → FORMAT_COLLAPSED
violation, soft-demote STRICT → HYBRID
- format_collapsed: bool added to verdict dict
Plumbing:
- claim_lattice_format_collapse_check_enabled: True in DEFAULT_POLICY
and DEFAULT_QUERY_POLICY
- _VERIFIER_POLICY_FIELDS in keys.py adds the field so it folds
into verifier_policy_hash
- threaded through ask() and query() call sites
CLI:
- _SOFT_DEMOTE_VIOLATION_KINDS includes FORMAT_COLLAPSED so the
audit-line ladder rendering treats it as a soft demote
- _render_warrant_tail appends "· format collapsed" tail
Bench fixture: new "under-specified 'all'" section in
qa_questions.txt with `winners of all major sports?` and rationale
about cross-model resilience signal.
Tests:
- test_format_collapsed_fires_on_bracketless_multi_line_prose
- test_format_collapsed_does_not_fire_when_pointer_tags_present
- CLI render coverage
Full suite: 781 passed (up from 776).
Open Ticket #000008 — Broad-quantifier preflight guard. Cleaner
upstream fix: detect quantifier-intensity at query layer and
apply a per-model claim ceiling BEFORE the 13-second LLM call.
FORMAT_COLLAPSED stays as the downstream catch; #000008 proposes
the upstream prevention. TICKETS.md index + Next ID 000008→000009.
Closes the first confirmed EVIDENCE-WARRANTED false-positive
surfaced by the 200-cycle bench-emergent run on
`steer/reply/correcter` (Ticket #000006 amend 2026-05-02b). The
model parroted three question-distinctive tokens (correcter,
steer, reply) into its claim while citing a glossary article whose
33.5K-char content contains ZERO occurrences of any of them.
Generic linguistic vocabulary (language, communication, terms,
relationships) carried Rule 5's citation-coverage check on its
own; the actual subject tokens rode along unverified.
New per-claim check `_parroted_subject_tokens_absent`: for each
resolving claim, compute the question∩claim content-token set,
then check substring presence in the union of cited evidence
spans (lower-cased, mirroring Rule 5). When ≥ threshold parroted
tokens are absent, emit `SUBJECT_TOKENS_ABSENT` and demote STRICT
→ HYBRID. Default threshold = 3 — single-token absence is often
stem-variant noise; three+ is the parrot fingerprint.
Plumbing:
- New default `DEFAULT_SUBJECT_TOKENS_ABSENT_THRESHOLD = 3`
- Both `verify_claim_lattice` and `verify_claim_lattice_json`
gain `subject_tokens_absent_threshold` kwarg + per-claim check
block (mirrors TITLE_MISMATCH plumbing, sits right after it
in the rule order)
- `claim_lattice_subject_tokens_absent_threshold` policy field
added to `DEFAULT_QUERY_POLICY` and `DEFAULT_POLICY`; folds
into `governance_policy_hash` and (via _VERIFIER_POLICY_FIELDS)
`verifier_policy_hash`
- All four runner/query call sites pass the policy-derived value
Live verification (cache-split cleanly via policy-hash bump):
pre-fix cache_key 08dbd2c1… : STRICT (false positive)
post-fix cache_key 6a519636… : UNGROUNDED
Three new unit tests in `tests/test_verify_json.py`:
- threshold-meeting parrot demotes STRICT → HYBRID
- no-op when question is None
- below-threshold absence stays STRICT
Full suite: 776 passed, 34 skipped.
aborist now writes one JSONL session per `make query` invocation
and per `bench-emergent` cycle to:
~/.aborist/unfirehose/{project-slug}/{session-uuid}.jsonl
Unfirehose's native-harness auto-discovery picks up any
~/.{name}/unfirehose/ directory (see ingest.ts:discoverNativeHarnesses)
without registration — once a session lands, the unfirehose watcher
debounces, ingests, and exposes it in the dashboard alongside
Claude Code / Fetch / uncloseai sessions.
Schema: unfirehose/1.0 (per ~/git/unfirehose-nextjs-logger/docs/
unfirehose-schema.md). Each session file:
line 1 type=session (header — id, projectId, firstPrompt,
harness="aborist", harnessVersion)
line 2 type=message role=user
line 3 type=message role=assistant
content=[text]
model=hermes-3-llama-3.1-8b-fp8-dynamic
provider=hermes
durationMs=<wall>
aborist_meta={audit_mode, n_verified/n_quotes,
cache_key, cache_status, lookup_path,
violations, sources, timings_ms, answer_mode}
line 4 type=message role=system subtype=session_end durationMs
aborist-specific extras (verifier verdict, sources, timings) ride
under namespaced ``aborist_meta`` so the canonical fields stay clean
for off-the-shelf consumers; per the spec, unknown fields are
ignored downstream.
Bench-emergent cycles emit an additional system init message at
the start of each session noting the 3 random words, marking the
session as a generator-driven cycle vs a normal user query.
Failure-isolation: journal write is wrapped in a broad try/except
at every call site. A journaling bug must NEVER break the query
or bench loop.
Tests: 10 new in tests/test_journal.py (slug encoding, session
header, parent-id chain, session_end on close, aborist_meta
passthrough, usage block, idempotent close). Full suite: 663 passed.
Live verified: `make query Q="what is photosynthesis?"` produced
a 4-line JSONL with STRICT 3/3, all sources + timings populated,
ready for unfirehose ingestion.
Three changes that shape the same lever:
(1) The metaphor-cue wordlist now unions /usr/share/dict/words +
/usr/share/dict/american-english + /usr/share/dict/british-english.
The Debian split made the prior 'just symlink to american-english'
miss British spellings (colour, organisation, realise) which
silently became false negatives on British-speaker questions.
Union: 102,485 → 104,305 entries on this machine. ~1,820 added
British-specific entries.
(2) Supplemental dictionary support: operators can layer
domain-specific vocabulary into the morphological substrate.
Two paths:
- Env var: ABORIST_METAPHOR_DICTS=/path/a:/path/b
- Programmatic: register_metaphor_dictionary(path)
Each supplemental dict is one word per line. The cue suffix
tests (-ly stem, -ing stem, -est stem) then resolve domain
stems automatically — adding 'aerodynamic' to a custom dict
makes 'aerodynamically' classify as adverbial without code
changes.
Use case: 'a tree with its own vocabulary' — an aviation
forest, a medical corpus, a legal-domain shard each carries
jargon the standard wordlist doesn't cover. Register once,
suffix tests pick up domain stems forever.
(3) README gains a 'Sidecar diagnostics' section with a table of
the three sidecars (deflection, title-relevance, metaphor-
deflection) plus a 'Metaphor-deflection cue dictionary' subsection
explaining the derivation rule, the load order, and the per-
forest vocabulary configurability. Architecturally documents
why the rule is *derived* from the union (Phase-2 lesson) and
not hand-curated.
3 new tests in tests/test_inspect.py:
- register_metaphor_dictionary unions a custom path's words
- ABORIST_METAPHOR_DICTS env var supplements with two paths
- re-registering same path is idempotent
763/34 tests pass.
Closes the FTS5 hyphen-tokenization asymmetry: `bi-polar is rare?`
retrieved only the Bi-Polar album/disambiguation cluster while the
medical-condition cluster (Bipolar disorder, Bipolar I/II disorder,
etc.) sat in the same shards untouched. `unicode61` splits hyphens
at index AND query time; `Bi-Polar Blues` indexes as [bi, polar, ...]
while `Bipolar disorder` indexes as [bipolar] — non-overlapping
token sets that never met.
Fix is query-layer only — no canonicalization_version bump, no
re-index, existing cache_keys stay valid:
- _hyphen_fold_variants(s): emit joined-no-hyphen variants for
every hyphenated run.
- _title_query_tokens(s): additively merges variants symmetrically
(queries AND titles when called on either).
- _filter_by_title_relevance: accept-path 5 — title stem-overlap
with hyphen-fold anchors passes the breadth gate. Rescues
`Bipolar disorder` (1-of-N qtoken match) without disrupting
non-hyphen queries (anchors empty → zero side effect).
- DEFAULT_QUERY_POLICY / DEFAULT_POLICY: hyphen_fold_v1: True
marker folds into governance_policy_hash; new records
cache-split cleanly from pre-fold records.
Live verification on /home/fox/.aborist/shards: same query now
retrieves `Bipolar disorder` (#5) and `Bipolar` disambiguation
(#7); model cites both, answer reads "Bi-polar disorder is not
rare; it affects approximately 2.8% of the U.S. population".
EVIDENCE-WARRANTED 2/2, properly grounded.
Tests: 4 new (3 unit, 1 integration with regression-pinned
Bipolar-disorder retrieval). Full suite 760 passed, 34 skipped.
Also: CLAUDE.md gains a close-when-complete hint for tickets — an
open ticket whose code already shipped is a stale map.
Empirically motivated by the 2026-05-02 emergent log:
Q: 'How can a swallowtail butterfly, gracefully fluttering amidst
the rockiest terrain, remain undeterred by the upbraiding
winds...'
A: 'The Macleay's Swallowtail butterfly is found in Eastern
Australia including the ACT, New South Wales, Queensland...'
The model traded the metaphor for literal Macleay's-Swallowtail
taxonomic facts. Warrant passed (the literal anchor IS in cited
spans), DEFLECTION_DETECTED didn't fire (the last content token
'flight' did echo somewhere), the bench landed HYBRID 3/3 — but
the user's metaphorical question was never engaged.
Honest gap: catching this structurally requires NLI-grade
semantics, which is the verifier-semantic-gap design proposal.
Until that lands, ship a SMELL SIDECAR — purely lexical, sidecar
only, never enters the binary verifier output.
Detection rule:
1. Extract metaphor cues from the question:
- -ly adverbs (gracefully, defiantly), excluding common
-ly nouns (butterfly, italy, july) via blocklist
- -ing present participles >=6 chars (upbraiding,
fluttering, brooding), excluding common verb -ing forms
- -est superlatives >=6 chars (rockiest, harshest)
- prepositional cues (amidst, despite, against, beneath)
2. Count overlap with answer's content tokens.
3. Fire metaphor_deflection when:
cue_count >= 3 AND answer_overlap_count == 0
The threshold is conservative; the smell only triggers on
STRONGLY poetic questions with PURELY literal answers.
Wire-up:
- aborist/qa/inspect.py:diagnose_metaphor_deflection
- bench/qa_sweep.py: rows gain metaphor_deflection_kind +
metaphor_cue_count + metaphor_overlap_count
- scripts/bench_emergent.py: same fields on emergent log rows
5 new tests in tests/test_inspect.py:
- swallowtail canary case fires metaphor_deflection
- literal questions (mona lisa) return no_signal
- questions whose answer engages cues return no_signal
- common -ly nouns (butterfly, italy, july, family) filtered
- sub-threshold cue counts return no_signal
756/34 tests pass (5 new + 751 prior).
Emergent stress-test log surfaced two failure shapes the curated
bench can't reach. Reviewer (claude-opus-4-7 + fox) appended
teacher: blocks to four log entries; two of them named real
defects in the demote chain. This commit ships those fixes plus
the teacher-block annotations.
Cases reviewed (2026-05-02 emergent_log.jsonl):
✅ Menkar/sterilizers/trifle — working as designed
🟡 swallowtail/upbraided/rockiest — metaphorical deflection
🔴 cashback/widescreens/within — warrant gap on inferential claims
🔴 comeliness/fetish/investitures — topic shift earned ANCHOR-WARRANTED unfairly
Two code changes:
1) verify_claim_lattice + verify_claim_lattice_json: when EVERY
resolving claim has TITLE_MISMATCH, demote audit_mode →
UNGROUNDED. Previously HYBRID. Catches the cashback case
('widescreens offer cashback' cited to a generic Coupon
article — n_verified=1 overclaimed when the citation was
meaningless).
2) cli._ladder_rung_for_lattice: DEFLECTION_DETECTED moves from
soft-demote (cap at ANCHOR-WARRANTED) to hard-demote (cap at
POINTER-LINKED) alongside WARRANT_MISSING and TITLE_MISMATCH.
Catches the comeliness case (model fully shifted topic to
'Rock & Chips'; pre-fix the verified Rock & Chips claims
landed at ANCHOR-WARRANTED unfairly).
Test updates:
- tests/test_verify_json.py:test_verify_json_title_mismatch_demotes_to_ungrounded
(renamed; expected outcome flipped HYBRID → UNGROUNDED)
- 4 fixtures in tests/test_claim_lattice.py and 1 in
tests/test_verify_json.py: claim text augmented with 'in the
film' so the Jurassic-Park-titled fixture's title shares a
stem with the claim. These tests were testing other paths
(NO_EVIDENCE_POINTER, EVIDENCE_LINKED_PARTIAL, UNKNOWN_EVIDENCE_ID)
and the title-mismatch was incidental to the fixture choice.
Teacher blocks on the four log entries record the verdict +
failure_class + recommendation + notes, with reviewer + date.
The two ✅/🟡 entries have no recommended code change; the two 🔴
entries reference this commit as the fix.
751/34 tests pass.
Two compounding things in one commit because they're tightly coupled
(the new violation is what makes the new fixtures meaningful):
(1) DEFLECTION_DETECTED — new soft-demote violation kind.
`aborist.qa.inspect.diagnose_deflection` was a read-only sidecar:
when the question's subject anchor (last content token after
stopword strip) is missing from the answer, it returned
`kind="deflection"`. Useful telemetry but never affected the
verdict. 2026-05-02 fox surfaced two cases where the missing
signal mattered:
Q: "who burns the amazon river?"
A: "Deforestation in the Amazon Rainforest is primarily caused
by human activities..." [E10 | Deforestation of the Amazon
Rainforest]
Pre: EVIDENCE-WARRANTED 1/1 ← silent river→rainforest topic shift
Post: ANCHOR-WARRANTED-PARTIAL 1/2 with DEFLECTION_DETECTED
The verifier now runs diagnose_deflection() after all hard checks.
On `kind == "deflection"` it appends a DEFLECTION_DETECTED
violation (rationale + subject_anchor + overlap_ratio) and caps
audit_mode at HYBRID. Renderer's four-rung ladder picks it up via
`_SOFT_DEMOTE_VIOLATION_KINDS` (cli.py) and demotes EVIDENCE-
WARRANTED → ANCHOR-WARRANTED automatically.
Folds into verifier_policy_hash via new
`claim_lattice_deflection_check_enabled: True` policy field
(defaults on). Bumps the 9-dim cache_key when toggled.
Wired into both verify_claim_lattice (pointer) and
verify_claim_lattice_json (JSON). Deferred import keeps verify.py
module-load clean.
(2) Three live fixtures gating the river/rainforest/deflection family:
- test_amazon_river_burning_who_deflects_or_grounds_river
Gates the silent topic-shift pattern: if model deflects, the
verifier MUST catch it (DEFLECTION_DETECTED present OR
UNGROUNDED OR "river" actually in answer). Failure mode this
catches: EVIDENCE-WARRANTED with rainforest answer to a river
question and no soft-demote.
- test_amazon_river_burning_culture_refused_or_ungrounded
Adversarial-impossible mirror of Mars-BDFL: rivers don't burn,
so model must refuse / deflect / refute. Failure mode:
STRICT/HYBRID with affirmative culture-burns-river claim.
- test_amazon_rainforest_burning_culture_grounds_or_deflection_caught
Feasible-but-framing-specific: corpus has deforestation
content but no "culture" framing. Either grounds with rainforest
content OR a soft-demote/UNGROUNDED catches the framing gap.
Live verified (2026-05-02): all 3 pass against the real Hermes
endpoint. 641 unit tests still pass (deflection check skipped on
fixtures lacking question or rendered_text).
Captures the canonical "model knows it but corpus doesn't" case fox
surfaced 2026-05-02:
Q: what is boss baby?
Expected: UNGROUNDED (the 2010-11 wiki snapshot has no Boss Baby
coverage — the 2017 DreamWorks film didn't exist; the 2010 Marla
Frazee picture book had just been published & no article)
Model: emits training-prior content about the film/book
Verifier: 0/N verified — no evidence chunk anchors the claims
This is the failure-by-honest-admission case the verifier must
preserve. Two compounding false-positive risks the test guards:
1. Verifier accepting the claim against an unrelated chunk that
happens to share content tokens (Death of Baby P, Cake Boss,
Beanie Baby — all adjacent-token noise observed at top-K).
This is the warrant-failure class warrant-lite was built to
catch — if it ever passes here, anchor-class warrant has a hole.
2. Verifier accepting via OR-mode FTS5 noise — a token-level match
of "baby" or "boss" in unrelated content surfacing as positive
grounding.
Acceptable behaviors:
A. UNGROUNDED (verifier returns 0/N — corpus-truth over prior)
B. STRICT/HYBRID without "boss baby" anywhere in the answer
(deflection — model declined the false-corpus question and
answered an adjacent grounded fact, like Mars-BDFL → Guido
pattern).
Failure: STRICT/HYBRID + "boss baby" in answer = false-positive
grounding. Test fails by name pointing at the warrant gap.
Live verified (2026-05-02): UNGROUNDED 0/2, model emitted both the
2017-film claim AND the 2010-book claim, verifier rejected both
honestly. Test passes in 10s.
Regression fox surfaced 2026-05-02:
Q: "what technology are currently or soon available which may
enable one person to reconstruct and understand some or a
portion of another persons thoughts or ideas without
speaking or sign language."
→ sqlite3.OperationalError: Expression tree is too large
(maximum depth 1000)
Root cause: the v1 of _search_titles (commit 0052845) chained N
``CASE WHEN ... THEN 1 ELSE 0 END + ...`` expressions for the
title_score column. Each CASE WHEN is multiple tree nodes; +-
chained N times exceeded SQLite's default 1000-depth bound on
question texts with ~30+ content tokens.
Fix: simplified SQL — OR-chain WHERE + ORDER BY LENGTH(title) ASC
+ LIMIT bumped 4x to compensate for the lost smart sorting. The
caller's post-filter (word-boundary stem-aware token-set
intersect) does the actual title-relevance ranking; SQL just
needs to surface enough candidates for the post-filter to grade.
Also: cap the OR-chain at MAX_TITLE_LIKE_TOKENS=24 so pathological
200-token queries don't cascade SQL expression growth even
defensively. Beyond ~24 tokens the post-filter is doing all the
work; extra LIKEs just inflate candidate sets without signal.
5 new tests in tests/test_query.py covering the regression at
unit / integration / functional layers:
- test_unit_search_titles_handles_long_question_without_crash
50-token query through _search_titles directly. Pre-fix raised
sqlite3.OperationalError; post-fix returns row list.
- test_unit_search_titles_handles_zero_tokens
Defensive: empty token list → empty result, no SQL executed.
- test_unit_search_titles_caps_or_chain_at_max_tokens
200-token pathological query — bounded by MAX_TITLE_LIKE_TOKENS,
doesn't crash.
- test_integration_query_completes_on_long_question
End-to-end query() with StubClient + long question completes
without the SQLite error. Pre-fix raised before reaching the
LLM call.
- test_functional_long_question_returns_sources
The neurotech doc (richest body match) appears in top-K despite
the long-question retrieval path.
Test_query.py: 35 → 40 passing. Full suite (excluding parallel
test_concepts churn from concepts/query.py rewrite): no other
regressions.
Two paired changes addressing fox's "learn this hyperparameter
from model use, not hard coding" + the 1M-context-window
caveat:
(1) Log-scale prompt-size buckets extend from 8KB through 1M+:
<8KB / 8-16KB / 16-32KB / 32-64KB / 64-128KB / 128-256KB /
256-512KB / 512K-1M / >=1M
The same bench harness now covers 8B-class models (Hermes 82K
context, max useful prompt ~32-64KB) through 1M-context models
(Gemini 1.5 Pro, Claude with extended context, Llama 4) without
code change. A model whose context window stops at 82K simply
never populates the giant buckets; a 1M-context model fills
them and finds its own sweet spot.
(2) New "recommended context budget (learned from this bench)"
section — per-mode peak-strict-rate bucket. Operator-driven
landing per the five-step algorithm step 5: surfaced, not
auto-applied. Minimum sample size of 5 runs per bucket so
statistical noise doesn't masquerade as signal. Tie-break on
smaller-bucket-wins so equivalent strict-rates favor the
cheaper choice.
The substrate is now self-tuning at the OBSERVATION layer: bench
records what budget actually grades best per model. Per-model
profile JSON (storing the recommended budget back into
~/.aborist/model_profiles/<model>.json) is the next beat once
this surface is observable in real bench runs.
3 new bench tests cover the recommended-budget section, the
sample-size floor, and the giant-context bucket coverage.
Full suite: 746 passed (was 738, +8).
Connects to D8 (automate after test-pinning): the bench tells us;
we don't guess.
Phase 2 of the concepts/ layer. The Apr 27 commit (c6182ae) shipped
hand-curated frozensets in aborist/qa/concepts.py with a TODO to
"derive from Wikipedia's category graph or 'See also' sections" —
that's this commit. Fox's 2026-05-01 critique landed it: a 7-entry
list of arbitrary frozensets won't scale to a 3.47M-doc corpus, &
adding domains shouldn't require a Python edit + commit + redeploy.
Architecture:
(1) Per-shard concept_relations SQLite table. Append-only, with
UNIQUE (source_root, relation_kind, token, target, evidence_kind)
so re-derivation is idempotent. Lives next to documents in each
shard so mesh sync moves relations alongside the docs that
derived them. A SECONDARY index — writes here NEVER affect
document_root / chunk_root / cache_key, so backfilling is safe
across the entire corpus.
(2) aborist/concepts/ package:
- store.py: add_concept_relation, concept_relations_for_token,
purge_by_evidence_kind, list_evidence_kinds
- query.py: cross-shard synonym_expand, rivalry_excluded;
union-find collapse on synonym edges so partial
pairs build full equivalence classes; mtime-keyed
per-process LRU so retrieval doesn't re-walk
shards on hot loops
- seed.py: one-shot migration of legacy frozensets (8 groups
incl. brain-tech) to evidence_kind='manual_legacy'
rows under source_root='__legacy__concepts__'
- extract.py: pluggable extractor registry. Built-in:
link_reciprocity_synonym — for any reciprocal
edge pair (A→B AND B→A) in the existing edges
table, emit synonym edges between the docs'
title-tokens. Works for Wikipedia (See-also
bidirectional), HTML site internal-link clusters
(russell.ballestrini.net pattern), or any link
graph the corpus already encodes — no new
crawler needed; the html_page parser already
populates `edges` rows on ingest.
(3) aborist/qa/concepts.py rewritten as a backwards-compat shim —
same public API (synonym_expand, rivalry_excluded,
has_compare_phrasing) so query.py call sites unchanged.
shards_dir threaded through _filter_by_title_relevance &
_search_corpus' synonym_expand calls. Without shards_dir
(legacy 2-arg call shape), helpers degenerate to no-op —
matches the behavior the frozenset code had when no group hit.
(4) Cross-shard UNION view: concept_relations added to
_SHARDABLE_TABLES in store.py so connect_query() exposes a
unified view across all shards (same pattern as documents,
chunks, providence_cache, etc.).
Live-verified on the 4-shard 3.47M-doc corpus + the
crawl_russell_ballestrini_net.db shard:
Q: what technology are currently or soon available which may
enable one person to reconstruct and understand some or a
portion of another persons thoughts or ideas without speaking
or sign language?
Result: same as the bde1bd6 in-memory frozenset version —
Telepathy E4 cited alongside Videoconferencing E1/E2,
POINTER-LINKED-PARTIAL 6/10. The DB-backed lookup reproduces
the frozenset behavior byte-for-byte.
Tests: 633 passed (was 624). 9 new concept tests covering
DB-backed synonym/rivalry lookup, shards_dir=None degenerate
behavior, brain-tech group seed, cache invalidation. Old tests
that called helpers directly without shards_dir kept as no-op
assertions (synonym_expand({"athlon"}) without shards_dir returns
{"athlon"} unchanged).
Backfill mechanics: existing live shards needed a one-shot
`connect()` to auto-create the new concept_relations table
(SCHEMA_SQL has CREATE TABLE IF NOT EXISTS). Re-derivation never
mutates the Merkle tree — concept_relations is fully orthogonal
to document_root / chunk_root. Cache_key dimensions are
unaffected.
Deferred (follow-on):
- CLI commands: aborist concepts {seed,list,add,derive,purge}
(currently fox runs the helpers via python -c)
- Wikipedia See-also extractor (requires parsing wikitext sections
beyond what's already in edges)
- Wikipedia category extractor (requires reading Category: links
from chunked wikitext)
