Native, Obsidian-graph-view-like network of the precedent corpus, rendered
in web-ui from a read-only projection of the live DB. Replaces the idea of
exporting to an external Obsidian vault (which would be a parallel, drifting
copy of the corpus — the exact root cause G2 forbids).
The graph edges already existed in the data model; this only surfaces them:
nodes = precedents (case_law) + synthesized topic/practice-area hubs;
edges = cites (precedent_internal_citations) + same_chain (case_law_relations)
+ tagged/in_area (subject_tags / practice_area membership). Node size =
incoming-citation count (index-backed GROUP BY on idx_pic_target). Click a
node → local-graph neighborhood focus; panel deep-links to /precedents/[id].
Backend (read-only, SELECT only — G2):
- web/graph_api.py — Pydantic models (CorpusGraph/GraphNode/GraphEdge, so
OpenAPI emits real types — UI2) + SQL assembly over the shared db.get_pool().
- web/app.py — GET /api/graph/corpus, GET /api/graph/node/{id}/neighborhood,
both with explicit response_model. practice_area validated against the
closed enum (G5); both endpoints write nothing.
Frontend:
- react-force-graph-2d (canvas/d3-force), loaded via next/dynamic ssr:false.
- /graph page + nav entry; graph.ts TanStack hooks; filter panel (practice_area
/ source / min-citations / search / node-type toggles), node detail panel,
hover+selection neighborhood highlight. Explicit error handling (UI4).
Not a retrieval path (03-retrieval): returns graph topology, never ranked
search results. Halacha nodes + corroboration/equivalence edges are Phase 2,
already gated behind the node_types param (no contract change needed).
SQL validated read-only against the live DB (142 precedents, 85 resolved
citations, JSONB tag expansion, ANY(uuid[]) edge + BFS queries). web-ui lint
+ build pass; /graph in the route table.
Invariants: keeps G2 (single source of truth — live projection, no parallel
store), G5 (corpus separation filtered server-side), UI2 (response models),
UI4 (no swallowed UI errors).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The extractor classified rule_type by SOURCE bindingness (higher-court→binding,
committee→persuasive) instead of by rule KIND. The gold-set proved it: 'binding'
appeared on 19/19 external rulings & 0 committees; 'persuasive' on 13/13
committees & 0 external — only 58% agreement with the human role tags. The two
axes (authority vs rule role) were crammed into one enum.
This splits them per INV-DM7:
- authority (binding/persuasive) — DERIVED from case_law.precedent_level
(עליון/מנהלי→binding, ועדת_ערר_מחוזית→persuasive), never stored, never
LLM-guessed. New helper halacha_quality.derive_authority; surfaced read-only
in list_halachot / goldset_list / search results.
- rule_type — now the rule ROLE only: holding/interpretive/procedural/
application/obiter. Both extractor prompts unified to this vocabulary;
_coerce_halacha no longer defaults rule_type from the source; legacy
binding→holding / persuasive→interpretive fold for safety.
UI: authority shown as a separate read-only badge (gold=מחייב / muted=משכנע)
across the review queue, precedent detail, and gold-set; the gold-set role
selector drops binding/persuasive and adds מהותי (holding).
Migration: scripts/halacha_rule_role_backfill.py re-classifies the 276 pre-split
binding/persuasive rows into a genuine role via local claude_session (run after
deploy). Gold-set correct_type/ai_correct_type 'binding'→'holding' via SQL.
Sources (≥3, per research-decision policy): OASIS LegalRuleML v1.0
(appliesAuthority/Strength as metadata orthogonal to rule logic) · SemEval-2023
Task 6 LegalEval (rhetorical roles by function, authority kept separate) ·
Bluebook signals (weight-of-authority is a separate dimension).
Invariants: ESTABLISHES INV-DM7. Upholds G1 (normalize at source — extractor
classifies role, system derives authority) and G2 (single source of truth —
authority derived, not a parallel stored field). Tests: 211 pass + new
derive_authority/coerce coverage. web-ui build + tsc clean.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The old independent toggles had a trap: clicking "אי-הסכמות AI" set a filter,
and once all disagreements were resolved the toggle button disappeared
(rendered only when count>0) while the filter stayed ON — so the list showed
zero items and the untagged ones were unreachable.
Replaced hideTagged + disagreeOnly with one mutually-exclusive segmented
control: הכל / לא תויגו / תויגו / ⚠ אי-הסכמות, each with a live count and always
visible. No stuck state; "לא תויגו" makes the remaining work obvious.
Verified: tsc --noEmit 0.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The chair wanted an independent recommendation beside each tag, to reconsider
his own judgments. Adds a NON-ground-truth AI second-opinion:
- schema: halacha_goldset.ai_is_holding / ai_correct_type / ai_rationale /
ai_generated_at (additive).
- db.goldset_set_ai_recommendation + goldset_list now returns the ai_* fields.
- scripts/goldset_ai_recommend.py — local claude_session judges is_holding +
type + a one-line rationale per item, INDEPENDENTLY (own legal rubric).
Independent of the rule-based validators #81.8 measures → no circularity.
Never auto-applied; QA aid only.
- web-ui: each card shows "🤖 המלצת AI: הלכה/לא · type" + rationale and an
agreement/disagreement chip vs the human tag (amber on disagree); a
"⚠ אי-הסכמות AI (N)" filter to review only the conflicts.
Methodology note kept explicit: the human stays the ground truth; the AI is a
prompt to reconsider, not to copy.
Verified: tsc --noEmit 0; generator stores recs and flags disagreements with
existing human tags.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The validator score panel was collapsed by default, so taggers thought nothing
was happening. Now open by default, with a caption explaining the metrics
measure "not-a-holding" detection and become meaningful as more "לא הלכה" items
are tagged (showing the current negative count while it's small).
Verified: tsc --noEmit 0.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Tagging is easier one source-type at a time. goldset_list now returns
case_law.source_type; the page adds:
- a filter (הכל / פסקי דין / ועדת ערר) with live counts,
- a group-sort so even in "הכל" all court rulings come first, then all
committee decisions,
- a per-card source badge (פסק-דין / ועדת ערר).
Verified: tsc --noEmit 0; source_type splits the live batch 58 court / 92 committee.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
TYPE_HELP popover now follows the same order as the type buttons:
מחייבת · פרשני · יישום · אמרת-אגב · פרוצדורלי · משכנע.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
"לא הלכה" + "מחייבת" (or any holding-type) is a logical contradiction — binding
means it IS the holding. Likewise "הלכה" + application/obiter. The three controls
are independent, so the combo was clickable with no signal.
Adds a non-blocking amber warning under the type buttons when is_holding and
correct_type contradict (holding ↔ binding/interpretive/procedural/persuasive;
not-holding ↔ application/obiter). Soft by design — flags the inconsistency for
the tagger to fix without forcing, leaving room for genuine edge cases.
Verified: tsc --noEmit exits 0.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Two UX fixes on the gold-set tagging page:
1. isTagged now requires is_holding AND correct_type AND quote_complete — not
just is_holding. Previously, in "hide tagged" mode the card vanished the
instant is_holding was clicked, so the type and quote-complete answers could
never be set. The progress counter / "תויג" badge now reflect full tagging.
2. An info (ℹ) icon next to "הסוג הנכון" opens a popover explaining the six
rule types (definition + the deciding test + an example each), so the tagger
has the criteria in front of them while tagging.
Verified: tsc --noEmit exits 0.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Replaces the CSV-edit workflow with an in-app tagging page so the chair/Dafna
can label the extraction-quality gold-set by clicking, and see validator
precision/recall live.
Schema (V29): halacha_goldset — a stratified, human-tagged evaluation batch
(is_holding / correct_type / quote_complete, NULL until tagged).
db.py:
- goldset_create_sample (stratified round-robin over case×rule_type, idempotent),
- goldset_list (items + halacha content + the machine's own labels),
- goldset_tag (partial — one field at a time for keyboard tagging),
- goldset_score (ports the script's P/R/F1: each validator scored as a
not-a-holding detector against the human tags — the #81.8 input).
API: GET /api/goldset, POST /api/goldset/sample, GET /api/goldset/score,
PATCH /api/goldset/{id}.
web-ui:
- lib/api/goldset.ts (hooks),
- components/goldset/goldset-panel.tsx — card-per-item, keyboard-first
(J/K nav, H/N holding, C/X quote), progress bar, hide-tagged toggle, and a
collapsible live score table,
- app/goldset/page.tsx + nav link "מדגם-זהב" under ידע ולמידה.
Methodology guard kept explicit in UI + docstrings: tags are HUMAN ground truth,
no AI pre-fill (circular bias). Populated a 150-item stratified batch.
Verified: backend create/list/tag/score against the live DB; tsc --noEmit 0;
py_compile ok. (Local Turbopack build blocked by worktree symlink — CI builds clean.)
Invariants: G1 (eval set modeled at source in its own table); G2 (reuses the same
halacha_quality validators the extractor runs — no parallel scoring logic).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Cross-precedent recurrence of a principle is real but is NOT citation
corroboration (X11) — the 5 candidate pairs have ZERO citations between their
precedents. Recording them in halacha_citation_corroboration would fabricate
citation data and inflate corroboration_count. This adds a proper, separate
halacha-level link for parallel authority.
Schema (V28): equivalent_halachot — symmetric (halacha_a < halacha_b, CHECK +
UNIQUE), non-citation, cross-precedent-only. ON DELETE CASCADE.
db.py:
- link_equivalent_halachot (idempotent; rejects same-id and SAME-precedent pairs
— parallel authority is cross-precedent by definition), unlink, and
list_equivalent_for_halacha.
- list_halachot gains include_equivalents → _annotate_equivalents attaches an
`equivalents` list (both directions) per row.
API: include_equivalents on GET /api/halachot; GET/POST/DELETE
/api/halachot/{id}/equivalents for the chair to view/link/unlink manually.
scripts/halacha_batch_reconcile.py: --link records found cross-precedent pairs
as equivalent_halachot (non-destructive, idempotent).
web-ui: Halacha.equivalents type; the clean review queue fetches
include_equivalents; the review card shows a gold "עיקרון מקביל ב-N" badge + an
expandable list (case + rule + similarity) labeled "אסמכתה מקבילה — לא ציטוט".
Populated the 5 reviewed pairs (chair decision: keep all + link as parallel
authority). Verified: 5 rows; the 1023-20 hub annotates 3 of its halachot with
equivalents; tsc --noEmit exits 0.
Invariants: G1 (model recurrence at source in its own table, not by abusing the
citator); G2 (no parallel path — extends list_halachot); citator integrity
preserved (corroboration stays citation-only).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Document the failure mode hit on 06/06/26: a pruned npx cache makes the
running paperclip serve GET / → 500 (deleted ui-dist) and, on restart,
crash-loop because the server's startup assertCloudDatabaseContract()
out-races the post-exec patch loop.
Records the synchronous pre-extract+patch gate now in start-paperclip.sh
(paperclip-config c824e0f), the `--help` clean-extract trick, the three
bugs found while building the fix (ui-dist vs dist marker, set -e on patch
failure, pkill -f self-match), the manual recovery runbook, and the e2e
verification.
Invariants: docs-only; touches no G*/INV-* code paths.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
style_distance.measure_corpus_ratios(): מפצל כל החלטה ב-style_corpus לסעיפים
(chunker) ומחשב ממוצע %-סעיף — אגרגט "_all" + פר-תוצאה (כשיש). cached.
get_style_guide מציג שורת "נמדד בפועל" עם ⚠️ על פער מטווח-היעד.
מצב נוכחי: style_corpus.outcome לא מאוכלס → מוצג אגרגט כל-ההחלטות (n=48:
רקע 26.4% / טענות 9.7% / דיון 43.8% / סיכום 20.1%); פיצול לפי-תוצאה future-ready.
המדידה גם מאירה מגבלות זיהוי-סעיפים (כוונת T10 — לסמן פער לבדיקה). חופף-חלקית
ל-T7 שמודד adherence per-draft; זה מודד את הקורפוס. כשל מדידה מוצג, לא נבלע.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Completes #84 — surfaces the backend gating/prioritization (#84.1/#84.3, PR
#93) in the chair's review UI and adds near-duplicate clustering (#84.2).
Backend
- db.list_halachot gains `cluster` (#84.2): annotates each row with cluster_id +
cluster_size by unioning same-precedent halachot within HALACHA_CLUSTER_COSINE
(0.90, new config). Display-only — never merges/deletes. Pairwise is confined
to the returned set (cheap).
- GET /api/halachot exposes the `cluster` query param (default off).
Frontend (web-ui)
- Halacha type gains optional cluster_id / cluster_size (hand-written module; no
api:types regen needed — halachot aren't typed off the generated schema).
- useHalachotPending(opts): the default "clean" queue now fetches
exclude_low_quality + order_by_priority + cluster; needsFix:true returns the
flagged 'needs extraction fix' bucket (filtered client-side).
- HalachaReviewPanel: a "תור נקי / דורש תיקון-חילוץ" toggle (#84.1); near-dup
clusters collapse into ONE card showing "+N וריאנטים" with an expandable list,
and approve/reject/defer on a clustered card applies to all variants via the
batch endpoint (#84.2 + #84.4). Counts show true halacha totals (pendingTotal).
New flag labels added (application / near_duplicate / nevo_preamble_leak).
Verified:
- backend: list_halachot(cluster=True) on the live queue — algorithm correct
(groups related same-precedent rules at 0.78; none at the production 0.90
because dedup #82 already removed near-dups — the desired state).
- frontend: `tsc --noEmit` exits 0 (type-clean); no new lint errors (the one
lint error is pre-existing in training/learning-panel.tsx from #94). Local
Turbopack build can't run on the worktree node_modules symlink — CI builds in
a clean checkout.
Invariants: G1 (gate/cluster at source in SQL, not post-hoc); G2 (same
list_halachot path); §6 (flagged items routed to a visible bucket, not dropped).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
#88 (DB↔file, lessons #35): drafts/decision.md דרסה את עצמה רק ב-save_block_content;
renumber_all_blocks + נתיבי store_block אחרים השאירו את הקובץ stale → QA נכשל
פעמיים על אותה בעיה (CMPA-62). תיקון: _update_draft_file הפך ל-hook אוטומטי
(מקבל decision_id, מאתר case פנימית) שנקרא מ-store_block (כל persist) ומ-
renumber_all_blocks. legal-qa ממילא קורא מ-DB → שני הצדדים זהים תמיד.
#87 (claims_coverage, 1033-25): טענות מתכתובת (claim_type='reply' — תגובה/
השלמת-טיעון) סומנו "לא נענו" כ-false-positive. תיקון: check_claims_coverage
דורש מענה רק לטענות כתב-הערר (claim_type='claim', appellant); reply/תכתובת
מוחרגות. בקבלה מלאה הסף מוקל (0.2→0.4) כי העורר זכה במלואו.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
npm run api:types — מסנכרן types.ts המחולל עם ה-endpoints החדשים
(/api/learning/pairs, style-distance, promote). הקוד משתמש בטיפוסים ידניים
(learning.ts) אז זה היגיינה לעתיד, לא תלות. סוגר את T11.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
שורש #85 התברר: `claude -p` נכשל מדי פעם ב-exit מהיר + stderr ריק על
פרומפטים גדולים/איטיים (CEO write_interim_draft, learning_loop distillation),
**אותו פרומפט מצליח בריצה חוזרת** — כשל חולף, לא nesting (אומת: nested claude
מ-bash וגם פרומפט 70K הצליחו; הכשל אינו דטרמיניסטי).
query() עוטף spawn+communicate ב-לולאת retry (MAX_RETRIES=3, backoff לינארי
5s*attempt). FileNotFoundError + timeout נשארים דטרמיניסטיים (ללא retry).
empty-response גם מטופל כ-transient.
אומת e2e: distillation על 1130-25 רץ בהצלחה → pair=analyzed (9 שינויים,
6 style_method, 33.8% diff). פותר גם את write_interim_draft של ה-CEO.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Backend for the halacha approval-queue triage (#84). The keyboard UI, batch
actions and defer/reject (#84.4–6) already shipped; this adds the gating,
prioritization and metrics the queue was missing.
db.list_halachot — two opt-in triage controls:
* exclude_low_quality (#84.1): drop items carrying ANY quality_flag
(application / quote_unverified / truncated / non_decision / thin /
nli_unsupported / near_duplicate) — they belong in a 'needs extraction fix'
bucket, not the chair's approve queue.
* order_by_priority (#84.3): active-learning order — negatively-treated
first, then most-uncertain (lowest confidence), then oldest — instead of
FIFO, so the highest-value decisions surface first.
halachot_pending (MCP) — now gated + prioritized BY DEFAULT; include_low_quality=
true reveals the needs-fix bucket. The agent review path benefits immediately.
GET /api/halachot — same two params, default OFF (non-breaking; the UI opts in).
metrics.halacha_backlog (#84.7) — splits pending into clean vs flagged, adds
deferred, reviewed_total, approve_ratio, and a pending_by_flag breakdown, so the
backlog distinguishes real review work from extraction noise.
Deferred (documented): #84.2 near-duplicate cluster cards and wiring the UI
fetch to the new params require frontend work + an api:types regen AFTER this
deploys (the new query params aren't in prod's OpenAPI until then) — a clean
follow-up. The backend fully supports both now.
Verified against the live DB (read-only):
- pending 177 → gated-clean 110, 0 flagged items leak into the clean queue.
- priority order surfaces the lowest-confidence items first (0.55, 0.55, ...).
- backlog: pending_clean=110 / pending_flagged=67 / approve_ratio=0.916,
pending_by_flag={nli_unsupported:59, quote_unverified:3, thin:3, truncated:2}.
- pytest tests/test_halacha_quality.py — 52 passed (no regression).
Invariants: G1 (gate at source — SQL filter, not post-hoc); G2 (no parallel
path — same list_halachot); §6 (flagged items routed to a bucket, never dropped).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Halacha-extraction quality (#81) and dedup-on-insert (#82) — engine changes
(pure + tested) plus measurement/ops tooling.
halacha_quality.py
- #81.4 application gate: is_fact_dependent() (high-precision "applied to THIS
case" deixis per the strict rubric §3/§27) + FLAG_APPLICATION. compute_quality_flags
now takes rule_type and flags rule_type=='application' OR fact-dependent —
blocking auto-approve (an illustration is not a generalizable holding).
- #82.3 lexical tail signal: jaccard_shingles / normalized_levenshtein /
lexical_near_duplicate + FLAG_NEAR_DUPLICATE, for the 0.83–0.93 cosine band.
halacha_extractor.py — pass rule_type to the flag computation; re-type a
binding-labeled fact-application to 'application' (mirrors non_decision→obiter).
db.py (store_halachot_for_chunk) — dedup now fetches the nearest same-precedent
neighbor once: cosine ≥ DEDUP → skip (unchanged); cosine in [BAND, DEDUP) with
high lexical overlap → FLAG_NEAR_DUPLICATE (review, not skip — never drop a
possibly-distinct principle unreviewed).
config.py — HALACHA_DEDUP_BAND_COSINE (0.83).
Scripts:
- scripts/halacha_goldset.py (#81.7) — export stratified sample for human
tagging; score validators (P/R/F1) against the tags. Backbone for #81.8.
- scripts/halacha_batch_reconcile.py (#82.7) — conservative cross-precedent
dedup (cosine ≥0.95), dry-run report only.
- scripts/calibrate_halacha_dedup.py (#82.1) — calibrate the lexical thresholds
against the 2026-06-03 cleanup gold-set.
Deferred (documented): #82.4 merge-provenance and #82.5 DB ON CONFLICT/UNIQUE
on normalized quote are NOT included — the current skip+flag behavior is safe,
whereas a UNIQUE on normalized_quote would fail on existing dups and a blind
merge risks losing provenance; they need their own chair-reviewed migration.
#82.6 over-merge guard is moot until merge lands. #81.6 full rhetorical-role
classifier deferred (section pre-filter + application flag cover the practical
case); #81.8 blocked on the human-tagged gold-set (harness now provided).
Verified:
- pytest tests/test_halacha_quality.py — 52 passed (14 new).
- calibrate: configured (0.55,0.70) → precision 1.0 (zero false-merge), recall
0.30 — correct profile for an auto-approve-blocking signal.
- goldset export: 15-row sample CSV. batch reconcile: 819 halachot → 5
cross-precedent candidate pairs.
Invariants: G1 (normalize at source — flag at insert, not at read); §6 (no
silent swallow — suspect items flagged to review, never dropped); G2 (no
parallel path — same store_halachot_for_chunk / compute_quality_flags).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
#86.2 backfill + #86.3 benchmark, plus a #86.1 over-strip fix found en route.
extractor.py
- extract_nevo_ratio(): capture Nevo's מיני-רציו block (editorial holdings
summary) before it is stripped — a free professional gold-set (#86.3).
- _DECISION_START hardening (#86.2): the merged #86.1 regex over-stripped.
(a) פסק-דין headers are markdown-wrapped (**פסק דין**); the old anchor
required the keyword as the first line char with one separator, so it
missed the header and matched a citation 32K deep (עמ"נ 50567-07-21,
losing 45% of the body). Now tolerates leading markdown + 0-3 seps,
and the final-nun form (דין ן vs דינו נ).
(b) bare השופט/הנשיא matched CITATIONS ("השופט מ' חשין, פסקה 23"). The
authoring-judge line ends with a colon; we now require it.
ingest.py
- capture the ratio before stripping and store it on the row (best-effort,
non-fatal); also strip the text-upload path (was file-only).
db.py
- add case_law.nevo_ratio column (additive); allow it in update_case_law.
scripts/backfill_nevo_preamble.py (#86.2) — dry-run-by-default data migration:
finds historically-leaked rulings, captures ratio→nevo_ratio, rewrites
full_text (+content_hash), reindexes, and FLAGS (never deletes) halachot whose
quote lives in the removed preamble (review_status=pending_review +
nevo_preamble_leak flag). Safety guard: rows with keep%<--min-keep (60) are
excluded from --apply as suspected over-strip. --apply writes backup+manifest
to data/audit/ first. Chair-gated — NOT applied here.
scripts/nevo_ratio_benchmark.py (#86.3) — LLM-as-judge (local claude_session,
zero cost) measures recall/precision/granularity of our halachot vs the Nevo
ratio. Works pre- and post-backfill (reads nevo_ratio, falls back to full_text).
Verified:
- pytest tests/test_nevo_preamble.py — 12 passed (incl. citation/markdown
over-strip regressions).
- backfill dry-run: 19 leaked rulings, 27 contaminated halachot, all ≥75%
keep (the 32K over-strip is gone).
- benchmark on בג"ץ 1764/05: recall=0.875 precision=1.0 granularity=1.75x.
Invariants: G1 (normalize at source — strip/capture at ingest, not at read);
no silent swallow (contaminated halachot flagged + reported, not dropped);
data-migration is dry-run-default with backup+manifest, chair-gated.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
write_interim_draft failed for all blocks from the CEO MCP instance with
"Claude CLI failed (exit 1): unknown error". Two fixes:
1. Error surfacing (the certain win): on non-zero exit, capture and log
both stderr AND stdout (the CLI sometimes writes its diagnostic to
stdout or nowhere), so the next occurrence is diagnosable instead of
collapsing to "unknown error". This is why #85 was unsolved — the real
error was swallowed (engineering rule §6: no silent swallow).
2. Defensive hardening: strip Claude Code session markers (CLAUDECODE,
CLAUDE_CODE_*, CLAUDE_AGENT_*, AI_AGENT, CLAUDE_EFFORT) from the env of
nested `claude -p` calls and run them from $HOME, decoupling them from
the parent agent's session/project state. Aligns query() with the
existing query_streaming() path (which already sets cwd=HOME). Auth/
config vars are preserved.
Note: the original adapter-context failure could not be reproduced in a
plain interactive session (nested claude -p succeeds there in both old and
new code), so the env markers are a suspect, not a proven cause. The real
value is the diagnostics. Verified: nested query() returns PONG from
inside a CLAUDECODE=1 session; unit tests cover env sanitization.
Invariants: G1 (normalize at source — fix the spawn, not readers),
G2 (no parallel path — same query()), §6 (no silent error swallow).
INV: feedback_claude_session_local_only preserved (all calls stay local).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
