The chair (Dafna/chaim) reviewed and approved the full corpus-refresh proposal
generated by scripts/regenerate_voice_fingerprint.py and committed it to the live
voice-fingerprint — satisfying the INV-LRN1 hard chair-gate (a human approved;
the script only ever proposed). +81/-15 lines: all the deletions are reword-and-
expand of existing lines (no curated insight lost), the additions are style/method
refinements grounded in the 56-decision corpus (INV-LRN5 — no case substance):
- §1.2 conditional-acceptance as an "anחנו" verb (מקובל עלינו vs נציין)
- §1.3 ruling variation "ראשית, צודק [צד]... אלא ש"
- §1.5 emphasis always annotated "(הדגשת הח\"מ)"
- §1.8 bounded appraiser-restraint (professional plane only; legal plane = no deference)
- §1.9 inverse twin "ניתן היה לסיים... אלא ש"
- §1.11 quantitative anchoring as a reframing device (cross-type)
- §1.12 measured block ratios (background 17 / claims 27 / discussion 42 / summary 14)
- §1.13 faithful rendering of a party's internal reasoning
- §2.2 two-sided pendulum for the restraint paragraph + expanded party-verb catalog
- §4.8 new template "ניתן היה לסיים — אלא ש"
- §5.x agent instructions updated to reference the new patterns
Invariants: INV-LRN1 (chair approved before commit — the gate held), INV-LRN5
(style/method only, no substance).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The voice-fingerprint (docs/daphna-voice-fingerprint.md) is the PRIMARY abstract
style channel the writer consumes (07-learning §0.2 channel A), but it was
hand-authored and never regenerated from the growing corpus — the "voice" the
writer adapts stayed frozen while finals accumulated. PR #345 unfroze the
structural half (corpus-measured ratios → writer); this is the prose half.
scripts/regenerate_voice_fingerprint.py reads the corpus (style_corpus stats +
a bounded block-level style_exemplars sample + measured section ratios) and asks
Opus (local) to PROPOSE refinements/additions to the fingerprint — STYLE / METHOD
/ VOICE / LEXICON only, grounded in corpus evidence, never case substance
(INV-LRN5), preserving curated insights rather than replacing them.
CHAIR-GATED, HARD (INV-LRN1): the prose profile is voice-knowledge, not a
low-risk style rule, so it does NOT auto-flow. The script writes a PROPOSAL to
data/curator-proposals/ (the existing curator-proposal surface) and NEVER
overwrites the live fingerprint; the chair reviews and hand-commits accepted parts
— the same manual gate the fingerprint already uses. Runs on the host (claude CLI).
Reuses claude_session + measure_corpus_ratios + the curator-proposals dir (G2 —
no parallel synthesis or gate). SCRIPTS.md + spec §0.2 updated.
Invariants: INV-LRN1 (hard chair gate for voice-knowledge prose), INV-LRN5
(style-only synthesis), G2 (reuses existing synthesis inputs + proposal surface).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The writer, learning panels, and legal_mcp tools run from the HOST tree
(Paperclip agents claude -p with cwd=~/legal-ai; pm2 services import from
mcp-server/src) — not the container. A merge + Coolify deploy only refreshes the
FastAPI container; host-side code stayed on the last manual `git pull`. On
2026-06-28 the host was 16 commits behind, so a day of learning-loop fixes sat
dormant until pulled by hand.
host_sync.sh (run every minute via cron, like the existing data/training pull)
fast-forwards the host tree to origin/main when it falls behind. Fast-forward
ONLY — never forces, so the perpetually-dirty .taskmaster/tasks/tasks.json is
never clobbered (clean ff leaves it; an upstream conflict logs + bails for manual
handling). Agent runs spawn fresh and pick up new code with no restart; only the
long-running pm2 services that import app code (chat_service, court_fetch_service,
reaper) are restarted, and only when their own files changed (precise, minimal
churn). Logs to data/logs/host_sync.log.
Cron entry (added on the host, flock-guarded):
* * * * * flock -n /tmp/host_sync.lock bash ~/legal-ai/scripts/host_sync.sh
SCRIPTS.md updated.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Golden ratios were measured from the corpus (style_distance.measure_corpus_ratios)
but never reached the writer — it used only the hardcoded STRUCTURE_GUIDANCE text.
So the structural target was frozen, and drafts kept deviating (e.g. discussion
block 10% vs a 40-47% target) with no corrective signal.
_structure_guidance_with_corpus(outcome, practice_area) now appends the
corpus-measured section ratios for the block's outcome to the structure guidance,
at both writer entry points (write_block + get_block_context) via one shared helper
(G2). Because measure_corpus_ratios reads style_corpus — which grows with every
enrolled final (see exemplar-growth, #343) — the writer's structural target now
reflects Dafna's ACTUAL current distribution and improves as the corpus grows.
Deterministic (no LLM); best-effort.
This is the STRUCTURAL half of the voice-profile-refresh (#7). The remaining half —
LLM-regenerating the abstract voice-fingerprint PROSE from the corpus (chair-gated)
— is a distinct larger initiative, deliberately deferred rather than rushed.
Invariants: G1 (the writer gets the live measured target, not a frozen constant),
G2 (one structure-guidance builder shared by both entry points; reuses the existing
measure_corpus_ratios — no parallel measurement), INV-LRN4 (the corpus the loop
grows now feeds the writer's structural target).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The chair-feedback chain was DEAD: 27 feedback rows captured, 0 ever became a
lesson the writer reads (no weekly-analysis job ever existed). The chair's own
corrections — the most authoritative signal of all, and exactly "learn from every
returned draft" — went nowhere.
decision_lessons can't carry them: it's FK-coupled to a style_corpus row (a signed
final), which a case-in-progress doesn't have. So chair STYLE feedback instead
rides the discussion_rules channel that already reaches the writer for all blocks —
the same path /training promote uses.
- db.append_global_rule: the locked read-modify-write append, extracted from web
`_append_methodology_override` into one shared impl (G2). The web function is now
a thin wrapper that seeds defaults; chair-feedback calls it directly.
- record_chair_feedback (MCP tool): a STYLE-category correction (style/wrong_tone/
wrong_structure) with a lesson_extracted flows immediately to discussion_rules.
The chair IS the gate — no separate approval (INV-LRN1 graduated gate). SUBSTANCE
feedback (missing_content/factual_error/other) is case-specific → recorded only.
Invariants: INV-LRN1 (chair-authored style = highest authority, flows; substance
not auto-flowed), G2 (single append impl shared by promote + feedback), INV-LRN5
(style channel only).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The style-exemplar corpus (channel B — the writer's block-level retrieval of
Dafna's real prose) was FROZEN at the one-time seed backfill: new finals were
enrolled into style_corpus but never broken into exemplars, so the richest style
channel never grew (8137/8126/8174 had 0 exemplars). The writer kept retrieving
only March–April seed paragraphs no matter how many finals were signed.
Extract the per-decision exemplar logic (section→paragraph→Voyage-embed→replace)
into a shared service `legal_mcp.services.style_exemplars.extract_and_store` —
the SINGLE implementation now used by BOTH the one-time backfill and the live
enrollment path (G2; no parallel extractor). `_enroll_final_in_library` calls it
on every final upload (source='internal_committee', the same source the writer's
search_style_exemplars reads). Voyage embeds over REST → container-safe;
best-effort, surfaced in the upload response, never fails the upload.
Effect: every signed final now grows the exemplar corpus, so the writer's
block-level style retrieval improves with each decision — the core "learn from
every decision" fix for channel B. Path A (style_distance_history) will track
whether the larger exemplar pool reduces style-distance over time.
Invariants: G2 (one extraction path shared by backfill + enroll), INV-LRN5
(style/structure prose only — substance routes elsewhere), INV-LRN4 (the
draft↔final loop now feeds the exemplar channel, not just the lesson channel).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The voice-learning panel produced 81 vetted style lessons — all stuck at
review_status='proposed' with 0 ever approved — so the writer (which reads only
'approved') received NONE of them. The system captured learning but never let it
flow. Chair decision (2026-06-28): a GRADUATED gate by content risk.
- STYLE lessons (categories style/structure/lexicon/tabular) the 2/2 panel kept →
created as review_status='approved' → flow to the writer immediately, reversibly
(chair vetoes in /training). The deepseek+gemini panel only emits style_method
and only on 2/2 consensus, so this is exactly the gate's criterion; substance is
already filtered out and skipped, and routes through the strict halacha gate.
- SUBSTANCE (halacha/precedent/fact) stays a HARD chair gate — unchanged.
style_lesson_panel.py: _review_status_for(category) sets the gate explicitly
(approved for _STYLE_CATEGORIES, else proposed); the apply loop passes it to
db.add_decision_lesson (which already accepts review_status — no DB change).
Spec: INV-LRN1 rewritten as the graduated gate (hard for substance; reversible
auto-flow for consensus style — still "under user control" via veto, per
NCSC/CEPEJ); §0.6 updated to match.
A one-time backfill of the 81 existing panel style lessons to 'approved' runs
separately (DB, post-merge).
Invariants: INV-LRN1 (amended — graduated), INV-LRN5 (style-only, substance never
auto-flows), G10 (human control preserved as reversible veto).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The learning loop measured anti-patterns but never corrected them. style_distance
detects markdown headers / bullet lists / mid-paragraph mini-lists (from the
canonical lessons.ANTI_PATTERNS), but the writer only received anti-pattern
guidance if a chair `anti_patterns` override existed in appeal_type_rules — and
none does. So _build_style_context's `if ov:` branch injected nothing, the writer
was never told to avoid them, and drafts kept emitting them (8137: 28 hits, the
worst, newest — anti-patterns were trending UP, not down).
Anti-patterns are structural invariants of Dafna's voice (continuous legal
narrative — no markdown, no bullets), not overridable preferences. So inject the
canonical ANTI_PATTERNS notes ALWAYS, from the same list style_distance measures
against (single source of truth), with any chair additions layered on top. This
closes the measure-but-don't-correct gap: the next draft should show the markdown/
bullet anti-patterns drop, and Path A (style_distance_history) will confirm it.
Invariants: G1 (correct at source — the writer, not a post-hoc stripper), G2
(one canonical anti-pattern list shared by detection and instruction — no parallel
list), INV-LRN4 (closes the feedback half of the draft↔final loop).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
תיקוני-מבנה ללולאת-הלמידה (TaskMaster #157):
1. כרטיס ה-curator (/training טאב "אוצֵר") ספר decision_lessons WHERE source='curator'
— ערך שאף מסלול-קוד לא כתב → תמיד 0. עוצב-מחדש (דרך שער-העיצוב Claude Design, אושר)
להציג ביושר את שלושת ערוצי-ההזנה לכותב: דיסטילציה→appeal_type_rules (180, זורם),
פאנל→decision_lessons (81, ממתין), אוצֵר→source='curator'. get_curator_stats שוכתב.
2. drift ספ↔סוכן: 07-learning.md §1.1 + INV-LRN3 קבעו שהאוצֵר רושם ממצאים כ-decision_lesson
source='curator', אך הסוכן כתב comments בלבד — הממצאים האיכותיים אבדו. נוסף כלי-MCP
record_curator_findings + §A.5b ב-hermes-curator.md (read-only נשמר; הצעה מגודרת-שער).
3. get_recent_decision_lessons(limit=15) חתך בשקט — נוסף WARN על מה שנחתך (חוקה §6);
הפתרון האמיתי = סינתזת-לקחים (TaskMaster #158).
Invariants: מקיים INV-LRN1/G10 (שער-יו"ר), INV-LRN3 (לכידה מובנית), INV-IA2/IA5 (מקור-אמת
יחיד), G12 (leak-guard עובר), G2 (אין מסלול מקביל — אותם מאגרים). פער-מימוש פתוח מתועד:
§A לא רץ אוטומטית על mark-final (pipeline-wake exits) → נדחה לתכנון נפרד.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Documents the prospective held-out methodology shipped in PR #337: why a clean
retrospective held-out is impossible (lessons stored universal/untagged → no
leave-one-out), and how the system instead captures a clean generalization
datapoint at final-upload — before this case's lessons are folded — via a
style_distance snapshot + lesson-pool size into style_distance_history,
surfaced by GET /api/learning/style-distance-history.
Adds §0.7, wires step [7] MEASUREMENT and INV-LRN4 to it. Notes the
change_percent style/content confound and the one-time clean window.
Invariants documented: INV-LRN4 (this is its trend surface), G2 (reuses
style_distance + appeal_type_rules — no parallel metric path).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
A clean held-out test of voice learning was no longer runnable: every
final-uploaded case already has its lessons folded, and lessons are stored
universal/untagged so leave-one-out is impossible. Path A makes the test
prospective instead — capture the generalization datapoint at the one moment
it's clean.
On final upload, after the draft↔final pair is created but BEFORE this
case's lessons are folded (folding is a separate manual /training step), we
snapshot style_distance (anti_pattern_total, golden-ratio max-deviation,
change_percent) alongside the current voice-lesson pool size. Because the
draft was written with only the PRIOR pool, each row is a clean "with N
accumulated lessons, our draft on this unseen case scored X" datapoint. As
the pool grows over cases, a downward trend = learning generalizes.
- db: SCHEMA_V45 style_distance_history (append-only) + helpers
voice_lesson_pool_sizes / record_style_distance_snapshot /
get_style_distance_history.
- app: best-effort capture in api_upload_final_decision (never fails the
upload); GET /api/learning/style-distance-history for the trend.
Reuses the existing style_distance service + appeal_type_rules pool — no
parallel metric path. The 8 existing cases are already folded, so the table
starts empty and fills from the next final (their clean window is past).
Invariants: G2 (reuse style_distance/appeal_type_rules — one path),
INV-LRN4 (measure the draft↔final gap; this is its trend surface). LLM-free
(style_distance is deterministic) so it runs in the container.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The two stage indicators in the compose page's "השלמה והעברה" rail
("הרץ למידת-קול" / "הרץ אימות-הלכות") were static placeholder text
translated from mockup 03 and never wired to data — they always read
"ממתין להעלאת הסופי", even after the final was uploaded and both
pipelines completed. (The real status was already shown correctly by
LearningStatusBadges on the case page.)
Wire them to useCaseLearningStatus (/api/cases/{n}/learning-status) — the
same source the drafts-panel badges use (G2). The trailing text is now
derived: "ממתין להעלאת הסופי" until the final is uploaded, then the live
state ("✓ הושלם · 12 לקחים הופקו · 12 הוצעו לאישור" / "✓ הושלם · חולצו 48
· 33 אושרו · 15 נדחו", or running/queued/failed).
Data-binding bugfix only — identical markup/classes (mockup-03 layout
preserved), so no visual redesign; within the design-gate bugfix exception
(chair-approved approach). tsc + eslint clean.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
When a chair's signed final decision is uploaded it is enrolled into the
precedent library, but _enroll_final_in_library only set deterministic
fields (citation, proceeding_type, date) and copied subject_tags from the
case's subject_categories — which is usually empty. The Gemini metadata
pass (subject_tags / summary / headnote / key_quote) was never triggered,
so the row sat at metadata_extraction_status='pending' with no subject
tags until a drain happened to pick it up. In practice a freshly-enrolled
final showed an empty "תגיות נושא" in the precedent edit UI.
Fix: after enrollment + citation, call the existing reextract_metadata
path inline (G2 — one path, full status lifecycle). It runs on Gemini
Flash over REST (GOOGLE_GEMINI_API_KEY, already in Coolify), so it is
container-safe — unlike the halacha path (claude CLI, host-only).
apply_to_record fills only empty fields, so the deterministic seeds and
any chair-curated subject_categories are preserved. Result surfaced in the
upload response (out["metadata"]); failures logged, upload still succeeds.
Also corrects two now-stale comments: the "Gemini returns no_metadata for
internal decisions" note in the enroll loop, and the "MCP-tool-only path"
docstring on reextract_metadata (true for halacha, not for Gemini REST).
Invariants: G1 (fill at source on enroll, not a read-time workaround),
G2 (reuse reextract_metadata — no parallel extraction path). LLM call is
Gemini REST, not claude_session, so the container LLM-call constraint holds.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
renumber_cases.py step 6 only renamed the Paperclip project, leaving the
case↔issue linkage on the OLD case number. get_case_issues() keys on two
text surfaces the script never touched:
• plugin_state.legal-case-number (value_json) — the authoritative linkage
• issues.title — the '[ערר {cn}] …' tag the title-path lookup matches
Result: after a renumber the issues kept the old number, get_case_issues
returned [], and post-final actions (run-learning / run-halacha) silently
skipped with reason "no_issue" — surfaced in the UI as "לא הופעלה למידה".
Discovered on case 8137-11-24 (renamed from 8137-24).
Now the Paperclip step rewrites all three surfaces (projects.name +
plugin_state + issue titles); inspect_paperclip + the dry-run report show
the linkage-row and issue-title counts that will be rewritten.
The 11-case migration already ran; the matching DB rows were fixed
manually (incl. this commit's logic) for all stale cases. This change is
for any future renumber.
Invariants: G1 (normalize at source — the linkage, not a read-time
workaround). G12 note: this is a one-time host-side migration script that
already connects directly to the Paperclip DB by design (below the platform
port, like the existing projects/MinIO/Gitea surgery) — it does not add a
parallel runtime path through agent_platform_port.py.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Inline # comments in gitignore are not supported — they were silently
breaking three patterns (data/checkpoints/, data/adapter-migration-state.json,
.claude/agents/.generated/). Moved comments to their own lines and added
missing entries for runtime dirs (data/audit/, data/logs/, etc.) and
temp files (.interaction_tmp.json, .design-build/, .taskmaster bak files).
Also tracks previously untracked legitimate files: scripts, tests, docs,
skills references, .env.example, taskmaster templates.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Switches the scanned-PDF fallback from Google Cloud Vision to
Mistral OCR (mistral-ocr-latest) for better Hebrew accuracy and
robustness against broken embedded OCR layers (e.g. case 1044-03-26
which returned English garbage through Vision).
Routing strategy (document-level, not per-page):
- PyMuPDF extracts all pages; pages that pass _text_quality_ok()
use PyMuPDF output directly (free, ~50ms).
- If ANY page fails quality → Mistral OCR called once for the whole
PDF, returning per-page Markdown for all pages (consistent format,
no plain-text/Markdown mix within a document).
Markdown output preserved: Mistral returns ## headers and |tables|;
chunker updated to recognise ATX Markdown headers (##/###) as section
boundaries in _split_into_sections().
Config: GOOGLE_CLOUD_VISION_API_KEY → MISTRAL_API_KEY; allowlist
updated vision.googleapis.com → api.mistral.ai.
MISTRAL_API_KEY added to Coolify container env.
Invariants: G1 (single OCR fallback path, not parallel), G2 (no
duplicate extractor route), INV-AH (Mistral handles gershayim
natively; quote-fix only on PyMuPDF path).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
qa_passed was set by the old agent pipeline but not included in the
trimmed 10-status CASE_STATUSES list or LEGACY_STATUS_LABELS, causing
the status badge and workflow timeline to render nothing ("לא ידוע").
Added qa_passed → "טיוטה" to LEGACY_STATUS_LABELS as a display-only
fallback so any case still carrying this value renders correctly until
migrated. Case 8174-12-24 status updated to drafted via PUT /api/cases.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Adds a one-click 'reset agents' action for cases where writer/QA agents
are stuck in Paperclip's error state (triggered by recovery loop or
failed run). Addresses the root cause documented in
reference_paperclip_recovery_loops: reassigns open issues from agents
back to the chair user, and calls reset_agent_session for each error
agent to clear wedged runtime sessions.
Changes:
- paperclip_client.py: reset_case_agents() — reassigns stuck issues +
clears error status in Paperclip DB + calls reset_agent_session
- agent_platform_port.py: exports pc_reset_case_agents (G12 gate)
- app.py: POST /api/cases/{case_number}/agents/reset endpoint
- agents.ts: useResetCaseAgents mutation hook + AgentResetResult type
- agent-status-widget.tsx: 'אפס' button (shown only when error agents
exist) with Dialog confirmation + loading state + toast feedback
Invariants: G12 (Paperclip only via port), G2 (no parallel path —
uses existing reset_agent_session + pc_get_case_issues).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
aggregate_claims_to_arguments crashed with "current transaction is aborted,
commands ignored until end of transaction block" on large cases (confirmed on
1027-04-26, 195 claims; reported via CMP-186).
Root cause: the proposition INSERT (legal_argument_propositions) was wrapped in
a broad except Exception with no savepoint. When the LLM echoes a
syntactically-valid-but-nonexistent claim_id, the FK violation
(legal_argument_propositions_claim_id_fkey) puts the asyncpg transaction into
aborted state. The except caught only that INSERT's error but never issued
ROLLBACK TO SAVEPOINT, so the next statement (the following argument's INSERT
into legal_arguments) raised InFailedSQLTransactionError uncaught and crashed
the whole call. With many claims the bad-UUID probability is high -> consistent
failure.
Fix:
- Validate each claim_id against the known set of claim ids fetched for the
case before INSERT, so a hallucinated id never reaches the DB (G1: fix at
source). Malformed UUIDs are already dropped in _normalize_argument; this
catches the valid-but-nonexistent ones.
- Wrap the INSERT in a per-row savepoint (async with conn.transaction()) as
defense-in-depth, so any unexpected constraint failure rolls back to the
savepoint instead of poisoning the surrounding transaction.
Invariants: G1 (normalize at source, not symptom-catch on read). No parallel
path (G2). No silent swallow — skips are logged.
TaskMaster: legal-ai #156
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Full code review of the case-detail page (14 components) surfaced these,
all fixed here:
Logic bugs
- case-edit-dialog: form.reset ran on the 5s useCase refetch while the dialog
was open, clobbering in-progress edits. Now resets only on open→true.
- status-changer: `selected` never synced to async/external `currentStatus`
(stale dropdown). Reworked to track currentStatus until an explicit pick;
resets to tracking after save.
- decision-blocks-panel: `block.content`/`word_count` accessed without null
guards (endpoint has no response model) → potential render crash. Coerced
with `?? ""` / `?? 0`. `STATUS_LABELS[status]` now falls back to the raw
status instead of rendering literal "undefined".
- document-type-editor: `await mutateAsync()` in async click handlers without
try/catch → unhandled promise rejection. Wrapped (errors still surface via
isError).
Resilience / hygiene
- page.tsx: a transient 5xx on the background poll flipped the WHOLE page to
the error card and discarded loaded data. Now gated on `!data`, plus a
"נסה שוב" retry.
- cases.ts useUpdateCase: invalidated casesKeys.all, which re-invalidated the
detail it had just optimistically patched. Scoped to the list prefix.
RTL correctness (logical properties)
- agent-status-widget `mr-auto`→`ms-auto`; agent-activity-feed `mr-auto`→
`me-auto`, icon `ml-1/ml-2`→`me-1/me-2`, required `*` `mr-1`→`ms-1`;
document-type-editor list `pr-4`→`ps-4`.
Minors
- drafts-panel: `<a href>`→`next/link` (operations + citation links) for SPA
nav. agent-activity-feed: issueMap memoized; comment Textarea aria-label.
upload-sheet: `unknown` status no longer shown as green success (neutral
icon + "רענן לאישור"). citations.ts: case_name typed `string | null`.
Design gate: visual-touching items (RTL gap side, retry button, neutral
upload icon) were chair-authorized via the reviewed-findings approval ("fix
all"); none alter an approved page layout — they are correctness fixes.
tsc clean; eslint clean (1 pre-existing form.watch warning, untouched line).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Implements the Claude-Design-approved inline status banners for the
"חשב טיעונים" panel (mockup 25-legal-arguments-panel): the four endpoint
states (queued / exists / no_claims / skipped) now render as tone-coded
banners below the header instead of a transient toast. Toast is kept only
for hard transport errors.
Also fixes a pre-existing double-card bug found while reviewing the page:
the page's "arguments" tab already wraps the panel in <Card><CardContent>
(page.tsx:151-155), yet LegalArgumentsPanel rendered its OWN <Card> too —
unlike its sibling tab panels (DecisionBlocksPanel/DraftsPanel/
AgentActivityFeed) which render a plain <div>. The panel now matches that
convention (single card, no double border/padding), consistent with the
approved single-card mockup.
Design gate: card 25 approved by חיים. tsc + eslint clean.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
