Commit Graph

27 Commits

Author SHA1 Message Date
5f43659b5a fix: add defensive JSON parsing in check_instructions 2026-05-16 17:53:42 +00:00
86734da210 feat: add --check-instructions, pre-flight validation, and mtime tracking to sync script
- P3-T1: --check-instructions flag + check_instructions() prints a table of all
  agents' instructionsFilePath with status ( OK /  MISSING / ⚠ NOT SET),
  size, mtime, and ⚠ DRIFT when file has changed since last sync
- P3-T2: --apply now runs a pre-flight check on master agents and aborts if any
  instruction file is missing, before touching the DB or calling any API
- P3-T3: get_claude_md_mtime() helper; --apply stamps claude_md_mtime and
  claude_md_last_synced into each mirror agent's metadata via the PATCH call
- P3-T4: alias check-agents added to ~/.bashrc

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-16 17:51:34 +00:00
45341a0bc8 feat(curator): switch Hermes Curator to DeepSeek V4-Pro via deepseek_local adapter
A/B test (2026-05-05) showed DeepSeek V4-Pro is 2-3x faster and ~20x cheaper
than Sonnet for style/lexicon pattern analysis, with comparable quality.
Adds adapters/deepseek-paperclip-adapter/ package, documents adapter requirements
(env injection, run-id headers), updates CLAUDE.md with adapter integration notes,
and records lessons from ערר 1200-25 (block order for 1xxx, "להלן מתוך" pattern,
expanded factual background, bridge planning analysis, flat heading structure).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-10 05:58:52 +00:00
1b14e04373 chore(skills): remove paperclip-dev, scope converting-plans-to-tasks
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paperclip-dev is for maintaining the Paperclip codebase itself — not
relevant to legal work. Removed from all 14 agents (was on CMPA mirror).

paperclip-converting-plans-to-tasks helps decompose a plan into assigned
issues. Useful for the planning-heavy agents (CEO, analyst). Now scoped
to those two — removed from the other 5 in CMPA where it had crept in.

Net effect: zero drift on paperclipai/* skills across all 7 master+mirror
pairs. Verified via the new Agents tab dashboard.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-04 17:47:05 +00:00
cf5f6fe274 feat(paperclip): close 11 integration gaps (#16-#28)
Brings the legal-ai ↔ Paperclip integration in line with the official
Paperclip skill. Net effect: HEARTBEAT.md -47% (370→195 lines), all 14
agents on uniform runtime_config + budget + instructionsBundleMode, and
two cross-company helpers replacing manual SQL.

Highlights:
- HEARTBEAT.md refactor: project-specific only, delegates to the official
  paperclipai/paperclip skill (loaded per agent). Adds heartbeat-context
  fast-path (§1.7) and PAPERCLIP_WAKE_PAYLOAD_JSON shortcut (§1.5).
- Issue Thread Interactions API: legal-ceo.md now uses
  ask_user_questions / request_confirmation / suggest_tasks instead of
  free-text comments — gives chair structured UI with idempotency keys.
- pc.sh + paperclip_api.pc_request: every API call goes through helpers
  that inject Authorization + X-Paperclip-Run-Id (audit trail).
- sync_agents_across_companies.py: master(CMP)→mirror(CMPA) sync via
  Paperclip API, idempotent, with --verify and --apply modes.
- skills/new-company-setup: 11-step blueprint distilling all 11 gaps
  into a single onboarding runbook for the next company.
- .taskmaster: 12 tasks covering each gap (one already closed: #29).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-04 17:25:45 +00:00
8a815ecff5 fix(retrieval): rewrite chunk-page retrofit to skip OCR
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The first-pass retrofit re-extracted via extractor.extract_text, which
re-runs Google Vision OCR on scanned pages. OCR is non-deterministic,
so the new text didn't match the chunk content stored in the DB
(produced by the original OCR run) — only ~7% of chunks were located.

New approach (no OCR cost):

1. Use the stored documents.extracted_text from the DB — the exact
   text the chunks were produced from, so chunk lookups match.
2. Anchor page boundaries via PyMuPDF direct text reads (free, no
   OCR). Pages with usable direct text are anchored by snippet match;
   OCR-only pages are linearly interpolated between anchors.
3. Search each chunk in extracted_text using a whitespace-tolerant
   helper — needed because the chunker joins paragraphs with single
   '\\n' while extracted_text uses '\\n\\n' as page separators.

Verified on 8174-24 (5 docs, 307 chunks) + 8137-24 (9 docs, 512
chunks): 100% chunks tagged, 13s total, $0 cost.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-03 20:04:33 +00:00
81ccf3a888 feat(retrieval): track page_number on text chunks for multimodal hybrid boost
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The legacy chunker did not track which PDF page each chunk came from.
Stored chunks had page_number=NULL, which blocked the multimodal
hybrid retriever's text+image boost — it joins (chunk, image) on
(document_id, page_number) and the join could never fire.

This change:

- extractor.extract_text now returns (text, page_count, page_offsets);
  page_offsets[i] is the start char offset of page (i+1) in the joined
  text. None for non-PDFs.
- chunker.chunk_document accepts an optional page_offsets and tags
  each chunk with the page that contains its first character (uses
  the existing chunker logic; pages assigned post-hoc by content
  search to keep the diff minimal).
- processor.process_document and precedent_library.ingest_precedent
  forward page_offsets through the chunker. New uploads now carry
  accurate page_number on every chunk.
- Other extract_text callers (tools/documents, tools/workflow,
  web/app.py) updated to unpack the third element (ignored).
- scripts/backfill_chunk_pages.py: per-case retrofit. Re-extracts each
  PDF (re-OCRs via Google Vision if needed, ~$0.0015/page), computes
  page_offsets, and updates page_number on every chunk by content
  search. Idempotent; --force re-runs on already-tagged docs.

Forward-only would leave the 419 image embeddings backfilled on
cases 8174-24 + 8137-24 unable to boost their corresponding text
chunks. The retrofit script closes that gap (cost ~$0.60).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-03 19:49:41 +00:00
242f668319 feat(retrieval): add voyage-multimodal-3 page-image embeddings (feature flag)
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Stage C: per-page image embeddings via voyage-multimodal-3 + hybrid
text+image search. Off by default; enable with MULTIMODAL_ENABLED=true.

- Schema V9: document_image_embeddings + precedent_image_embeddings
  (vector(1024), page_number, image_thumbnail_path)
- extractor.render_pages_for_multimodal renders PDF pages at
  MULTIMODAL_DPI (144) for embedding + JPEG thumbnails at
  MULTIMODAL_THUMB_DPI (96) for UI preview, in one pass
- embeddings.embed_images calls voyage-multimodal-3 in 50-page batches
- services/hybrid_search.py orchestrator: rerank applied to text side
  first (rerank-2 is text-only); image side cosine; weighted merge
  with text_weight 0.65 (env-tunable); image-only pages surface as
  match_type='image' so dense scanned content still appears
- processor.process_document and precedent_library.ingest_precedent
  gated by flag — non-fatal on multimodal failure
- scripts/multimodal_backfill.py — idempotent per-case CLI to embed
  existing documents without re-extracting text

Validated locally on a 5-page response brief: render 0.31s, embed 8.32s,
hybrid merge surfaces image rows correctly. Production rollout starts
with flag=false (no behavior change), then per-case A/B.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-03 19:24:52 +00:00
26c3fddf41 feat(retrieval): add voyage rerank-2 cross-encoder stage (feature flag)
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Stage B of voyage-upgrades-plan rewritten: instead of context-3 (which
4 POCs showed inconsistent improvement), add a cross-encoder rerank
layer on top of voyage-3. Default off (VOYAGE_RERANK_ENABLED=false).

POC validation (785-doc corpus, 12 queries, claude-haiku-4-5 judge):
- mean@3 +4.5% (4.306 → 4.500)
- practical-category queries +11.6% (3.78 → 4.22)
- latency +702ms per query
- no schema change, no re-embed, no double storage

Plumbing:
- config: VOYAGE_RERANK_ENABLED / _MODEL / _FETCH_K env vars
- embeddings.voyage_rerank() wraps voyageai client.rerank
- services/rerank.py: maybe_rerank() helper — fetches FETCH_K candidates
  via the bi-encoder then reranks to top-K. Fail-open if Voyage rerank is
  unavailable.
- tools/search.py: search_decisions, search_case_documents,
  find_similar_cases all wrapped
- services/precedent_library.search_library wrapped

Smoke-tested locally with flag on/off — produces expected behaviour and
latency profile. Ready for production rollout via Coolify env flip after
deploy.

POCs (kept under scripts/ for reference):
- voyage_context3_poc{_long}.py — context-3 evaluation (rejected)
- voyage_multimodal_poc.py — multimodal-3 (stage C, deferred)
- voyage_rerank_judge_poc.py — single-case rerank benchmark
- voyage_rerank_corpus_poc.py — full-corpus rerank validation

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-03 18:43:41 +00:00
da0a385d9c docs: register reembed_voyage.py in SCRIPTS.md
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2026-05-03 16:44:07 +00:00
cb0b4b6a8b ops: switch embeddings to voyage-3 + plan for context-3 + multimodal-3.5
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Phase A — voyage-3 migration (executed):

- VOYAGE_MODEL=voyage-3 set in Coolify (legal-ai app) and ~/.env
- scripts/reembed_voyage.py: re-embeds document_chunks (6157),
  case_law_embeddings (9), precedent_chunks (385), and halachot (400)
  using the new model. paragraph_embeddings was empty. 6951 rows
  re-embedded in 93s, ~75 rows/sec.
- Same 1024 dim → no schema change needed.

Why voyage-3 over voyage-law-2: benchmark on 3 Hebrew legal queries
with real passages from the corpus gave voyage-3 perfect ordering on
3/3 tests AND the largest separation (+0.483 vs voyage-law-2's
+0.238). voyage-4 family had bigger separation but missed top-1 on
the hardest test.

Phase B (voyage-context-3) and Phase C (voyage-multimodal-3.5 for
scanned + appraiser docs) are designed in docs/voyage-upgrades-plan.md
but deferred — to be picked up in a fresh conversation. The plan
includes:
- Phase B: contextualized embeddings refactor (~49% recall lift on
  legal docs per Anthropic's research). Same dim, but ingestion
  pipeline must pass full doc context per chunk.
- Phase C: page-level image embeddings via voyage-multimodal-3.5,
  stored in a parallel *_image_embeddings table. Hybrid text+image
  search. Targets appraiser report tables and scanned PDFs where
  current OCR loses layout.

After this commit: MCP server needs a /mcp reconnect to pick up the
new VOYAGE_MODEL env, and the legal-ai container will pick it up on
its next redeploy.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-03 16:43:48 +00:00
28f49defff LLM session: async, 30min timeout, semantic chunking + parallel
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The claude_session bridge had two structural defects that made any
non-trivial document extraction unreliable:

  1. subprocess.run() blocks the asyncio event loop in the MCP server
     for the full duration of every LLM call (60-180s typical).
  2. The 120-second timeout was below the cold-cache cost of any
     document over ~12K Hebrew characters. Three back-to-back timeouts
     on case 8174-24 dropped 43 appellant claims on the floor.

Phase 1 of the remediation plan — keeps claude_session as the engine
(no Anthropic API switch) and restructures around it:

claude_session.py
  • query / query_json are now async — asyncio.create_subprocess_exec
    instead of subprocess.run, so MCP server can serve other coroutines
    while a call is in flight.
  • DEFAULT_TIMEOUT 120 → 1800 (30 min). High enough that no realistic
    document hits it; bounded so a runaway never zombifies forever.
  • LONG_TIMEOUT 300 → 3600 for opus block writing on full case context.
  • TimeoutError now actually kills the subprocess (asyncio.wait_for
    cancellation alone leaves the child running).

claims_extractor.py
  • _split_by_sections: chunks at numbered sections / Hebrew letter
    headings / "פרק" markers / markdown ##, falls back to paragraph
    breaks, then to hard splits. Targets 12K chars per chunk — small
    enough that each chunk reliably finishes inside the timeout.
  • _extract_chunk: per-chunk retry (1 attempt by default) with
    structured logging on failure. Failed chunks no longer crash the
    overall extraction; they're skipped with a partial-result warning.
  • extract_claims_with_ai now runs chunks in parallel via
    asyncio.gather bounded by a semaphore (CHUNK_CONCURRENCY=3).
    For a 25K-char appeal: was sequential 150-300s, now ~70-90s.

Updated all 9 callers (claims, appraiser facts, block writer, qa
validator, brainstorm, learning loop, style analyzer × 3) to await
the now-async API.

The one-shot scripts/extract_claims_8174.py used to recover 43
appellant claims on case 8174-24 has been moved to .archive/ — phase 1
makes it obsolete. SCRIPTS.md updated.

Phase 2 (background-task wrapper around LLM-bound MCP tools, persistent
llm_tasks table, SSE progress) is the structural follow-up — separate PR.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-30 14:21:35 +00:00
726498126d Add Track Changes architecture for draft revisions (CMP + CMPA)
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Fixes critical bug in 1033-25: user-uploaded עריכה-*.docx files were
orphaned on disk while exports kept rebuilding from stale DB blocks.

New architecture:
- User-uploaded DOCX becomes the source of truth (cases.active_draft_path)
- System edits via XML surgery with real Word <w:ins>/<w:del> revisions
- User can Accept/Reject each change from within Word

Components:
- docx_reviser.py: XML surgery for Track Changes (15 tests)
- docx_retrofit.py: retroactive bookmark injection with Hebrew marker
  detection + heading heuristic (9 tests)
- docx_exporter.py: emits bookmarks around each of the 12 blocks
- 3 new MCP tools: apply_user_edit, list_bookmarks, revise_draft
- 4 new/updated endpoints: upload (auto-registers active draft),
  /exports/revise, /exports/bookmarks, /exports/{filename}/retrofit,
  /active-draft
- DB migration: cases.active_draft_path column
- UI: correct banner using real v-numbers, "מקור האמת" badge,
  detailed upload toast with bookmarks_added/missing_blocks
- agents: legal-exporter (3 export modes), legal-ceo (stage G for
  revision handling), legal-writer (revision mode)

Multi-tenancy:
- Works for both CMP (1xxx cases) and CMPA (8xxx/9xxx cases)
- New revise-draft skill added to both companies
- deploy-track-changes.sh syncs skills CMP ↔ CMPA
- retrofit_case.py: one-off retrofit of existing files

Tests: 34 passing (15 reviser + 9 retrofit + 4 exporter bookmarks + 6 e2e)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-16 18:49:30 +00:00
28daff58be Pre-existing agent updates + analysis DOCX export
Updates accumulated from prior sessions:
- HEARTBEAT: company-based filtering (CMP/CMPA) rules
- legal-qa, legal-researcher: routine updates
- analysis_docx_exporter: new service for analysis DOCX export
- compose page: "הורד כ-DOCX" button for analysis
- decision_template.docx: template for exporter

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-16 18:49:10 +00:00
5c9a5d702a Clean up scripts/: archive 17, delete 5, add SCRIPTS.md registry
Active scripts (5): auto-sync-cases.sh, backup-db.sh, restore-db.sh,
notify.py, bidi_table.py

Archived (17): one-time migration/seeding scripts whose functionality
is now in MCP server or web API. Moved to scripts/.archive/

Deleted (5): zero-value scripts (duplicates, hardcoded single-case,
debug scripts)

Added scripts/SCRIPTS.md — registry of all scripts with purpose,
status, and what superseded them. CLAUDE.md updated with rule:
any script change requires SCRIPTS.md update.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-14 16:30:19 +00:00
891f20dbb9 Clean up legacy references: update CLAUDE.md, remove dead import script
- CLAUDE.md: clarify vault was deleted, knowledge is in docs/+training/
- Remove import-final-decisions.py (migration completed, all decisions in DB)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-14 16:16:35 +00:00
ad3c2b7117 Remove duplicate paperclip-assets — source of truth is paperclip-config repo
Assets live in ezer-mishpati/paperclip-config (cloned at ~/.paperclip).
Deploy via: ~/.paperclip/hebrew/apply-hebrew.sh

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-14 15:57:18 +00:00
11c73a7c60 CEO: add email notifications, subtask parentId, and Paperclip UI assets
- CEO agent now sends email via notify.py when awaiting human response
- CEO creates child issues (parentId) instead of flat disconnected issues
- Fix notify.py email address to chaim+paperclip@marcus-law.co.il
- Move Paperclip UI assets (RTL CSS + Hebrew JS) into repo under scripts/
- Add deploy.sh script to push assets to live Paperclip instance
- Fix comment box positioning: newest comment on top, input below it

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-14 15:55:55 +00:00
82ba4663ba Fix case repo sync + auto-create Gitea repos + add sync indicator
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- auto-sync-cases.sh: fix broken directory scan (was looking for
  status subdirs that don't exist), fix env var word-splitting bug,
  add safe.directory handling and error logging
- cases.py: auto-create Gitea repo on case_create, fix
  documents/original → documents/originals naming mismatch
- app.py: add GET /api/cases/{case_number}/git-status endpoint
- web-ui: add SyncIndicator component in case header showing
  sync status (synced/pending/no remote) with last commit time
- pyproject.toml: add httpx dependency
- CLAUDE.md: update Paperclip wakeup API docs
- settings page: switch tag input from Select to free-text with datalist

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-14 15:28:16 +00:00
858333b386 Add style report dashboard — Dafna's style portrait
Visual dashboard at #/style-report with 4 sections:
- Hero: 24 decisions, char counts, subject donut, timeline
- Anatomy: average section-length breakdown (intro → ruling → conclusion)
- Signature Phrases Wall: pattern cards with real corpus frequencies, filter
  chips by type, click → modal with examples
- Contribution: per-decision "new vs confirmed" patterns, growth curve SVG

Backend:
- /api/training/style-report endpoint computes all 4 sections in one call
- Headlines in Hebrew are computed server-side from real data
- Backfill script for style_patterns.frequency using _strip_nikud +
  pattern-variant extraction (templates with [placeholders], / alternatives,
  ellipsis all handled)

Real findings from the 24-decision corpus:
- דיון משפטי = 49% of avg decision (the focus)
- 23/24 use "לפנינו ערר" opening formula
- 21/24 use "ניתנה פה אחד" closing
- After 7 decisions we already learned 85% of her style patterns

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-11 11:34:37 +00:00
32f18de049 Add training corpus UI with Nevo proofreading pipeline
- New proofreader service strips Nevo editorial additions (front matter,
  postamble, page headers, watermarks, inline codes) from DOCX/PDF/MD
- PDF pages use Google Vision OCR for clean Hebrew RTL extraction
- New training page at #/training with drag-and-drop upload, automatic
  metadata extraction (decision number, date, categories), reviewable
  preview, and style pattern report grouped by type
- API endpoints: /api/training/{analyze,upload,corpus,patterns,
  analyze-style,analyze-style/status}
- Fix claude_session.query to pipe prompt via stdin, avoiding ARG_MAX
  overflow when analyzing 900K+ char corpus
- CLI scripts for batch proofreading and corpus upload

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-11 11:04:58 +00:00
3f759d3610 Improve document processing pipeline and agent workflows
- Add delete_document_chunks for reprocessing, save extracted text to disk
- Expand case directory structure (original/extracted/proofread/backup)
- Update classifier patterns (תגובה, הודעת עמדה)
- Fix proofreader agent paths for new directory layout
- Update HEARTBEAT to notify on every task completion
- Improve bidi_table with LRE/PDF directional embedding
- Add Paperclip project verification and auto-close setup issue
- Add auto-sync-cases.sh for Gitea synchronization

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-09 16:45:49 +00:00
22e819363e Flatten cases directory structure and unify paths
- Remove cases/new|in-progress|completed subdivision (status managed in DB)
- Rename documents/original → documents/originals (consistent plural)
- Move exports from global data/exports/ into cases/{num}/exports/
- Add documents/research/ for case law and analysis files
- Update all agents, scripts, config, web API endpoints, and DB paths

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-09 14:33:27 +00:00
e1d2e18ea8 Add email notifications: agents send mail when human action needed
New: scripts/notify.py — sends via SMTP (notify@marcus-law.co.ilpaperclip+chaim@marcus-law.co.il)
Updated: HEARTBEAT.md — agents must send email when waiting for human decision

Triggers: outcome choice, direction approval, QA failures, review ready.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-07 17:07:43 +00:00
911c797eb2 Reorganize: skills/ directory + move memory to docs/
skill-legal-decision/ → skills/decision/
skill-legal-assistant/ → skills/assistant/
skill-legal-docx/ → skills/docx/
memory/*.md → docs/

Also removed: TASKS.md (use TaskMaster), classifier.py (replaced by local_classifier.py)
Updated all references in CLAUDE.md, scripts, PRDs, docs.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-04 14:27:07 +00:00
d5ccf03e4c Add docs, scripts, skills, commands, and taskmaster config to repo
Includes:
- docs/: architecture, block-schema, migration-plan, product-specification
- scripts/: bidi_table, decompose-decisions, extract-claims, seed-knowledge, etc.
- skill-legal-decision/: SKILL.md + references + block-schema
- skill-legal-assistant/: SKILL.md
- skill-legal-docx/: SKILL.md + references
- .claude/commands/: bidi-table skill
- .taskmaster/: task config + PRDs
- .gitignore: exclude legacy/, kiryat-yearim/, node_modules/, memory/

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-04 14:19:17 +00:00
d9e5ef0f46 Add full decision writing pipeline: classify, extract, brainstorm, write, QA, export
New services (11 files):
- classifier.py: auto doc-type classification + party identification (Claude Haiku)
- claims_extractor.py: claim extraction from pleadings (Claude Sonnet + regex)
- references_extractor.py: plan/case-law/legislation detection (regex)
- brainstorm.py: direction generation with 2-3 options (Claude Sonnet)
- block_writer.py: 12-block decision writer (template + Claude Sonnet/Opus)
- docx_exporter.py: DOCX export with David font, RTL, headings
- qa_validator.py: 6 QA checks with export blocking on critical failure
- learning_loop.py: draft vs final comparison + lesson extraction
- metrics.py: KPIs dashboard per case and global
- audit.py: action audit log
- cli.py: standalone CLI with 11 commands

Updated pipeline: extract → classify → chunk → embed → store → extract_references
New MCP tools: 29 total (was 16)
New DB tables: audit_log, decisions CRUD, claims CRUD
Config: Infisical support, external service allowlist

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-03 10:21:47 +00:00