Backend changes cherry-picked from ui-rewrite branch to enable
feedback API endpoints for the Next.js staging UI.
- chair_feedback DB table + API endpoints (GET/POST/PATCH)
- Content checklists by appeal subtype injected into block-yod prompt
- MCP tools for recording and listing chair feedback
- Corpus analysis documentation (24 decisions)
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
New self-contained table + MCP tools + FastAPI endpoints for letting
the chair attach external case-law quotes (quote + citation מראה מקום,
optional chair note, optional archived PDF) to either a specific
threshold_claim / issue or the case as a whole.
Data model
- case_precedents (SCHEMA_V5_SQL) — case_id, section_id NULL/
"threshold_N"/"issue_N", quote, citation (free-text), chair_note,
pdf_document_id FK to documents, denormalized practice_area for
cross-case library filtering.
- Deliberately NOT linked to the existing case_law table — that one
has UNIQUE(case_number) which would force parsing the free-text
citation into a structured key. A backfill pass into case_law is
a later follow-up once the UI stabilizes.
- db.py gains 4 helpers: create_case_precedent, list_case_precedents,
delete_case_precedent, search_precedent_library. The last uses
DISTINCT ON (citation) for the cross-case typeahead so each
precedent appears once even if reused across many cases.
MCP tools (legal_mcp/tools/precedents.py)
- precedent_attach, precedent_list, precedent_remove,
precedent_search_library — registered in server.py.
FastAPI (web/app.py)
- POST /api/cases/{n}/precedents — create, with PrecedentCreateRequest
- POST /api/cases/{n}/precedents/upload-pdf — one-shot PDF upload to
a dedicated documents/precedents/ subdirectory, creates a
documents row with doc_type="precedent_archive" and no text
extraction (archive only)
- GET /api/cases/{n}/precedents — list
- DELETE /api/precedents/{id} — uses path param since precedent_id
is a UUID (slash-safe, unlike case numbers)
- GET /api/precedents/search?q=...&practice_area=... — library
typeahead
Block-writer integration into _build_precedents_context is a deferred
follow-up — Phase 1 surfaces the feature in the compose UI only.
Plan: ~/.claude/plans/woolly-cooking-graham.md
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Wires a new case-deletion path across the three layers that needed it:
- db.delete_case(case_id) — single SQL DELETE; documents, chunks, and
qa_results cascade via existing schema FKs, audit_log nullifies.
- cases_tools.case_delete(case_number, remove_files=False) — MCP tool
wrapper. File tree on disk is kept by default (audit trail); pass
remove_files=True for a hard delete.
- DELETE /api/cases?case_number=... — FastAPI endpoint taking the case
number as a QUERY param rather than a path segment. Case numbers
like "1000/0426" can't be passed through a path parameter because
FastAPI routing decodes %2F before matching, so a query param is
the only shape that works for historical data.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Closes the loop so דפנה's positions (written inline in the UI and
saved to analysis-and-research.md) automatically become binding
direction for the legal-writer agent — no manual copy-paste,
no bypass.
Backend:
- research_md.extract_chair_directions(path) returns a compact dict
with status (missing/empty/partial/complete), filled_count,
empty_count, and a reduced list of threshold_claims + issues each
with {id, number, title, direction}. Designed to be directly usable
as direction_doc by the writer.
- New MCP tool: drafting.get_chair_directions(case_number) wraps the
helper, resolves the case research file path via config.find_case_dir,
returns formatted JSON.
- Registered in server.py as mcp__legal-ai__get_chair_directions.
legal-writer agent update:
- Adds get_chair_directions to the tools list.
- New mandatory "שלב 1ב" before any block writing: call
get_chair_directions, branch on status.
- missing → halt, report "legal-analyst לא רץ עדיין"
- empty → halt, instruct Dafna to fill positions via the UI URL
- partial → halt unless user confirms; write only filled sections
- complete → proceed
- New "שלב 1ג" constructs an internal direction_doc from the
received chair rulings before writing block י.
- Block י section expanded with 5 binding rules:
1. Open each discussion with Dafna's ruling as the thesis
2. Frame the reasoning in her style (use get_style_guide phrases)
3. Match her tone (decisive vs nuanced)
4. Must NOT contradict her position — if she disagreed with your
own inclination, her position rules
5. Use legal_questions from the analysis file as the analytical
structure (principle question first, concrete application second)
- New bullet section for block יא: summarize each chair ruling
briefly, state final outcome, close with the signed date formula.
Verified all four status paths (missing/empty/partial/complete) via
local test. Now Dafna's workflow is fully end-to-end: she reads the
analyst report in the UI, fills "עמדת ועדת הערר" in each card, hits
blur to auto-save, then triggers legal-writer — which picks up her
positions as direction without any file shuffle.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
New architecture: MCP provides context, Claude Code writes.
New functions:
- get_block_context(case_id, block_id) → returns full context package
(prompt, source docs, claims, direction, precedents, style guide)
WITHOUT calling Anthropic API
- save_block_content(case_id, block_id, content) → saves block to DB
New MCP tools: get_block_context, save_block_content
The old write_block (API-based) still works as fallback.
The new flow uses Claude Code's own model (Opus 4.6, 1M context)
which has no separate API billing.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- Add expected_outcome field to cases (rejection/partial/full/betterment_levy)
- New lessons.py module with golden ratios, templates, and drafting guidance per outcome type
- Style analyzer now uses Opus with full decision text (no truncation), with multi-pass fallback for large corpora
- Drafting tool provides outcome-specific templates, section guidance, and ratio comments
- Improved JSON extraction with bracket-matching fallback
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Ezer Mishpati - AI legal decision drafting system with:
- MCP server (FastMCP) with document processing pipeline
- Web upload interface (FastAPI) for file upload and classification
- pgvector-based semantic search
- Hebrew legal document chunking and embedding
