Chaim
21ff52aff9
The radar's query was built from dozens of raw claims (procedural-heavy noise), so matches were thematic but imprecise and gave no reason WHY a lead is relevant. Now: - Prefer the analyst's distilled legal_arguments (argument_title + legal_topic — one crisp CREAC issue per row) over raw claims. - Search EACH issue separately and MERGE, so every lead is attributed to the case issue(s) it answers (`matched_issues`) — the chair sees "this ruling is for your 'זכות עמידה' issue", not just a blended score. - Fall back to the raw-claims blended query pre-aggregation; `source` reports the path. - Shared `_radar_enrich` helper (gap status + action + matched_issues), bounded to 25 issues to cap the per-issue fan-out. Validated: 8124-09-24 (32 args → per-issue) surfaces betterment rulings each tagged to its issue (היעדר השבחה / זהות הנישום / סעיף 7(ב)); 1044-03-26 (0 args) falls back to claims unchanged. No tool/endpoint signature change (new fields pass through the dict). Invariants: G2 (reuses the one digest search + arg accessor), INV-DIG1 (radar only). No schema change. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>