investigator-runtime/src/detectives/case_writer.ts

@@ -16,7 +16,7 @@ import { audit } from "../lib/audit";
 import { callClaude } from "../lib/claude";
 import { env } from "../lib/env";
 import { query } from "../lib/pg";
-import { fetchDocChunks, hybridSearch, type SearchHit } from "../lib/search";
+import { hybridSearch, type SearchHit } from "../lib/search";
 import { writeCaseReport } from "../tools/write_case_report";
 
 const HERE = path.dirname(fileURLToPath(import.meta.url));
@@ -286,27 +286,18 @@ export async function runCaseWriter(task: CaseWriterTask): Promise<
 
   const filter = `%${topic.toLowerCase()}%`;
 
-  // Grounding pass — assemble the scenes the narrator weaves from.
-  //
-  // For a per-document case file (doc_id set) we pull THIS document's own
-  // chunks in reading order. A hybridSearch keyed on the document's
-  // auto-derived topic ("Fbi Photo B20", "Doc 59 214434 …") returns zero
-  // hits even though the doc has dozens of embedded chunks — the dense gate
-  // rejects them all because the garbage topic has no semantic neighbours.
-  // That single bug skipped 61 of 75 batch documents on its own.
-  //
-  // For a corpus-wide topic report (no doc_id) the semantic search is
-  // exactly right — we want the strongest chunks across all documents.
-  const docIdFilter = task.doc_id ?? null;
-  const scenes = docIdFilter
-    ? await fetchDocChunks(docIdFilter, lang, 24).catch(() => [] as SearchHit[])
-    : await hybridSearch({
+  // Grounding pass — retrieve top scenes from the corpus via hybrid_search.
+  // This is what gives the narrator real verbatim material to weave. Without
+  // this, the case-writer only sees pre-digested artefacts (which is what
+  // produced the academic prose in v1).
+  const scenes = await hybridSearch({
     query: topic, lang,
-        doc_id: null,
+    doc_id: task.doc_id ?? null,
     top_k: 18,
     recall_k: 80,
     max_dense_dist: 0.55,
   }).catch(() => [] as SearchHit[]);
+  const docIdFilter = task.doc_id ?? null;
 
   // Pull artefacts SEQUENTIALLY. The investigator role has rolconnlimit=4 and
   // pool.max=4; Promise.all of 5 queries × max_parallel=2 jobs would demand

investigator-runtime/src/lib/search.ts

@@ -67,50 +67,6 @@ export interface HybridSearchOpts {
   max_dense_dist?: number;
 }
 
-/**
- * Fetch a single document's own chunks — no semantic gating. For a
- * per-document case file the narrator wants THIS document's substance, not
- * a corpus search; a hybridSearch keyed on the document's (often garbage)
- * auto-derived topic returns zero hits even though the doc has dozens of
- * embedded chunks.
- *
- * We pick the most substantive chunks (by content length, deprioritising
- * pure redaction boxes) and THEN present them in reading order. Naively
- * taking the first N by `order_global` starves the narrator on long files:
- * the opening chunks of a 1000-chunk FBI dossier are cover pages, routing
- * slips, classification stamps and redaction boxes — administrative front
- * matter, not narrative. The substance sits deeper in the file, so a
- * length-ranked pick surfaces it regardless of position, while the final
- * reading-order sort keeps the story coherent.
- */
-export async function fetchDocChunks(
-  doc_id: string,
-  _lang: "pt" | "en" = "pt",
-  limit = 24,
-): Promise<SearchHit[]> {
-  if (!doc_id) return [];
-  return await query<SearchHit>(
-    `WITH ranked AS (
-       SELECT chunk_pk, doc_id, chunk_id, page, type, bbox,
-              content_en, content_pt, classification,
-              order_global, order_in_page,
-              length(COALESCE(content_en,'') || COALESCE(content_pt,'')) AS richness
-         FROM public.chunks
-        WHERE doc_id = $1
-          AND is_searchable = TRUE
-          AND length(COALESCE(content_en,'') || COALESCE(content_pt,'')) > 40
-        ORDER BY (type = 'redaction') ASC, richness DESC
-        LIMIT $2
-     )
-     SELECT chunk_pk, doc_id, chunk_id, page, type, bbox,
-            content_en, content_pt, classification,
-            1.0::float8 AS score, NULL::int AS bm25_rank, NULL::int AS dense_rank
-       FROM ranked
-      ORDER BY order_global ASC NULLS LAST, page ASC, order_in_page ASC`,
-    [doc_id, limit],
-  );
-}
-
 export async function hybridSearch(opts: HybridSearchOpts): Promise<SearchHit[]> {
   const {
     query: q,

web/app/c/[slug]/page.tsx

@@ -81,14 +81,7 @@ export async function generateMetadata(
   const c = await loadCase(slug);
   if (!c) return { title: "Case file not found" };
 
-  // Prefer the narrator's body H1 (the magazine headline) over the generic
-  // auto-derived frontmatter topic ("Dow Uap D44 …"). This is what search
-  // engines and link cards show, so it must be the human title. Two H1s when
-  // present: EN then PT-BR; fall back across them, then to frontmatter.
-  const h1s = [...c.body.matchAll(/^#\s+(.+)$/gm)].map((m) => m[1].trim());
-  const title = locale === "pt-br"
-    ? (h1s[1] ?? h1s[0] ?? c.fm.topic_pt_br ?? c.fm.topic ?? slug)
-    : (h1s[0] ?? c.fm.topic ?? slug);
+  const title = locale === "pt-br" ? (c.fm.topic_pt_br ?? c.fm.topic ?? slug) : (c.fm.topic ?? slug);
   const desc = pickLead(c.body, locale).slice(0, 200);
   const canonical = `${SITE_URL}/c/${slug}`;
   // OG image — use the case's editorial illustration when present. WhatsApp,