diff --git a/investigator-runtime/src/detectives/case_writer.ts b/investigator-runtime/src/detectives/case_writer.ts
index 04ae51d..3389c0a 100644
--- a/investigator-runtime/src/detectives/case_writer.ts
+++ b/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 { hybridSearch, type SearchHit } from "../lib/search";
+import { fetchDocChunks, hybridSearch, type SearchHit } from "../lib/search";
 import { writeCaseReport } from "../tools/write_case_report";
 
 const HERE = path.dirname(fileURLToPath(import.meta.url));
@@ -286,18 +286,27 @@ export async function runCaseWriter(task: CaseWriterTask): Promise<
 
   const filter = `%${topic.toLowerCase()}%`;
 
-  // 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: task.doc_id ?? null,
-    top_k: 18,
-    recall_k: 80,
-    max_dense_dist: 0.55,
-  }).catch(() => [] as SearchHit[]);
+  // 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({
+        query: topic, lang,
+        doc_id: null,
+        top_k: 18,
+        recall_k: 80,
+        max_dense_dist: 0.55,
+      }).catch(() => [] as SearchHit[]);
 
   // Pull artefacts SEQUENTIALLY. The investigator role has rolconnlimit=4 and
   // pool.max=4; Promise.all of 5 queries × max_parallel=2 jobs would demand
diff --git a/investigator-runtime/src/lib/search.ts b/investigator-runtime/src/lib/search.ts
index 8f15ae5..15e664c 100644
--- a/investigator-runtime/src/lib/search.ts
+++ b/investigator-runtime/src/lib/search.ts
@@ -67,6 +67,35 @@ export interface HybridSearchOpts {
   max_dense_dist?: number;
 }
 
+/**
+ * Fetch a single document's own chunks in reading order — 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 pull substantive `is_searchable`
+ * chunks ordered by `order_global` so the document tells its own story in
+ * sequence.
+ */
+export async function fetchDocChunks(
+  doc_id: string,
+  _lang: "pt" | "en" = "pt",
+  limit = 24,
+): Promise<SearchHit[]> {
+  if (!doc_id) return [];
+  return await query<SearchHit>(
+    `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 public.chunks
+      WHERE doc_id = $1
+        AND is_searchable = TRUE
+        AND length(COALESCE(content_en,'') || COALESCE(content_pt,'')) > 40
+      ORDER BY order_global ASC NULLS LAST, page ASC, order_in_page ASC
+      LIMIT $2`,
+    [doc_id, limit],
+  );
+}
+
 export async function hybridSearch(opts: HybridSearchOpts): Promise<SearchHit[]> {
   const {
     query: q,