provenance for successful LLM-assisted candidate generation

src/repo_registry/core/service.py

@@ -128,7 +128,11 @@ class RegistryService:
         )
         stored_chunks = self.store.list_content_chunks(repository_id, completed_run.id)
         try:
-            candidates = self._generate_candidates(repository, facts, stored_chunks)
+            candidates, candidate_source = self._generate_candidates(
+                repository,
+                facts,
+                stored_chunks,
+            )
         except Exception as exc:
             self.store.create_review_decision(
                 repository_id,
@@ -141,7 +145,15 @@ class RegistryService:
                 facts,
                 stored_chunks,
             )
+            candidate_source = "deterministic"
         self.store.replace_candidate_graph(repository_id, completed_run.id, candidates)
+        if candidate_source == "llm":
+            self.store.create_review_decision(
+                repository_id,
+                completed_run.id,
+                action="llm_extraction_used",
+                notes=f"Generated {len(candidates)} candidate ability draft(s).",
+            )
         return ScanSummary(
             analysis_run=completed_run,
             snapshot=snapshot,
@@ -157,8 +169,8 @@ class RegistryService:
         if self.llm_extractor is not None:
             extracted = self.llm_extractor.extract(repository, chunks)
             if extracted:
-                return self.llm_mapper.map(extracted, facts, chunks)
-        return self.candidate_generator.generate(repository, facts, chunks)
+                return self.llm_mapper.map(extracted, facts, chunks), "llm"
+        return self.candidate_generator.generate(repository, facts, chunks), "deterministic"
 
     def list_analysis_runs(self, repository_id: int) -> list[AnalysisRun]:
         return self.store.list_analysis_runs(repository_id)