feat(aggregation): Implement sub-agent summarization pass

src/summarize.py

@@ -153,9 +153,9 @@ _SUMMARISERS: dict[str, Callable[[Path, str], str]] = {
 
 def summarise_file(path: Path, content: str) -> str:
  """
-    Return a compact markdown summary string for a single file.
-    `content` is the already-read file text (or an error string).
-    """
+ Return a compact markdown summary string for a single file.
+ `content` is the already-read file text (or an error string).
+ """
  content_hash = get_file_hash(content)
  cached = _summary_cache.get_summary(str(path), content_hash)
  if cached:
@@ -164,7 +164,25 @@ def summarise_file(path: Path, content: str) -> str:
  suffix = path.suffix.lower() if hasattr(path, "suffix") else ""
  fn = _SUMMARISERS.get(suffix, _summarise_generic)
  try:
-  summary = fn(path, content)
+  heuristic_outline = fn(path, content)
+  
+  # Smart AI Summarization
+  is_code = suffix in [".py", ".ps1", ".js", ".ts", ".cpp", ".c", ".h", ".cs", ".go", ".rs", ".lua"]
+  try:
+   from src import ai_client
+   smart_summary = ai_client.run_subagent_summarization(
+    file_path=str(path),
+    content=content[:10000], # Cap content to 10k chars for summarization
+    is_code=is_code,
+    outline=heuristic_outline
+   )
+   if smart_summary and not smart_summary.startswith("ERROR:"):
+    summary = f"{smart_summary}\n\n**Outline:**\n{heuristic_outline}"
+   else:
+    summary = heuristic_outline
+  except Exception:
+   summary = heuristic_outline # Fallback
+  
   _summary_cache.set_summary(str(path), content_hash, summary)
   return summary
  except Exception as e: