feat(agent): align the document tools with the harness-trained shape — ls, read(path), grep(pattern, path?)

app/rag/llm.py

@@ -74,12 +74,12 @@ class ToolCallPiece:
     ``id`` is the model's tool_call id (synthesized as ``call_<index>``
     when the wire never carried one), ``name`` is the function name
     (whatever the caller's ``tools`` list names — for the agent loop,
-    ``list_documents`` / ``read_document``), and ``arguments`` is the
+    ``ls`` / ``read`` / ``grep``, phase 70), and ``arguments`` is the
     parsed JSON object (``{}`` when the model sent none).
     """
 
     id: str  # the model's tool_call id; synthesized "call_<index>" when absent
-    name: str  # "list_documents" | "read_document" (whatever AGENT_TOOLS names)
+    name: str  # "ls" | "read" | "grep" (whatever AGENT_TOOLS names, phase 70)
     arguments: dict[str, Any]
 
 
@@ -124,7 +124,7 @@ def _materialize_tool_calls(
     Malformed ``arguments`` JSON raises :class:`LLMError` — a silently
     dropped tool call would corrupt the agent loop (fail-loud house
     style). Empty/``null`` arguments become ``{}`` (a no-parameter call
-    such as ``list_documents``).
+    such as an unscoped ``ls``).
     """
     pieces: list[ToolCallPiece] = []
     for index in sorted(slots):