fix(agent): enforce guide-only tool policy (#3088)

routes/chat_helpers.py

@@ -277,11 +277,16 @@ def extract_preset(chat_handler, preset_id) -> PresetInfo:
 async def preprocess(
     chat_handler, message, att_ids, sess,
     auto_opened_docs: Optional[list] = None,
+    allow_tool_preprocessing: bool = True,
 ) -> PreprocessedMessage:
     """Run chat_handler.preprocess_message and wrap the result."""
     enhanced, user_content, text_ctx, yt_transcripts, att_meta = (
         await chat_handler.preprocess_message(
-            message, att_ids, sess, auto_opened_docs=auto_opened_docs
+            message,
+            att_ids,
+            sess,
+            auto_opened_docs=auto_opened_docs,
+            allow_tool_preprocessing=allow_tool_preprocessing,
         )
     )
     return PreprocessedMessage(
@@ -450,6 +455,7 @@ async def build_chat_context(
     webhook_manager=None,
     use_enhanced_message: bool = False,
     agent_mode: bool = False,
+    allow_tool_preprocessing: bool = True,
 ) -> ChatContext:
     """Build the full context (preface + messages) for an LLM call.
 
@@ -467,6 +473,7 @@ async def build_chat_context(
     preprocessed = await preprocess(
         chat_handler, message, att_ids or [], sess,
         auto_opened_docs=auto_opened_docs,
+        allow_tool_preprocessing=allow_tool_preprocessing,
     )
 
     # Add user message to history
@@ -485,6 +492,9 @@ async def build_chat_context(
     # Skills injection respects its own enable toggle (mirrors memory_enabled).
     # When off, the "Available skills" index is not added to the prompt.
     skills_enabled = not incognito and uprefs.get("skills_enabled", True)
+    if not allow_tool_preprocessing:
+        mem_enabled = False
+        skills_enabled = False
     logger.debug(
         "Memory enabled=%s for user=%s (incognito=%s, no_memory=%s, pref=%s)",
         mem_enabled, user, incognito, no_memory, uprefs.get("memory_enabled", "NOT_SET"),
@@ -492,11 +502,11 @@ async def build_chat_context(
 
     # Use RAG?
     use_rag_val = (str(use_rag).lower() != "false") if use_rag is not None else True
-    if incognito:
+    if incognito or not allow_tool_preprocessing:
         use_rag_val = False
 
     # If pre-fetched search context was provided (compare mode), skip live web search
-    skip_web = bool(search_context)
+    skip_web = bool(search_context) or not allow_tool_preprocessing
 
     # Build context preface
     # The stream path uses enhanced_message (with CoT/preprocessing applied),
@@ -523,7 +533,7 @@ async def build_chat_context(
     used_memories = getattr(chat_processor, '_last_used_memories', [])
 
     # Inject pre-fetched search context (compare mode)
-    if search_context:
+    if search_context and allow_tool_preprocessing:
         preface.append(untrusted_context_message("prefetched search context", search_context))
 
     # YouTube transcripts
@@ -855,12 +865,13 @@ def run_post_response_tasks(
     skills_manager=None,
     owner: str = None,
     extract_skills: bool = True,
+    allow_background_extraction: bool = True,
 ):
     """Fire background tasks after a completed response: memory extraction, webhooks, auto-name, skill extraction."""
     # Memory extraction — only every 4th message pair to avoid excess LLM calls
     _msg_count = len(sess.history) if hasattr(sess, 'history') else 0
     _should_extract = (_msg_count >= 4) and (_msg_count % 4 == 0)
-    if not incognito and not compare_mode and _should_extract and uprefs.get("auto_memory", True):
+    if allow_background_extraction and not incognito and not compare_mode and _should_extract and uprefs.get("auto_memory", True):
         from services.memory.memory_extractor import extract_and_store
         from src.task_endpoint import resolve_task_endpoint
         t_url, t_model, t_headers = resolve_task_endpoint(
@@ -887,6 +898,7 @@ def run_post_response_tasks(
     )
     if (
         extract_skills
+        and allow_background_extraction
         and auto_skills_enabled
         and not incognito
         and not compare_mode