Simplify planning stage by executing tasks directly. Make research notes available to more agents/tools.

ra_aid/agent_utils.py

@@ -404,6 +404,7 @@ def run_task_implementation_agent(
         related_files=related_files,
         key_facts=get_memory_value('key_facts'),
         key_snippets=get_memory_value('key_snippets'),
+        research_notes=get_memory_value('research_notes'),
         work_log=get_memory_value('work_log'),
         expert_section=EXPERT_PROMPT_SECTION_IMPLEMENTATION if expert_enabled else "",
         human_section=HUMAN_PROMPT_SECTION_IMPLEMENTATION if _global_memory.get('config', {}).get('hil', False) else "",

ra_aid/prompts.py

@@ -470,9 +470,6 @@ Guidelines:
 
     After finalizing the overall approach:
         Use emit_plan to store the high-level implementation plan.
-        For each sub-task, use emit_task to store a step-by-step description.
-            The description should be only as detailed as warranted by the complexity of the request.
-        You may use delete_tasks or swap_task_order to adjust the task list/order as you plan.
 
     Once you are absolutely sure you are completed planning, you may begin to call request_task_implementation one-by-one for each task to implement the plan.
     If you have any doubt about the correctness or thoroughness of the plan, consult the expert (if expert is available) for verification.
@@ -506,6 +503,9 @@ Key Snippets:
 Relevant Files:
 {related_files}
 
+Research Notes:
+{research_notes}
+
 Work done so far:
 <work log>
 {work_log}

ra_aid/tool_configs.py

@@ -96,10 +96,7 @@ def get_planning_tools(expert_enabled: bool = True, web_research_enabled: bool =
     
     # Add planning-specific tools
     planning_tools = [
-        delete_tasks,
         emit_plan,
-        emit_task,
-        swap_task_order,
         request_task_implementation,
         plan_implementation_completed
     ]
@@ -144,7 +141,8 @@ def get_web_research_tools(expert_enabled: bool = True) -> list:
     """
     tools = [
         web_search_tavily,
-        emit_research_notes
+        emit_research_notes,
+        task_completed
     ]
 
     if expert_enabled:

ra_aid/tools/agent.py

@@ -111,12 +111,10 @@ def request_web_research(query: str) -> ResearchResult:
     
     success = True
     reason = None
-    web_research_notes = []
     
     try:
         # Run web research agent
         from ..agent_utils import run_web_research_agent
-        original_research_notes = _global_memory.get('research_notes', [])
         result = run_web_research_agent(
             query,
             model,
@@ -125,7 +123,6 @@ def request_web_research(query: str) -> ResearchResult:
             console_message=query,
             config=config
         )
-        web_research_notes = _global_memory.get('research_notes', [])
     except AgentInterrupt:
         print()
         response = ask_human.invoke({"question": "Why did you interrupt me?"})
@@ -138,7 +135,6 @@ def request_web_research(query: str) -> ResearchResult:
         success = False
         reason = f"error: {str(e)}"
     finally:
-        _global_memory['research_notes'] = original_research_notes
         # Get completion message if available
         completion_message = _global_memory.get('completion_message', 'Task was completed successfully.' if success else None)
         
@@ -155,8 +151,8 @@ def request_web_research(query: str) -> ResearchResult:
     return {
         "work_log": work_log,
         "completion_message": completion_message,
-        "web_research_notes": web_research_notes,
         "key_snippets": get_memory_value("key_snippets"),
+        "research_notes": get_memory_value("research_notes"),
         "success": success,
         "reason": reason
     }

ra_aid/tools/expert.py

@@ -132,6 +132,7 @@ def ask_expert(question: str) -> str:
     related_contents = read_related_files(file_paths)
     key_snippets = get_memory_value('key_snippets')
     key_facts = get_memory_value('key_facts')
+    research_notes = get_memory_value('research_notes')
     
     # Build display query (just question)
     display_query = "# Question\n" + question
@@ -153,6 +154,9 @@ def ask_expert(question: str) -> str:
     if related_contents:
         query_parts.extend(['# Related Files', related_contents])
         
+    if related_contents:
+        query_parts.extend(['# Research Notes', research_notes])
+        
     if key_snippets and len(key_snippets) > 0:
         query_parts.extend(['# Key Snippets', key_snippets])