diff --git a/src/interface.jl b/src/interface.jl
index 3addc40..8a66e04 100755
--- a/src/interface.jl
+++ b/src/interface.jl
@@ -3,7 +3,7 @@ module interface
 
 export agentReact, agentReflex,
         addNewMessage, clearMessage, removeLatestMsg, conversation, directconversation, 
-        writeEvaluationGuideline, grading, analyze, selfReflext, actor_mistral_openorca2, 
+        writeEvaluationGuideline, grading, analyze, selfReflext, 
         formulateUserresponse, extractinfo, updateEnvState, chat_mistral_openorca
 
 using JSON3, DataStructures, Dates, UUIDs, HTTP
@@ -178,7 +178,7 @@ function planner_mistral_openorca(a::agentReflex)
   end
 
   # skip objective and plan because LLM is going to generate new plan
-  shorttermMemory = dictToString(a.memory[:shortterm], skiplist=["Objective:", "Plan 0:"])
+  shorttermMemory = dictToString(a.memory[:shortterm], skiplist=["Objective:", "Plan 1:"])
   
   assistant_plan_prompt =
     """
@@ -187,7 +187,8 @@ function planner_mistral_openorca(a::agentReflex)
     The required info you need for wine recommendation:
         - type of food: ask the user
         - occasion: ask the user
-        - user's personal taste of wine: ask the user
+        - type of wine (red, white, rose, sparkling, etc): ask the user
+        - user's personal taste of wine characteristic (sweetness, acidity, etc): ask the user
         - wine price range: ask the user
         - ambient temperature at the serving location: ask the user
         - wines we have in stock
@@ -255,7 +256,7 @@ end
 #   end
 
 #   # skip objective and plan because LLM is going to generate new plan
-#   shorttermMemory = dictToString(a.memory[:shortterm], skiplist=["Objective:", "Plan 0:"])
+#   shorttermMemory = dictToString(a.memory[:shortterm], skiplist=["Objective:", "Plan 1:"])
   
 #   assistant_plan_prompt =
 #     """
@@ -348,7 +349,7 @@ function updatePlan(a::agentReflex)
 
   result = sendReceivePrompt(a, prompt, max_tokens=512, temperature=0.1)
   @show updatedPlan = result
-  a.memory[:shortterm]["Plan 0:"] = result
+  a.memory[:shortterm]["Plan 1:"] = result
   
 end
 
@@ -428,9 +429,9 @@ function actor_mistral_openorca(a::agentReflex)
     response = splittext(response, ["Obs", "<|im_end|>"])
 
     if !occursin("Thought", response)
-      response = "Thought: " * response
+      response = "Thought $(a.step): " * response
     end
-
+    @show response_actor1 = response
     headerToDetect = ["Question:", "Plan:", "Thought:", 
                       "Act:", "Actinput:", "Obs:", "...", 
                       "Answer:", "Conclusion:", "Summary:"]
@@ -442,7 +443,7 @@ function actor_mistral_openorca(a::agentReflex)
     headers = detectCharacters(response, headerToDetect)
 
     println("")
-    @show response_actor = response
+    @show response_actor2 = response
 
     headerToDetect = ["Plan $(a.attempt):",
                       "Thought $(a.step):", 
@@ -465,14 +466,14 @@ function actor_mistral_openorca(a::agentReflex)
   toolinput = chunkedtext["Actinput $(a.step):"]
 
   # change trailing number to continue a.memory[:shortterm]
-  _latest_step = keys(a.memory[:shortterm])
-  _latest_step = [i for i in _latest_step]
-  _latest_step = _latest_step[end]
-  latest_step = parse(Int, _latest_step[end-2:end-1])
+  _latestStep = keys(a.memory[:shortterm])
+  _latestStep = [i for i in _latestStep]
+  _latestStep = _latestStep[end]
+  latestStep = parse(Int, _latestStep[end-2:end-1])
   headerToDetect = ["Question:", "Plan:", "Thought:", 
                       "Act:", "Actinput:", "Obs:", "...", 
                       "Answer:", "Conclusion:", "Summary:"]
-  nextstep = latest_step+1  # next step in short term memory
+  nextstep = latestStep+1  # next step in short term memory
   response = replaceHeaders(response, headerToDetect, nextstep)
   headerToDetect = ["Plan $(a.attempt):",
                       "Thought $nextstep:", 
@@ -535,12 +536,12 @@ function conversation(a::agentReflex, usermsg::String; attemptlimit::Int=3)
 
   # a.earlierConversation = conversationSummary(a)
   _ = addNewMessage(a, "user", usermsg)
-  isusetools = isUseTools(a)
+  isuseplan = isUsePlans(a)
   # newinfo = extractinfo(a, usermsg)
   # a.env = newinfo !== nothing ? updateEnvState(a, newinfo) : a.env
-  @show isusetools
+  @show isuseplan
 
-  if isusetools # use tools before responseing
+  if isuseplan # use plan before responding
     workstate, response = work(a)
   end
 
@@ -557,21 +558,6 @@ function conversation(a::agentReflex, usermsg::String; attemptlimit::Int=3)
   return response
 end
 
-""" Direct conversation is not an agent, messages does not pass through logic loop
-  but goes directly to LLM.
-  
-"""
-function directconversation(a::agentReflex, usermsg::String)
-  response = nothing
-
-  _ = addNewMessage(a, "user", usermsg)
-
-  response = chat_mistral_openorca(a)
-  response = removeTrailingCharacters(response)
-  _ = addNewMessage(a, "assistant", response)
-  return response
-end
-
 """
   Continuously run llm functions except when llm is getting Answer: or chatbox.
   There are many work() depend on thinking mode.
@@ -582,10 +568,10 @@ function work(a::agentReflex)
   
   # user answering LLM -> Obs
   if length(a.memory[:shortterm]) != 0
-    latest_step = dictLatestStep(a.memory[:shortterm])
-    if haskey(a.memory[:shortterm], "Act $latest_step:")
-      if occursin("chatbox", a.memory[:shortterm]["Act $latest_step:"])
-        a.memory[:shortterm]["Obs $latest_step:"] = a.messages[end][:content]
+    latestStep = shortMemLatestStep(a.memory[:shortterm])
+    if haskey(a.memory[:shortterm], "Act $latestStep:")
+      if occursin("chatbox", a.memory[:shortterm]["Act $latestStep:"])
+        a.memory[:shortterm]["Obs $latestStep:"] = a.messages[end][:content]
       end
     end
   end
@@ -601,7 +587,7 @@ function work(a::agentReflex)
       plan = planner_mistral_openorca(a)
       a.memory[:shortterm]["Plan $(a.attempt):"] = plan
       a.memory[:log]["Plan $(a.attempt):"] = plan
-      a.step = 0  # reset because new plan is created
+      a.step = 1  # reset because new plan is created
 
       println("")
       @show plan
@@ -706,30 +692,15 @@ function actor(a::agentReflex)
   totalsteps = checkTotalStepInPlan(a)
 
   while true  # Actor loop
-
-    # decide whether to repeat step or do the next step
-    decision = "Yes"  # yes because a.step start at 0
-    if a.step != 0
-      decision, reason = goNogo(a)
-    end
-
-    if decision == "Yes"   # in case there is a cancel, go straight to evaluation
-      a.step += 1
-    elseif decision == "No" # repeat the latest step
-      a.memory[:shortterm] = removeHeaders(a.memory[:shortterm], a.step, ["Plan"])
-      a.memory[:log] = removeHeaders(a.memory[:log], a.step, ["Plan"])
-      println("repeating step $(a.step)")
-    else
-      error("undefined condition decision = $decision $(@__LINE__)")
-    end
     @show a.step
-    #WORKING checkStepCompletion
-    iscomplete = checkStepCompletion(a::agentReflex)
-    # if iscomplete
-    
-    if a.step < totalsteps   # the last step of the plan is responding, let work() do this part
+    # check whether the current step is completed
+    iscomplete, reason = checkStepCompletion(a)
+    @show stepcompletecheck = iscomplete
 
+    if !iscomplete  # not yet done
+      # work
       toolname, toolinput = actor_mistral_openorca(a)
+      println("")
       @show toolname
       @show toolinput
 
@@ -747,11 +718,35 @@ function actor(a::agentReflex)
         a.memory[:shortterm]["Obs $(a.step):"] = toolresult
         a.memory[:log]["Obs $(a.step):"] = toolresult
       end
-    else
-      actorState = "all steps done"
-      msgToUser = nothing
-      break
+    else  # already done
+      a.step +=1
+      # if not add to memory yet. Add
+
+      # step +1
+
+      #TODO may be let LLM call finalResponse()
+      # if a.step > totalsteps   # the last step of the plan is responding, let work() do this part
+      #   actorState = "all steps done"
+      #   msgToUser = nothing
+      #   break
+      # end
+      
     end
+
+
+
+
+
+    # elseif decision == "No" # repeat the latest step
+    #   a.memory[:shortterm] = removeHeaders(a.memory[:shortterm], a.step, ["Plan"])
+    #   a.memory[:log] = removeHeaders(a.memory[:log], a.step, ["Plan"])
+    #   println("repeating step $(a.step)")
+    # else
+    #   error("undefined condition decision = $decision $(@__LINE__)")
+    # end
+
+
+    
   end
 
   return actorState, msgToUser
@@ -1144,14 +1139,14 @@ julia> shorttermMemory = OrderedDict{String, Any}(
   "Actinput 2:" => "  amd graphics card latest\n",
   "Obs 2:"      => "No info available for your search query.")
 
-julia> decision = goNogo(agent)
+julia> decision = checkStepCompletion(agent)
 "Yes"
 ```
 """
-function goNogo(a)
+function checkStepCompletion(a)
   # stimulus = a.memory[:shortterm]["user:"]
   work = dictToString(a.memory[:shortterm])
-
+  #WORKING
   prompt =
   """
     <|system|>
@@ -1165,76 +1160,91 @@ function goNogo(a)
     Your earlier work:
     $work
     
+
     Your job is to check whether step $(a.step) of your work is completed according to the plan.
     So for instance the following:
-    
-      step 2 of the plan: Ask user about the occasion type. But you can't find any relevant info of occasion type in your work.
-      assistant: Step 2 isn't done yet. {No}
-      step 5 of the plan: Ask user if they have any preference for the style of wine. And you found relevant info in your work such as the user like full-bodied wine.
-      assistant: Step 5 is done. {Yes}
+      Step 2 of the plan: Ask user about their preferred taste in white wine.
+      Your interpretation of step 2 of the plan: My understanding of this step is that I need info about their preferred taste in white wine e.g. dryness, sweetness and etc. But I can't find any relevant info that the user tell me their preferred taste in white wine according to Obs.
+      assistant: Thus, step 2 isn't done yet. Answer: {Not done}
+
+      Step 5 of the plan: Ask user if they have any preferred type of wine. 
+      Your interpretation of step 5 of the plan: My understanding of this step is that I need info about user preferred wine type. And I found relevant info such as the user like full-bodied wine according to Obs.
+      assistant: Step 5 is done. Answer: {done}
+    Let's think step by step.
     </s|>
     <|assistant|>
   """
 
-  response = sendReceivePrompt(a, prompt)
-  @show goNogo_response = response
+  response = sendReceivePrompt(a, prompt, max_tokens=512)
+  @show checkStepCompletion_response = response
 
   decision = nothing
-  reason = nothing
-  if occursin("Yes", response)
-    decision = "Yes"
-  elseif occursin("No", response)
-    decision = "No"
+  if occursin("Not done", response)
+    decision = false
+  elseif occursin("done", response)
+    decision = true
   else
     error("undefied condition, decision $decision $(@__LINE__)")
   end
 
-  startInd = findfirst(decision, response)[end] +2
-
-  if occursin(":", response[startInd:end]) # check for ":" after decision cha
-    startInd2 = findnext(":", response, startInd)[end]+1
-    reason = response[startInd2:end]
-  else
-    reason = response[startInd:end]
-  end
-
-  return decision, reason
+  return decision, response
 end
+# function checkStepCompletion(a)
+#   # stimulus = a.memory[:shortterm]["user:"]
+#   work = dictToString(a.memory[:shortterm])
 
+#   prompt =
+#   """
+#     <|system|>
+#     Symbol meaning:
+#     Plan: a plan
+#     Thought: your thought
+#     Act: the action you took
+#     Actinput: the input to the action
+#     Obs: the result of the action
 
-
-function checkStepCompletion(a::agentReflex)
-  result = false
-  #WORKING I need current step of the plan
-  plan = "Plan $(a.attempt):"
-  plan = a.memory[:shortterm][plan]
-
-  prompt =
-  """
-    <|system|>
-    Symbol meaning:
-    Plan: a plan
-    Thought: your thought
-    Act: the action you took
-    Actinput: the input to the action
-    Obs: the result of the action
-
-    Your plan:
-    $plan
+#     Your earlier work:
+#     $work
     
-    What is step $(a.step) of the plan?
-    <|/s|>
-    <|assistant|>
 
-  """
+#     Your job is to check whether step $(a.step) of your work is completed according to the plan.
+#     So for instance the following:
+#       step 2 of the plan: Ask user about the occasion type. But you can't find any relevant info about occasion type in your work.
+#       assistant: Step 2 isn't done yet. Answer {Not done}
+#       step 5 of the plan: Ask user if they have any preference for the style of wine. And you found relevant info in your work such as the user like full-bodied wine.
+#       assistant: Step 5 is done. Answer {done}
+#     Let's think step by step.
+#     </s|>
+#     <|assistant|>
+#   """
 
-  response = sendReceivePrompt(a, prompt)
-  
-  response = split(response, "<|im_end|>")[1] 
+#   response = sendReceivePrompt(a, prompt)
+#   @show checkStepCompletion_response = response
 
-  
-  
-  return result
+#   decision = nothing
+#   if occursin("Not done", response)
+#     decision = false
+#   elseif occursin("done", response)
+#     decision = true
+#   else
+#     error("undefied condition, decision $decision $(@__LINE__)")
+#   end
+
+#   return decision, response
+# end
+
+""" Direct conversation is not an agent, messages does not pass through logic loop
+  but goes directly to LLM.
+"""
+function directconversation(a::agentReflex, usermsg::String)
+  response = nothing
+
+  _ = addNewMessage(a, "user", usermsg)
+
+  response = chat_mistral_openorca(a)
+  response = removeTrailingCharacters(response)
+  _ = addNewMessage(a, "assistant", response)
+  return response
 end
 
 
@@ -1285,10 +1295,6 @@ end
 
 
 
-
-
-
-
 
 
 
diff --git a/src/type.jl b/src/type.jl
index d42eeb8..92ad69c 100644
--- a/src/type.jl
+++ b/src/type.jl
@@ -94,8 +94,8 @@ julia> agent = ChatAgent.agentReflex(
   tools::Union{Dict, Nothing} = nothing 
   newplan::Bool = false # if true, new plan will be generated
   attemptlimit::Int = 5 # thinking round limit
-  attempt::Int = 0 # attempted number
-  step::Int = 0 # step number
+  attempt::Int = 1 # attempted number
+  step::Int = 1 # step number
   env::AbstractString = "N/A"
   thinkingFormat::Union{Dict, Nothing} = nothing
   memory::Dict = Dict(
@@ -167,7 +167,7 @@ function agentReflex(
     :actor=> 
       """
       Use the following format:
-      Thought: you should always think about what to do according to step {step} of the plan (pay attention to correct numeral calculation and commonsense).
+      Thought: you should always think about what to do to achieve step {step} of the plan (pay attention to correct numeral calculation and commonsense).
       Act: the action to take that align with your thought, should be one of [{toolnames}]
       Actinput: your input to the action you chose (pay attention to the tool's input)
       Obs: the result of the action
diff --git a/src/utils.jl b/src/utils.jl
index 429a1fc..ea4547b 100644
--- a/src/utils.jl
+++ b/src/utils.jl
@@ -2,9 +2,9 @@ module utils
 
 export makeSummary, sendReceivePrompt, chunktext, extractStepFromPlan, checkTotalStepInPlan,
         detectCharacters, findDetectedCharacter, extract_number, toolNameBeingCalled,
-        isUseTools, conversationSummary, checkReasonableness, replaceHeaders,
+        isUsePlans, conversationSummary, checkReasonableness, replaceHeaders,
         addShortMem!, splittext, dictToString, removeHeaders, keepOnlyKeys, experience,
-        messagesToString, messagesToString_nomark, removeTrailingCharacters, dictLatestStep
+        messagesToString, messagesToString_nomark, removeTrailingCharacters, shortMemLatestStep
 
 using UUIDs, Dates, DataStructures
 using CommUtils, GeneralUtils
@@ -375,7 +375,7 @@ Return:
   1. true/false # is LLM going to use tools
   2. objective  # what LLM going to do
 """
-function isUseTools(a::agentReflex)
+function isUsePlans(a::agentReflex)
   toollines = ""
   for (toolname, v) in a.tools
     if toolname ∉ ["chatbox"] # LLM will always use chatbox
@@ -405,26 +405,26 @@ function isUseTools(a::agentReflex)
   """
   
   # if LLM mentions any tools, use Plan/Thought/Act loop
-  isusetool = false
+  isuseplan = false
   response = sendReceivePrompt(a, prompt, temperature=0.2, max_tokens=64)
   response = split(response, "<|assistant|>")[1] 
   response = split(response, "<|user|>")[1]
-  @show response
+
   for (toolname, v) in a.tools
     if occursin("Yes", String(response))
-      isusetool = true
+      isuseplan = true
       break
     end
   end
 
   if length(a.memory[:shortterm]) != 0
-    isusetool = true
+    isuseplan = true
   end
-  return isusetool
+  return isuseplan
 end
 
 
-# function isUseTools(a::agentReflex)
+# function isUsePlans(a::agentReflex)
 #   toollines = ""
 #   for (toolname, v) in a.tools
 #     if toolname ∉ ["chatbox"] # LLM will always use chatbox
@@ -451,21 +451,21 @@ end
 #   """
   
 #   # if LLM mentions any tools, use Plan/Thought/Act loop
-#   isusetool = false
+#   isuseplan = false
 #   response = sendReceivePrompt(a, prompt, temperature=0.0)
 #   response = split(response, "<|im_end|>")[1]
 #   for (toolname, v) in a.tools
 #     if occursin(toolname, String(response))
-#       isusetool = true
+#       isuseplan = true
 #       break
 #     end
 #   end
 
 #   if length(a.memory[:shortterm]) != 0
-#     isusetool = true
+#     isuseplan = true
 #   end
 
-#   return isusetool
+#   return isuseplan
 # end
 
 
@@ -1016,8 +1016,7 @@ function experience(dict::T) where {T<:AbstractDict}
 end
 
 
-function dictLatestStep(dict::T) where {T<:AbstractDict}
-  @show dict
+function shortMemLatestStep(dict::T) where {T<:AbstractDict}
   _latest_step = keys(dict)
   _latest_step = [i for i in _latest_step]
   _latest_step = _latest_step[end]