diff --git a/pandaserver/daemons/scripts/task_evaluator.py b/pandaserver/daemons/scripts/task_evaluator.py
index 4bf2c516..0d1cb99e 100644
--- a/pandaserver/daemons/scripts/task_evaluator.py
+++ b/pandaserver/daemons/scripts/task_evaluator.py
@@ -10,6 +10,7 @@
 from pandacommon.pandalogger import logger_utils
 from pandacommon.pandalogger.PandaLogger import PandaLogger
 from pandacommon.pandautils.thread_utils import GenericThread
+
 from pandaserver.config import panda_config
 from pandaserver.daemons.scripts.metric_collector import MetricsDB
 
@@ -204,6 +205,15 @@ def analy_task_eval(self):
             "AND ds.masterID IS NULL "
             "GROUP BY ds.jediTaskID "
         )
+        sql_get_task_n_jobs = (
+            "SELECT COUNT(*) FROM ( "
+            "SELECT DISTINCT c.PandaID "
+            "FROM ATLAS_PANDA.JEDI_Datasets ds, ATLAS_PANDA.JEDI_Dataset_Contents c "
+            "WHERE c.jediTaskID=ds.jediTaskID AND c.datasetID=ds.datasetID "
+            "AND ds.jediTaskID=:taskID AND ds.masterID IS NULL "
+            "AND ds.type IN ('input', 'pseudo_input') "
+            ") "
+        )
         try:
             # initialize
             # tmp_site_dict = dict()
@@ -235,8 +245,11 @@ def analy_task_eval(self):
                 n_files_total = 0
                 n_files_finished = 0
                 n_files_failed = 0
+                n_files_remaining = 0
                 pct_finished = 0
                 pct_failed = 0
+                n_jobs = 0
+                n_jobs_remaining = 0
                 # get dataset info of each task
                 varMap = {":taskID": taskID}
                 dsinfo_list = self.tbuf.querySQL(sql_get_task_dsinfo, varMap)
@@ -248,27 +261,34 @@ def analy_task_eval(self):
                     }
                     for tup in dsinfo_list
                 }
+                # get n jobs of each task
+                tmp_res = self.tbuf.querySQL(sql_get_task_n_jobs, varMap)
+                for obj in tmp_res:
+                    (n_jobs,) = obj
+                    dsinfo_dict[taskID]["nJobs"] = n_jobs
+                    break
                 # get task proceeding progress
                 ds_info = dsinfo_dict.get(taskID)
                 if ds_info is not None:
                     n_files_total = ds_info.get("nFiles", 0)
                     n_files_finished = ds_info.get("nFilesFinished", 0)
                     n_files_failed = ds_info.get("nFilesFailed", 0)
+                    n_files_remaining = max(n_files_total - n_files_finished - n_files_failed, 0)
+                    n_jobs = ds_info.get("nJobs", 0)
                     if n_files_total > 0:
                         pct_finished = n_files_finished * 100 / n_files_total
                         pct_failed = n_files_failed * 100 / n_files_total
+                        n_jobs_remaining = int(n_jobs * n_files_remaining / n_files_total)
                 # classify
                 if gshare == "Express Analysis":
                     # Express Analysis tasks always in class S
                     task_class = 2
                 else:
                     # parameters
-                    progress_to_boost_A = self.tbuf.getConfigValue("analy_eval", "PROGRESS_TO_BOOST_A")
-                    if progress_to_boost_A is None:
-                        progress_to_boost_A = 90
-                    progress_to_boost_B = self.tbuf.getConfigValue("analy_eval", "PROGRESS_TO_BOOST_B")
-                    if progress_to_boost_B is None:
-                        progress_to_boost_B = 95
+                    progress_to_boost_A = self.tbuf.getConfigValue("analy_eval", "PROGRESS_TO_BOOST_A", default=90)
+                    progress_to_boost_B = self.tbuf.getConfigValue("analy_eval", "PROGRESS_TO_BOOST_B", default=95)
+                    max_rem_jobs_to_boost_A = self.tbuf.getConfigValue("analy_eval", "MAX_REM_JOBS_TO_BOOST_A", default=500)
+                    max_rem_jobs_to_boost_B = self.tbuf.getConfigValue("analy_eval", "MAX_REM_JOBS_TO_BOOST_B", default=200)
                     # check usage of the user
                     usage_dict = ue_dict.get(user)
                     if usage_dict is None:
@@ -279,10 +299,10 @@ def analy_task_eval(self):
                         else:
                             task_class = 0
                     # boost for nearly done tasks
-                    if task_class == 1 and pct_finished >= progress_to_boost_A:
+                    if task_class == 1 and pct_finished >= progress_to_boost_A and n_jobs_remaining > 0 and n_jobs_remaining <= max_rem_jobs_to_boost_A:
                         # almost done A-tasks, to boost
                         task_class = 2
-                    elif task_class == 0 and pct_finished >= progress_to_boost_B:
+                    elif task_class == 0 and pct_finished >= progress_to_boost_B and n_jobs_remaining > 0 and n_jobs_remaining <= max_rem_jobs_to_boost_B:
                         # almost done B-tasks, to boost
                         task_class = 2
                 # fill in task class
diff --git a/pandaserver/taskbuffer/TaskBuffer.py b/pandaserver/taskbuffer/TaskBuffer.py
index c4737fce..aed02d9f 100755
--- a/pandaserver/taskbuffer/TaskBuffer.py
+++ b/pandaserver/taskbuffer/TaskBuffer.py
@@ -610,11 +610,13 @@ def lockJobsForReassign(
         return res
 
     # get a DB configuration value
-    def getConfigValue(self, component, key, app="pandaserver", vo=None):
+    def getConfigValue(self, component, key, app="pandaserver", vo=None, default=None):
         # get DB proxy
         proxy = self.proxyPool.getProxy()
         # exec
         res = proxy.getConfigValue(component, key, app, vo)
+        if res is None and default is not None:
+            res = default
         # release DB proxy
         self.proxyPool.putProxy(proxy)