diff --git a/app/prompt/visualization.py b/app/prompt/visualization.py
index 8e4fecc53..3f4e67379 100644
--- a/app/prompt/visualization.py
+++ b/app/prompt/visualization.py
@@ -1,4 +1,4 @@
-SYSTEM_PROMPT = """You are an AI agent designed to data analysis / visualization task. You have various tools at your disposal that you can call upon to efficiently complete complex requests.
+SYSTEM_PROMPT = """You are an AI agent designed for data analysis / visualization task. You have various tools at your disposal that you can call upon to efficiently complete complex requests.
 # Note:
 1. The workspace directory is: {directory}; Read / write file in workspace
 2. Generate analysis conclusion report in the end"""
diff --git a/app/tool/chart_visualization/python_execute.py b/app/tool/chart_visualization/python_execute.py
index 8a7b5bb4d..9dda4637b 100644
--- a/app/tool/chart_visualization/python_execute.py
+++ b/app/tool/chart_visualization/python_execute.py
@@ -22,9 +22,9 @@ class NormalPythonExecute(PythonExecute):
 # Note
 1. The code should generate a comprehensive text-based report containing dataset overview, column details, basic statistics, derived metrics, timeseries comparisons, outliers, and key insights.
 2. Use print() for all outputs so the analysis (including sections like 'Dataset Overview' or 'Preprocessing Results') is clearly visible and save it also
-3. Save any report / processed files / each analysis result in worksapce directory: {directory}
+3. Save any report / processed files / each analysis result in workspace directory: {directory}
 4. Data reports need to be content-rich, including your overall analysis process and corresponding data visualization.
-5. You can invode this tool step-by-step to do data analysis from summary to in-depth with data report saved also""".format(
+5. You can invoke this tool step-by-step to do data analysis from summary to in-depth with data report saved also""".format(
                     directory=config.workspace_root
                 ),
             },