Using my local crime data, can you give me the average age of suspects who committed robbery between 2016 and 2021, and identify where this type of crime occurred most frequently during that same time frame?
['Based on the local crime data, the average age of suspects who committed robbery between 2016 and 2021 is 32.60 years.', 'Based on the local crime data, the most frequent location where robbery occurred between 2016 and 2021 is Bank.']
["github_create_or_update_file","github_create_repository","memory_read_graph","memory_search_nodes","memory_open_nodes","calculator_calculate","github_push_files","github_create_issue","cli-mcp-server_run_command","cli-mcp-server_show_security_rules","mcp-code-executor_execute_code","arxiv_search_papers","fetch_fetch"]
[{"content":"First, I will use `cli-mcp-server_show_security_rules` to retrieve the allowed commands and the working directory.","role":"assistant","tool_calls":[{"function":{"arguments":"{}","name":"cli-mcp-server_show_security_rules"},"id":"2e9b94a2-cb87-49ca-b743-3cce52354dab","type":"function"}]},{"content":[{"text":"Security Configuration:\n==================\nWorking Directory: /data\n\nAllowed Commands:\n----------------\ncat, find, ls\n\nAllowed Flags:\n-------------\n\n\nSecurity Limits:\n---------------\nMax Command Length: 1024 characters\nCommand Timeout: 30 seconds\n","type":"text"}],"role":"tool","tool_call_id":"2e9b94a2-cb87-49ca-b743-3cce52354dab"},{"content":"With the identified commands and the directory \"/data\", I will now use `cli-mcp-server_run_command` to list the files in this directory and find the one related to crime data.","role":"assistant","tool_calls":[{"function":{"arguments":"{\n  \"command\": \"ls /data\"\n}","name":"cli-mcp-server_run_command"},"id":"447c675f-f786-48d9-9fbf-c7c7900839c9","type":"function"}]},{"content":[{"text":"Barber Shop.csv\nCoinbaseTradeHistory.csv\nCovid 19 impacts on hospitals.csv\nCrime_records.csv\nPet Care 2023 Weekly Financials.csv\nTop Movies.csv\nfantasy sports.csv\nfood and beverage consumption.csv\nrepos\n","type":"text"},{"text":"\nCommand completed with return code: 0","type":"text"}],"role":"tool","tool_call_id":"447c675f-f786-48d9-9fbf-c7c7900839c9"},{"content":"I identified the relevant file \"Crime_records.csv\". Now I will use `cli-mcp-server_run_command` to get its information and understand how this data file is structured.","role":"assistant","tool_calls":[{"function":{"arguments":"{\n  \"command\": \"cat Crime_records.csv\"\n}","name":"cli-mcp-server_run_command"},"id":"95694d5d-1ca6-49b0-aa6a-d736a25ae2a6","type":"function"}]},{"content":[{"text":"Crime_ID,Date_Reported,Crime_Type,Location,Arrest_Made,Suspect_Age,Suspect_Gender,Victim_Age,Victim_Gender,Crime_Severity\nCRIME679,2014-05-10,Theft,Shopping Mall,Yes,27,Male,35,Female,Moderate\nCRIME680,2014-06-22,Assault,Park,No,19,Female,45,Male,Severe\nCRIME681,2014-07-15,Burglary,Residential Area,Yes,35,Male,42,Female,High\nCRIME682,2014-08-03,Robbery,Convenience Store,Yes,40,Male,28,Male,High\nCRIME683,2014-09-18,Vandalism,Public Library,No,17,Male,55,Female,Low\nCRIME684,2014-10-05,Fraud,Online,No,30,Female,40,Female,Moderate\nCRIME685,2014-11-12,Drug Trafficking,Street,Yes,50,Male,29,Male,Severe\nCRIME686,2014-12-09,Kidnapping,Residential Area,No,23,Male,18,Female,High\nCRIME687,2015-01-20,Cybercrime,Financial Institution,Yes,28,Female,55,Male,Moderate\nCRIME688,2016-09-02,Assault,Bar,Yes,29,Male,32,Female,Moderate\nCRIME689,2016-10-15,Fraud,Telephone,No,45,Female,55,Female,Moderate\nCRIME690,2016-11-09,Robbery,Bank,Yes,35,Male,40,Male,High\nCRIME691,2016-12-18,Vandalism,School,No,18,Female,60,Male,Low\nCRIME692,2017-01-07,Cybercrime,Social Media,Yes,22,Male,28,Female,Moderate\nCRIME693,2017-02-03,Kidnapping,Parking Lot,No,40,Female,25,Female,High\nCRIME694,2017-03-20,Theft,Gas Station,Yes,30,Male,35,Male,Moderate\nCRIME695,2017-04-11,Drug Trafficking,Warehouse,Yes,38,Female,45,Male,Severe\nCRIME696,2017-05-29,Arson,Residential Area,No,27,Male,50,Female,High\nCRIME697,2017-06-14,Shoplifting,Department Store,Yes,20,Female,30,Male,Low\nCRIME698,2017-07-22,Assault,Restaurant,Yes,32,Male,40,Female,Moderate\nCRIME699,2017-08-05,Burglary,Office Building,Yes,28,Female,45,Male,High\nCRIME700,2017-09-18,Fraud,Online,No,50,Male,60,Female,Moderate\nCRIME701,2017-10-09,Vandalism,Public Park,No,21,Male,65,Male,Low\nCRIME702,2017-11-24,Cybercrime,Financial Institution,Yes,35,Female,55,Male,Moderate\nCRIME703,2017-12-15,Robbery,Convenience Store,Yes,25,Male,30,Female,High\nCRIME704,2018-01-28,Kidnapping,Shopping Mall,No,42,Male,20,Female,High\nCRIME705,2018-02-11,Theft,Supermarket,Yes,33,Female,38,Female,Moderate\nCRIME706,2018-03-09,Drug Trafficking,Street,Yes,48,Male,25,Male,Severe\nCRIME707,2018-04-17,Arson,Warehouse,No,30,Male,35,Female,High\nCRIME708,2018-05-03,Assault,Park,Yes,28,Female,30,Male,Moderate\nCRIME709,2018-06-28,Burglary,Residential Area,Yes,37,Male,42,Female,High\nCRIME710,2018-07-11,Fraud,Telephone,No,55,Female,60,Female,Moderate\nCRIME711,2018-08-19,Vandalism,School,No,24,Male,65,Male,Low\nCRIME712,2018-09-05,Cybercrime,Social Media,Yes,29,Male,55,Female,Moderate\nCRIME713,2018-10-10,Kidnapping,Parking Lot,No,45,Female,30,Female,High\nCRIME714,2018-11-27,Theft,Gas Station,Yes,31,Male,35,Male,Moderate\nCRIME715,2018-12-14,Drug Trafficking,Warehouse,Yes,40,Female,45,Male,Severe\nCRIME716,2019-01-30,Arson,Residential Area,No,29,Male,50,Female,High\nCRIME718,2019-03-20,Assault,Bar,Yes,34,Male,37,Female,Moderate\nCRIME719,2019-04-09,Fraud,Telephone,No,48,Female,58,Female,Moderate\nCRIME720,2019-05-14,Robbery,Bank,Yes,37,Male,42,Male,High\nCRIME721,2019-06-28,Vandalism,School,No,19,Female,62,Male,Low\nCRIME722,2019-07-11,Cybercrime,Social Media,Yes,25,Male,30,Female,Moderate\nCRIME723,2019-08-25,Kidnapping,Parking Lot,No,42,Female,27,Female,High\nCRIME724,2019-09-18,Theft,Gas Station,Yes,32,Male,38,Male,Moderate\nCRIME725,2019-10-30,Drug Trafficking,Warehouse,Yes,40,Female,48,Male,Severe\nCRIME726,2019-11-12,Arson,Residential Area,No,32,Male,55,Female,High\nCRIME727,2019-12-29,Shoplifting,Department Store,Yes,23,Female,35,Male,Low\nCRIME728,2020-01-15,Assault,Restaurant,Yes,37,Male,45,Female,Moderate\nCRIME729,2020-02-09,Burglary,Office Building,Yes,31,Female,48,Male,High\nCRIME730,2020-03-18,Fraud,Online,No,52,Male,62,Female,Moderate\nCRIME731,2020-04-07,Vandalism,Public Park,No,22,Male,67,Male,Low\nCRIME732,2020-05-22,Cybercrime,Financial Institution,Yes,37,Female,58,Male,Moderate\nCRIME733,2020-06-14,Robbery,Convenience Store,Yes,27,Male,32,Female,High\nCRIME734,2020-07-30,Kidnapping,Shopping Mall,No,45,Male,22,Female,High\nCRIME735,2020-08-17,Theft,Supermarket,Yes,35,Female,40,Female,Moderate\nCRIME736,2020-09-28,Drug Trafficking,Street,Yes,50,Male,27,Male,Severe\nCRIME737,2020-11-05,Assault,Park,Yes,30,Female,32,Male,Moderate\nCRIME738,2020-12-19,Burglary,Residential Area,Yes,28,Male,45,Female,High\nCRIME739,2021-01-02,Fraud,Telephone,No,60,Female,65,Female,Moderate\nCRIME740,2021-02-14,Robbery,Bank,Yes,39,Male,44,Male,High\nCRIME741,2021-03-28,Vandalism,School,No,20,Female,68,Male,Low\nCRIME742,2021-04-10,Cybercrime,Social Media,Yes,27,Male,32,Female,Moderate\nCRIME743,2021-05-15,Kidnapping,Parking Lot,No,48,Female,25,Female,High\nCRIME744,2021-06-29,Theft,Gas Station,Yes,34,Male,40,Male,Moderate\nCRIME745,2021-07-12,Drug Trafficking,Warehouse,Yes,42,Female,50,Male,Severe\nCRIME746,2021-08-27,Arson,Residential Area,No,33,Male,55,Female,High\nCRIME747,2021-09-10,Shoplifting,Department Store,Yes,25,Female,38,Male,Low\nCRIME748,2021-10-25,Assault,Restaurant,Yes,38,Male,47,Female,Moderate\nCRIME749,2021-11-07,Fraud,Online,No,55,Male,65,Female,Moderate\nCRIME750,2021-12-18,Vandalism,Public Park,No,24,Male,70,Male,Low","type":"text"},{"text":"\nCommand completed with return code: 0","type":"text"}],"role":"tool","tool_call_id":"95694d5d-1ca6-49b0-aa6a-d736a25ae2a6"},{"content":"After analyzing the data file, I will now use `mcp-code-executor_execute_code` to compute the average suspect age and the most frequent location of robberies between 2016 and 2021.","role":"assistant","tool_calls":[{"function":{"arguments":"{\n  \"code\": \"import pandas as pd; df = pd.read_csv('/data/Crime_records.csv'); f = df[(df['Crime_Type'] == 'Robbery') & (df['Date_Reported'].between('2016-01-01', '2021-12-31'))]; print(f\\\"Average suspect age: {f['Suspect_Age'].mean():.2f} years | Most frequent location: {f['Location'].mode()[0]}\\\")\"\n}","name":"mcp-code-executor_execute_code"},"id":"08774558-8716-46f9-9b36-70f6108bee24","type":"function"}]},{"content":[{"isError":false,"text":"{\"status\":\"success\",\"output\":\"Average suspect age: 32.60 years | Most frequent location: Bank\\n\",\"file_path\":\"/data/repos/mcp_code_executor_workspace/code_f52f1e9a.py\",\"generated_filename\":\"code_f52f1e9a.py\"}","type":"text"}],"role":"tool","tool_call_id":"08774558-8716-46f9-9b36-70f6108bee24"}]