GPT-6.1 Sol (effort default (no reasoning-effort override) · thinking on) on Q1 budget-vs-actual variance table and CFO memo from a raw ledger (out-of-period lines, intercompany, legacy codes, reversals)

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{"type": "turn.started"}
{"type": "item.completed", "item": {"id": "item_0", "type": "agent_message", "text": "I\u2019ll calculate Q1 actuals using the exclusions and department mappings, then write and verify both files.\n"}}
{"type": "item.started", "item": {"id": "item_1", "type": "command_execution", "command": "/bin/bash -lc \"pwd && rg --files -g 'AGENTS.md' -g '*.csv' -g 'memo.md'\"", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_1", "type": "command_execution", "command": "/bin/bash -lc \"pwd && rg --files -g 'AGENTS.md' -g '*.csv' -g 'memo.md'\"", "aggregated_output": "/home/bob/usecase-runs/batch/out/gpt-6.1-sol/187_g08/work\nledger.csv\ndept_remap.csv\nbudget.csv\n", "exit_code": 0, "status": "completed"}}
{"type": "item.started", "item": {"id": "item_2", "type": "command_execution", "command": "/bin/bash -lc 'cat budget.csv dept_remap.csv ledger.csv'", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_2", "type": "command_execution", "command": "/bin/bash -lc 'cat budget.csv dept_remap.csv ledger.csv'", "aggregated_output": "dept_code,dept_name,q1_budget\r\nENG,Engineering,420000.00\r\nMKT,Marketing,180000.00\r\nSAL,Sales,260000.00\r\nSUP,Customer Support,95000.00\r\nFIN,Finance,70000.00\r\nHR,People Operations,60000.00\r\nOPS,Operations,140000.00\r\nLEG,Legal,45000.00\r\nlegacy_code,dept_code\r\nMKT-OLD,MKT\r\nCS,SUP\r\nPEOPLE,HR\r\ndate,account,dept_code,amount,memo\r\n2026-01-23,6400,HR,\"4,980.59\",payroll alloc\r\n2026-02-09,9100,FIN,\"5,833.33\",intercompany transfer\r\n2026-02-24,5200,SAL,\"16,434.75\",accrual\r\n2026-02-14,6100,LEG,1709.90,travel\r\n2026-01-21,6400,OPS,\"4,046.00\",vendor invoice\r\n2026-01-03,6100,MKT-OLD,15239.03,contractor\r\n2026-03-11,7000,ENG,\"18,562.36\",vendor invoice\r\n2026-03-03,5100,SAL,\"14,048.48\",payroll alloc\r\n2026-02-07,9100,MKT,15000.00,intercompany transfer\r\n2026-02-08,5200,PEOPLE,2783.14,vendor invoice\r\n2026-01-15,5200,ENG,20100.69,accrual\r\n2026-02-02,5100,SAL,\"14,805.59\",vendor invoice\r\n2026-02-18,5100,FIN,\"2,074.14\",accrual\r\n2026-03-06,6400,MKT,12449.55,travel\r\n2026-02-03,7000,ENG,\"28,705.05\",payroll alloc\r\n2026-03-04,7000,SAL,\"8,042.67\",contractor\r\n2026-02-07,9100,ENG,\"35,000.00\",intercompany transfer\r\n2026-03-22,6100,HR,\"3,021.43\",payroll alloc\r\n2026-01-27,5100,HR,\"5,090.46\",payroll alloc\r\n2026-03-08,6400,MKT-OLD,11819.34,accrual\r\n2026-02-03,6100,SUP,\"4,799.89\",travel\r\n2026-04-03,6100,SAL,\"10,400.00\",accrual\r\n2026-04-03,6100,LEG,\"1,800.00\",accrual\r\n2026-02-01,5200,MKT,\"8,445.17\",contractor\r\n2026-02-13,5200,MKT,\"39,396.77\",vendor invoice\r\n2026-03-13,6100,ENG,\"23,162.04\",accrual\r\n2026-03-22,6100,LEG,1662.89,vendor invoice\r\n2026-03-21,5100,ENG,\"21,929.74\",accrual\r\n2026-02-07,5100,OPS,6836.27,travel\r\n2026-04-01,6100,SUP,\"3,800.00\",accrual\r\n2026-01-21,6100,OPS,\"5,094.80\",software\r\n2026-04-03,6100,HR,2400.00,accrual\r\n2026-03-05,5200,SUP,9165.75,travel\r\n2026-03-07,5200,SUP,\"4,389.93\",payroll alloc\r\n2026-02-11,5100,FIN,2429.77,payroll alloc\r\n2026-03-17,6100,LEG,\"(1,570.50)\",software\r\n2026-02-20,7000,SAL,(8042.67),payroll alloc\r\n2026-02-27,7000,MKT,\"6,984.00\",software\r\n2026-02-01,5200,CS,3035.15,vendor invoice\r\n2026-03-17,5200,FIN,2801.63,software\r\n2026-02-19,6100,SUP,5050.35,accrual\r\n2026-02-21,5200,FIN,3322.32,vendor invoice\r\n2026-03-04,5200,LEG,\"1,772.49\",travel\r\n2026-03-04,6100,LEG,\"2,736.41\",contractor\r\n2026-02-04,6400,FIN,\"3,039.00\",travel\r\n2026-01-11,7000,LEG,\"2,069.64\",payroll alloc\r\n2026-01-25,7000,ENG,\"27,545.07\",travel\r\n2026-02-19,6400,LEG,\"2,919.85\",vendor invoice\r\n2026-03-07,6100,CS,5721.94,payroll alloc\r\n2026-01-07,5200,OPS,3874.53,payroll alloc\r\n2026-01-08,5200,SAL,\"14,610.19\",vendor invoice\r\n2025-12-31,6100,ENG,\"16,800.00\",accrual\r\n2026-02-13,6100,OPS,8244.56,travel\r\n2026-01-21,6100,HR,3701.07,vendor invoice\r\n2026-01-25,7000,FIN,\"2,770.38\",accrual\r\n2026-02-06,5200,LEG,\"1,695.24\",vendor invoice\r\n2026-02-15,5200,SUP,\"4,499.84\",vendor invoice\r\n2026-02-16,5100,MKT-OLD,\"12,158.82\",accrual\r\n2026-03-18,7000,ENG,25137.51,travel\r\n2026-01-28,6400,MKT,\"14,511.14\",payroll alloc\r\n2026-01-22,6100,FIN,\"2,632.11\",vendor invoice\r\n2026-03-24,5200,ENG,16035.39,contractor\r\n2026-02-26,9100,HR,5000.00,intercompany transfer\r\n2026-02-01,6100,FIN,\"(2,284.33)\",travel\r\n2026-03-02,6100,SUP,5065.32,payroll alloc\r\n2026-02-25,5200,LEG,2071.17,travel\r\n2026-02-07,5200,FIN,\"3,082.45\",accrual\r\n2025-12-30,6100,HR,2400.00,accrual\r\n2026-02-18,9100,OPS,\"11,666.67\",intercompany transfer\r\n2026-02-20,7000,MKT,\"15,890.94\",contractor\r\n2026-03-01,5100,SAL,\"13,281.14\",software\r\n2026-03-13,6400,CS,\"5,145.13\",travel\r\n2026-01-01,7000,FIN,\"2,565.73\",contractor\r\n2026-02-11,6400,LEG,2023.80,travel\r\n2026-03-01,7000,SAL,\"17,021.79\",payroll alloc\r\n2026-01-18,7000,HR,3126.15,travel\r\n2025-12-31,6100,OPS,5600.00,accrual\r\n2026-01-16,6100,LEG,\"1,714.09\",vendor invoice\r\n2026-02-10,7000,ENG,(14434.00),travel\r\n2026-02-09,5100,MKT-OLD,11131.79,vendor invoice\r\n2026-01-01,5100,HR,\"2,534.54\",payroll alloc\r\n2026-02-21,5100,SUP,(3540.33),vendor invoice\r\n2026-02-20,6400,FIN,3056.32,software\r\n2026-01-09,5100,FIN,4227.21,payroll alloc\r\n2026-01-20,5100,LEG,\"2,454.76\",software\r\n2026-03-20,7000,LEG,2165.87,vendor invoice\r\n2026-03-26,6100,OPS,\"6,661.37\",contractor\r\n2026-03-21,5100,SUP,\"5,471.38\",payroll alloc\r\n2026-03-03,7000,CS,3540.33,accrual\r\n2026-03-18,6100,ENG,\"14,434.00\",travel\r\n2026-03-07,7000,ENG,17009.58,contractor\r\n2026-03-13,5200,OPS,\"6,980.46\",travel\r\n2026-03-04,6100,FIN,4194.97,travel\r\n2026-02-27,7000,MKT-OLD,\"12,380.06\",software\r\n2026-03-08,6100,SUP,\"3,177.87\",software\r\n2026-01-05,5200,SAL,17375.02,software\r\n2026-03-25,5100,FIN,2945.76,accrual\r\n2026-01-16,5200,MKT,\"13,965.54\",travel\r\n2026-03-13,6100,LEG,1979.73,payroll alloc\r\n2026-03-09,5200,OPS,\"7,990.52\",payroll alloc\r\n2026-02-10,9100,SAL,21666.67,intercompany transfer\r\n2026-01-08,5200,SAL,\"8,903.84\",software\r\n2026-03-27,7000,OPS,\"12,101.84\",accrual\r\n2026-04-03,6100,ENG,16800.00,accrual\r\n2026-02-11,7000,CS,5803.84,payroll alloc\r\n2026-03-13,5100,LEG,\"3,715.11\",software\r\n2026-02-09,9100,LEG,3750.00,intercompany transfer\r\n2026-03-27,5200,FIN,\"2,095.27\",software\r\n2026-01-20,5200,PEOPLE,\"4,807.83\",accrual\r\n2026-03-11,7000,FIN,\"4,542.93\",contractor\r\n2026-04-01,6100,MKT,7200.00,accrual\r\n2026-02-23,7000,SAL,14834.45,vendor invoice\r\n2026-02-23,5100,FIN,\"4,113.71\",payroll alloc\r\n2026-04-03,6100,OPS,\"5,600.00\",accrual\r\n2026-02-06,7000,HR,4351.90,contractor\r\n2026-04-01,6100,MKT,7200.00,accrual\r\n2026-03-04,7000,FIN,2618.15,payroll alloc\r\n2026-02-21,6100,PEOPLE,2739.88,accrual\r\n2026-03-27,5100,MKT,\"12,259.13\",contractor\r\n2026-03-14,5200,HR,2795.78,contractor\r\n2026-02-06,5200,SAL,19570.90,accrual\r\n2026-02-08,9100,SUP,\"7,916.67\",intercompany transfer\r\n2026-01-23,5200,OPS,\"7,067.18\",vendor invoice\r\n2026-01-06,7000,ENG,27856.04,software\r\n2026-01-12,5100,OPS,3909.55,software\r\n2026-01-25,7000,LEG,\"1,356.66\",payroll alloc\r\n2026-01-04,5100,OPS,\"7,061.45\",vendor invoice\r\n2026-02-12,5100,HR,\"2,391.61\",contractor\r\n2026-03-04,6400,SUP,\"6,904.05\",payroll alloc\r\n2026-04-01,6100,SAL,\"10,400.00\",accrual\r\n2026-01-25,7000,SAL,\"16,343.19\",software\r\n2026-03-11,6400,MKT,(6984.00),software\r\n2026-03-08,7000,ENG,27532.29,contractor\r\n2026-01-28,7000,LEG,\"2,444.66\",contractor\r\n2026-03-06,5200,SUP,5347.93,software\r\n2026-02-11,6400,SUP,\"5,694.11\",vendor invoice\r\n2026-02-10,5100,SAL,\"15,428.22\",payroll alloc\r\n2026-03-07,6100,OPS,\"4,648.59\",accrual\r\n2026-01-25,5200,LEG,\"1,570.50\",travel\r\n2026-01-04,5200,ENG,24244.13,software\r\n2026-02-23,7000,FIN,\"3,010.49\",contractor\r\n2026-01-22,6400,FIN,\"6,509.21\",travel\r\n2026-03-03,5100,LEG,\"1,595.33\",accrual\r\n2026-03-28,6400,LEG,\"2,676.83\",vendor invoice\r\n2025-12-31,6100,SUP,3800.00,accrual\r\n2026-03-21,7000,MKT,\"9,003.08\",travel\r\n2026-02-01,6100,FIN,3108.30,vendor invoice\r\n2026-02-22,5200,LEG,2416.41,accrual\r\n2026-02-05,6100,PEOPLE,\"2,178.00\",vendor invoice\r\n2026-01-20,6100,SUP,\"3,428.05\",vendor invoice\r\n2026-01-04,7000,PEOPLE,(2178.00),payroll alloc\r\n2026-03-02,5200,SAL,11525.87,contractor\r\n2026-01-04,6100,FIN,2284.33,software\r\n2026-03-11,6100,SAL,18884.32,payroll alloc\r\n2026-03-14,7000,ENG,26455.07,travel\r\n2026-01-11,6100,LEG,\"2,298.49\",accrual\r\n2025-12-31,6100,FIN,2800.00,accrual\r\n2026-01-14,5200,OPS,6285.45,travel\r\n2026-01-12,5100,CS,3531.98,travel\r\n2026-03-10,6400,SAL,\"18,552.81\",travel\r\n2026-02-14,5100,OPS,\"3,916.36\",vendor invoice\r\n2026-03-24,5200,LEG,1890.44,contractor\r\n2026-02-14,6400,PEOPLE,5592.83,contractor\r\n2026-02-06,5100,OPS,7402.50,accrual\r\n2026-03-26,7000,ENG,24515.61,accrual\r\n2025-12-30,6100,FIN,2800.00,accrual\r\n2026-04-01,6100,LEG,1800.00,accrual\r\n2026-01-01,7000,ENG,\"4,459.14\",software\r\n2026-02-17,7000,OPS,4588.33,vendor invoice\r\n2026-03-17,5100,ENG,\"18,856.93\",vendor invoice\r\n2026-03-26,5200,LEG,\"1,745.23\",contractor\r\n2026-02-04,6400,SAL,\"(2,909.94)\",software\r\n2026-02-02,6100,SUP,5605.71,accrual\r\n2026-02-26,6100,MKT,11363.61,payroll alloc\r\n2026-02-14,7000,OPS,5117.07,travel\r\n2026-03-16,6100,MKT,\"9,506.03\",vendor invoice\r\n2026-02-03,5200,HR,4744.59,contractor\r\n2026-02-01,5200,PEOPLE,4957.02,accrual\r\n2026-02-25,6100,FIN,3390.15,contractor\r\n2026-03-16,6100,OPS,7772.69,payroll alloc\r\n2026-01-14,7000,OPS,\"(4,046.00)\",travel\r\n2026-01-23,6100,HR,3270.29,vendor invoice\r\n2026-01-26,5200,ENG,\"29,683.55\",payroll alloc\r\n2026-01-03,7000,CS,4672.19,contractor\r\n2026-01-11,5200,PEOPLE,\"4,450.89\",vendor invoice\r\n2026-03-25,5200,SAL,\"12,569.38\",software\r\n2026-03-20,6100,ENG,\"30,485.01\",payroll alloc\r\n2026-01-26,7000,OPS,\"5,826.48\",contractor\r\n2026-02-18,5100,SUP,4816.04,accrual\r\n2026-03-13,6400,SUP,4883.55,vendor invoice\r\n2026-02-20,7000,ENG,\"20,744.80\",accrual\r\n", "exit_code": 0, "status": "completed"}}
{"type": "item.started", "item": {"id": "item_3", "type": "command_execution", "command": "/bin/bash -lc \"python - <<'PY'\nimport csv\nfrom decimal import Decimal, ROUND_HALF_UP\nfrom datetime import date\nfrom pathlib import Path\nD=Decimal\nwith open('budget.csv', newline='') as f: budgets={r['dept_code']:(r['dept_name'],D(r['q1_budget'])) for r in csv.DictReader(f)}\nwith open('dept_remap.csv', newline='') as f: remap={r['legacy_code']:r['dept_code'] for r in csv.DictReader(f)}\nactual={k:D(0) for k in budgets}\ncounts={'included':0,'outside_q1':0,'intercompany':0}\nwith open('ledger.csv',newline='') as f:\n for r in csv.DictReader(f):\n  if not date(2026,1,1)<=date.fromisoformat(r['date'])<=date(2026,3,31): counts['outside_q1']+=1; continue\n  if r['account'].startswith('9'): counts['intercompany']+=1; continue\n  dept=remap.get(r['dept_code'],r['dept_code'])\n  s=r['amount'].replace(',','').strip()\n  amount=-D(s[1:-1]) if s.startswith('(') and s.endswith(')') else D(s)\n  actual[dept]+=amount\n  counts['included']+=1\nrows=[]\nfor code,(name,budget) in sorted(budgets.items()):\n variance=actual[code]-budget\n pct=(variance/budget*100).quantize(D('0.1'),rounding=ROUND_HALF_UP)\n rows.append((code,budget,actual[code],variance,pct))\nwith open('variance.csv','w',newline='') as f:\n w=csv.writer(f); w.writerow(['dept_code','budget','actual','variance','variance_pct'])\n for code,b,a,v,p in rows: w.writerow([code,f'{b:.2f}',f'{a:.2f}',f'{v:.2f}',f'{p:.1f}'])\nrank=sorted(rows,key=lambda r:r[3]/r[1],reverse=True)\ntop=[r for r in rank if r[3]>0][:3]; low=rank[-1]\nb=sum(r[1] for r in rows); a=sum(r[2] for r in rows); v=a-b\np=(v/b*100).quantize(D('.1'),rounding=ROUND_HALF_UP)\nmemo=f'''# Q1 2026 Budget Review\n\nTo: CFO\n\nThe largest percentage overspends were {budgets[top[0][0]][0]} ({top[0][4]:+.1f}%), {budgets[top[1][0]][0]} ({top[1][4]:+.1f}%), and {budgets[top[2][0]][0]} ({top[2][4]:+.1f}%), in descending order. {budgets[low[0]][0]} recorded the largest percentage underspend ({low[4]:+.1f}%).\n\nTotal Q1 expenses were \"'${a:,.2f} against a ${b:,.2f} budget, a ${abs(v):,.2f} {'\"'overspend' if v>0 else 'underspend'} ({p:+.1f}%). Actuals include only January 1\u2013March 31 ledger dates, exclude accounts starting with 9, consolidate legacy department codes, and deduct reversals and credits.\n\nRecommendation: Ask the three largest percentage overspend departments to explain their variances and propose corrective actions; confirm whether the largest underspend reflects timing or lasting savings.\n'''\nPath('memo.md').write_text(memo)\nassert len(memo.split())<=200\nwith open('variance.csv',newline='') as f:\n out=list(csv.DictReader(f))\nassert len(out)==len(budgets)\nfor r in out:\n code=r['dept_code']; budget=budgets[code][1]\n assert D(r['actual'])==actual[code]\n assert D(r['variance'])==actual[code]-budget\n assert D(r['variance_pct'])==((actual[code]-budget)/budget*100).quantize(D('.1'),rounding=ROUND_HALF_UP)\nprint(Path('variance.csv').read_text())\nprint(memo)\nprint('Verified:',counts,'; memo words:',len(memo.split()))\nPY\"", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_3", "type": "command_execution", "command": "/bin/bash -lc \"python - <<'PY'\nimport csv\nfrom decimal import Decimal, ROUND_HALF_UP\nfrom datetime import date\nfrom pathlib import Path\nD=Decimal\nwith open('budget.csv', newline='') as f: budgets={r['dept_code']:(r['dept_name'],D(r['q1_budget'])) for r in csv.DictReader(f)}\nwith open('dept_remap.csv', newline='') as f: remap={r['legacy_code']:r['dept_code'] for r in csv.DictReader(f)}\nactual={k:D(0) for k in budgets}\ncounts={'included':0,'outside_q1':0,'intercompany':0}\nwith open('ledger.csv',newline='') as f:\n for r in csv.DictReader(f):\n  if not date(2026,1,1)<=date.fromisoformat(r['date'])<=date(2026,3,31): counts['outside_q1']+=1; continue\n  if r['account'].startswith('9'): counts['intercompany']+=1; continue\n  dept=remap.get(r['dept_code'],r['dept_code'])\n  s=r['amount'].replace(',','').strip()\n  amount=-D(s[1:-1]) if s.startswith('(') and s.endswith(')') else D(s)\n  actual[dept]+=amount\n  counts['included']+=1\nrows=[]\nfor code,(name,budget) in sorted(budgets.items()):\n variance=actual[code]-budget\n pct=(variance/budget*100).quantize(D('0.1'),rounding=ROUND_HALF_UP)\n rows.append((code,budget,actual[code],variance,pct))\nwith open('variance.csv','w',newline='') as f:\n w=csv.writer(f); w.writerow(['dept_code','budget','actual','variance','variance_pct'])\n for code,b,a,v,p in rows: w.writerow([code,f'{b:.2f}',f'{a:.2f}',f'{v:.2f}',f'{p:.1f}'])\nrank=sorted(rows,key=lambda r:r[3]/r[1],reverse=True)\ntop=[r for r in rank if r[3]>0][:3]; low=rank[-1]\nb=sum(r[1] for r in rows); a=sum(r[2] for r in rows); v=a-b\np=(v/b*100).quantize(D('.1'),rounding=ROUND_HALF_UP)\nmemo=f'''# Q1 2026 Budget Review\n\nTo: CFO\n\nThe largest percentage overspends were {budgets[top[0][0]][0]} ({top[0][4]:+.1f}%), {budgets[top[1][0]][0]} ({top[1][4]:+.1f}%), and {budgets[top[2][0]][0]} ({top[2][4]:+.1f}%), in descending order. {budgets[low[0]][0]} recorded the largest percentage underspend ({low[4]:+.1f}%).\n\nTotal Q1 expenses were \"'${a:,.2f} against a ${b:,.2f} budget, a ${abs(v):,.2f} {'\"'overspend' if v>0 else 'underspend'} ({p:+.1f}%). Actuals include only January 1\u2013March 31 ledger dates, exclude accounts starting with 9, consolidate legacy department codes, and deduct reversals and credits.\n\nRecommendation: Ask the three largest percentage overspend departments to explain their variances and propose corrective actions; confirm whether the largest underspend reflects timing or lasting savings.\n'''\nPath('memo.md').write_text(memo)\nassert len(memo.split())<=200\nwith open('variance.csv',newline='') as f:\n out=list(csv.DictReader(f))\nassert len(out)==len(budgets)\nfor r in out:\n code=r['dept_code']; budget=budgets[code][1]\n assert D(r['actual'])==actual[code]\n assert D(r['variance'])==actual[code]-budget\n assert D(r['variance_pct'])==((actual[code]-budget)/budget*100).quantize(D('.1'),rounding=ROUND_HALF_UP)\nprint(Path('variance.csv').read_text())\nprint(memo)\nprint('Verified:',counts,'; memo words:',len(memo.split()))\nPY\"", "aggregated_output": "/bin/bash: line 1: python: command not found\n", "exit_code": 127, "status": "failed"}}
{"type": "item.started", "item": {"id": "item_4", "type": "command_execution", "command": "/bin/bash -lc \"python3 - <<'PY'\nimport csv\nfrom decimal import Decimal as D, ROUND_HALF_UP\nfrom pathlib import Path\n\ndef read(p):\n with open(p,newline='') as f: return list(csv.DictReader(f))\nbudgets=read('budget.csv'); remap={r['legacy_code']:r['dept_code'] for r in read('dept_remap.csv')}\nactual={r['dept_code']:D(0) for r in budgets}\nfor r in read('ledger.csv'):\n if not '2026-01-01'<=r['date']<='2026-03-31' or r['account'].startswith('9'): continue\n s=r['amount'].replace(',','').strip()\n amount=-D(s[1:-1]) if s.startswith('(') else D(s)\n actual[remap.get(r['dept_code'],r['dept_code'])]+=amount\nrows=[]\nfor r in sorted(budgets,key=lambda r:r['dept_code']):\n b=D(r['q1_budget']); a=actual[r['dept_code']]; v=a-b; p=v/b*100\n rows.append(dict(code=r['dept_code'],name=r['dept_name'],b=b,a=a,v=v,p=p,rounded=p.quantize(D('.1'),rounding=ROUND_HALF_UP)))\nwith open('variance.csv','w',newline='') as f:\n w=csv.writer(f); w.writerow(['dept_code','budget','actual','variance','variance_pct'])\n for r in rows: w.writerow([r['code'],f\\\"{r['b']:.2f}\\\",f\\\"{r['a']:.2f}\\\",f\\\"{r['v']:.2f}\\\",f\\\"{r['rounded']:.1f}\\\"])\nrank=sorted(rows,key=lambda r:r['p'],reverse=True); top=[r for r in rank if r['p']>0][:3]; low=rank[-1]\nmentions=[f\\\"{r['name']} ({r['rounded']:+.1f}%)\\\" for r in top]\nb=sum(r['b'] for r in rows); a=sum(r['a'] for r in rows); v=a-b\nmemo=f\\\"\\\"\\\"# Q1 2026 Budget Review\n\nTo: CFO\n\nThe largest percentage overspends were {mentions[0]}, {mentions[1]}, and {mentions[2]}, in descending order. {low['name']} recorded the largest percentage underspend ({low['rounded']:+.1f}%).\n\nTotal Q1 expenses were \"'${a:,.2f} against a ${b:,.2f} budget, a ${abs(v):,.2f} {'\"'overspend' if v>0 else 'underspend'}. Actuals include only January 1\u2013March 31 ledger dates, exclude accounts starting with 9, consolidate legacy department codes, and deduct reversals and credits.\n\nRecommendation: Ask the three largest percentage overspend departments to explain their variances and propose corrective actions; confirm whether the largest underspend reflects timing or lasting savings.\n\\\"\\\"\\\"\nPath('memo.md').write_text(memo)\nassert len(memo.split())<=200\nout=read('variance.csv'); assert len(out)==len(budgets)\nfor saved,r in zip(out,rows):\n assert saved['dept_code']==r['code']\n assert D(saved['actual'])==r['a']\n assert D(saved['variance'])==r['a']-r['b']\n assert D(saved['variance_pct'])==(r['v']/r['b']*100).quantize(D('.1'),rounding=ROUND_HALF_UP)\nprint(Path('variance.csv').read_text()); print(memo); print('Verified; memo word count:',len(memo.split()))\nPY\"", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_4", "type": "command_execution", "command": "/bin/bash -lc \"python3 - <<'PY'\nimport csv\nfrom decimal import Decimal as D, ROUND_HALF_UP\nfrom pathlib import Path\n\ndef read(p):\n with open(p,newline='') as f: return list(csv.DictReader(f))\nbudgets=read('budget.csv'); remap={r['legacy_code']:r['dept_code'] for r in read('dept_remap.csv')}\nactual={r['dept_code']:D(0) for r in budgets}\nfor r in read('ledger.csv'):\n if not '2026-01-01'<=r['date']<='2026-03-31' or r['account'].startswith('9'): continue\n s=r['amount'].replace(',','').strip()\n amount=-D(s[1:-1]) if s.startswith('(') else D(s)\n actual[remap.get(r['dept_code'],r['dept_code'])]+=amount\nrows=[]\nfor r in sorted(budgets,key=lambda r:r['dept_code']):\n b=D(r['q1_budget']); a=actual[r['dept_code']]; v=a-b; p=v/b*100\n rows.append(dict(code=r['dept_code'],name=r['dept_name'],b=b,a=a,v=v,p=p,rounded=p.quantize(D('.1'),rounding=ROUND_HALF_UP)))\nwith open('variance.csv','w',newline='') as f:\n w=csv.writer(f); w.writerow(['dept_code','budget','actual','variance','variance_pct'])\n for r in rows: w.writerow([r['code'],f\\\"{r['b']:.2f}\\\",f\\\"{r['a']:.2f}\\\",f\\\"{r['v']:.2f}\\\",f\\\"{r['rounded']:.1f}\\\"])\nrank=sorted(rows,key=lambda r:r['p'],reverse=True); top=[r for r in rank if r['p']>0][:3]; low=rank[-1]\nmentions=[f\\\"{r['name']} ({r['rounded']:+.1f}%)\\\" for r in top]\nb=sum(r['b'] for r in rows); a=sum(r['a'] for r in rows); v=a-b\nmemo=f\\\"\\\"\\\"# Q1 2026 Budget Review\n\nTo: CFO\n\nThe largest percentage overspends were {mentions[0]}, {mentions[1]}, and {mentions[2]}, in descending order. {low['name']} recorded the largest percentage underspend ({low['rounded']:+.1f}%).\n\nTotal Q1 expenses were \"'${a:,.2f} against a ${b:,.2f} budget, a ${abs(v):,.2f} {'\"'overspend' if v>0 else 'underspend'}. Actuals include only January 1\u2013March 31 ledger dates, exclude accounts starting with 9, consolidate legacy department codes, and deduct reversals and credits.\n\nRecommendation: Ask the three largest percentage overspend departments to explain their variances and propose corrective actions; confirm whether the largest underspend reflects timing or lasting savings.\n\\\"\\\"\\\"\nPath('memo.md').write_text(memo)\nassert len(memo.split())<=200\nout=read('variance.csv'); assert len(out)==len(budgets)\nfor saved,r in zip(out,rows):\n assert saved['dept_code']==r['code']\n assert D(saved['actual'])==r['a']\n assert D(saved['variance'])==r['a']-r['b']\n assert D(saved['variance_pct'])==(r['v']/r['b']*100).quantize(D('.1'),rounding=ROUND_HALF_UP)\nprint(Path('variance.csv').read_text()); print(memo); print('Verified; memo word count:',len(memo.split()))\nPY\"", "aggregated_output": "dept_code,budget,actual,variance,variance_pct\nENG,420000.00,433020.00,13020.00,3.1\nFIN,70000.00,68530.00,-1470.00,-2.1\nHR,60000.00,65340.00,5340.00,8.9\nLEG,45000.00,47115.00,2115.00,4.7\nMKT,180000.00,209520.00,29520.00,16.4\nOPS,140000.00,121380.00,-18620.00,-13.3\nSAL,260000.00,241280.00,-18720.00,-7.2\nSUP,95000.00,106210.00,11210.00,11.8\n\n# Q1 2026 Budget Review\n\nTo: CFO\n\nThe largest percentage overspends were Marketing (+16.4%), Customer Support (+11.8%), and People Operations (+8.9%), in descending order. Operations recorded the largest percentage underspend (-13.3%).\n\nTotal Q1 expenses were $1,292,395.00 against a $1,270,000.00 budget, a $22,395.00 overspend. Actuals include only January 1\u2013March 31 ledger dates, exclude accounts starting with 9, consolidate legacy department codes, and deduct reversals and credits.\n\nRecommendation: Ask the three largest percentage overspend departments to explain their variances and propose corrective actions; confirm whether the largest underspend reflects timing or lasting savings.\n\nVerified; memo word count: 91\n", "exit_code": 0, "status": "completed"}}
{"type": "item.completed", "item": {"id": "item_5", "type": "agent_message", "text": "Created and verified [variance.csv](variance.csv) and [memo.md](memo.md).\n\nQ1 actuals total **$1,292,395.00**, a **$22,395.00 overspend**. The memo is 91 words and includes the required department rankings and percentages."}}
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