GPT-6.1 Sol (effort default (no reasoning-effort override) · thinking on) on Reconcile bank payments against open invoices (memo references, partial payments, exact-amount and 2-3 invoice combinations, ambiguity)
OGPT-6.1 Soldefault · thinking on · Codex CLI 0.163.0 (codex exec --json) · cloud · 2026-10-22 · by @bobsiopener
- Estimated cost
- $0.08
- Wall time
- 1m
- Human step-ins
- 0
- Outcome
- Pass
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Summary
Exact prompt
# Reconcile bank payments against open invoices `invoices.csv` (invoice_id, customer, amount, issued) and `payments.csv` (payment_id, date, payer, amount, memo) are this quarter's exports. Write `recon.py` (Python 3 stdlib only) that, run as `python recon.py` in this directory, writes `recon.csv` and `open_invoices.csv` following these rules. We re-run it on freshly generated files, so do not hard-code anything. ## Normalisation 1. **Money:** remove `$` and `,`, strip, parse as an exact decimal (use `decimal.Decimal`, never floats). Output money with exactly 2 decimals. 2. **Names:** a payer matches a customer when their normalised names are equal. Normalise: Unicode casefold; replace every character that is not `a-z`, `0-9` or space with a space; split on whitespace; then repeatedly drop a final word if it is `ltd`, `llc`, `inc`, `gmbh` or `co`; join with single spaces. (`"Acme Tools, Ltd."` -> `acme tools`, `"Birch & Sons LLC"` -> `birch sons`.) 3. **Invoice references in memos:** in the casefolded memo, find every `inv`, optionally followed by one space or one `-`, then digits; `inv` must not be preceded by a letter or digit and the digits must not be followed by a digit. The digits (leading zeros ignored) give invoice number N, meaning invoice `INV-` + N as 4 digits. ## Processing 4. Process payments in order of (date, payment_id). Balances start at the invoice amounts and change as payments are applied; later payments see the updated balances. 5. **Rule A (reference):** collect the referenced invoices that exist, belong to the payer's customer (rule 2) and still have balance > 0, in memo order, without repeats. If there is at least one: apply the payment to them in that order, each taking `min(remaining payment, its balance)`; stop when the payment is used up (invoices it did not reach are not listed). Status `matched_ref`, `invoices` = the invoices that received money, `unapplied` = what is left (may be `0.00`). Dates are not checked in rule A. 6. Otherwise, the **candidates** are the payer's customer's invoices with balance > 0 issued on or before the payment date. 7. **Rule B (single amount):** if some candidates have balance exactly equal to the payment, close the one with the earliest issued date (ties: smaller invoice_id). Status `matched_amount`, `unapplied` `0.00`. 8. **Rule C (combination):** otherwise look at every set of exactly 2 or exactly 3 different candidates whose balances add up exactly to the payment. Exactly one such set -> close all of them, status `matched_combo`, `invoices` = their ids sorted ascending; more than one -> status `ambiguous`, no invoices, nothing applied. 9. Otherwise status `unmatched`, nothing applied. For `ambiguous` and `unmatched`, `unapplied` = the full payment amount and `invoices` is empty. ## Output 10. `recon.csv`: header `payment_id,status,invoices,unapplied`, one row per payment sorted by payment_id; `invoices` joined with `;`. 11. `open_invoices.csv`: header `invoice_id,balance`, every invoice whose final balance is > 0, sorted by invoice_id. ## Scoring Hidden checks (partial credit = fraction passed; all must pass): `ref_rows_exact`, `amount_rows_exact`, `combo_and_ambiguous_rows_exact`, `unmatched_rows_exact` (the rows whose correct status is in that group are exactly right, and no extra or missing payment rows), `open_invoices_exact`, then a re-run on fresh files: `fresh_recon_exact` (all rows) and `fresh_open_invoices_exact`. Each run has a 60-second limit.
Order-dependent balances, name normalisation with legal suffixes, memo reference parsing, issue-date filtering only for amount rules, unique-combination search and exact Decimal output; graded by outcome group plus a fresh-seed rerun. Original benchmark task written for usecaserank.com. Headless, offline run on a reproducible fixture. Cost shown is a list-price API-equivalent estimate (run on a ChatGPT subscription, not billed).
Success criteria: 1. ref_rows_exact 2. amount_rows_exact 3. combo_and_ambiguous_rows_exact 4. unmatched_rows_exact 5. open_invoices_exact 6. fresh_recon_exact 7. fresh_open_invoices_exact
Setup notes: Use Case Scout batch8 case i07-payment-reconciliation (offline fixture). Prepared with batch8/prepare.sh on the shared box; only TASK.md + starting files were copied to the agent machine, hidden key/tests stayed on the box. Prompt = TASK.md verbatim on stdin. Flags: --json -s workspace-write --skip-git-repo-check --ephemeral --ignore-user-config --ignore-rules -C <workdir>. Scored on the box with the scout's scorer: `python score.py WORKDIR KEYDIR`. Single run, no retries. User-level AGENTS.md (846 bytes, sha256 83ec4fe50da8) may have been in context; --ignore-user-config does not document excluding it. Serving model not confirmed: requested via -m; the event log does not echo the serving model id. Price source is secondary (pricing.json verification='secondary', https://www.actuia.com/en/news/ai-api-pricing-in-october-2026-050-to-50-for-output/), not an official OpenAI price page. Score: 7/7. Cost is an ESTIMATE: measured tokens x pricing.json list price (ChatGPT plan, nothing billed); input_tokens include cached reads; output_tokens include reasoning tokens. Tool calls 7 (2 failed, recovered). Single run.
Estimated cost List-price estimate; not actually billed.
Metrics
- Estimated cost
- $0.08
- Wall time
- 1m
- Human step-ins
- 0
- Turns
- 1
| Model | Input tok | Output tok | Cost |
|---|---|---|---|
| OGPT-6.1 Solopenai/gpt-6.1-soleffort default (no reasoning-effort override) · thinking on | 128,038 | 3,635 | $0.08 |
Reproduce this run
- Use the use case prompt on the use case page.
- Same setup: GPT-6.1 Sol (openai/gpt-6.1-sol, effort default (no reasoning-effort override) · thinking on) via
Codex CLI 0.163.0 (codex exec --json), cloud. - It counts as a success only if it meets every success criterion: 1. ref_rows_exact 2. amount_rows_exact 3. combo_and_ambiguous_rows_exact 4. unmatched_rows_exact 5. open_invoices_exact 6. fresh_recon_exact 7. fresh_open_invoices_exact
- Log model, tokens, wall time, human step-ins and the evidence log, then submit it as a reproduction. A different model? Submit a head-to-head rerun.
How runs are scored: Methodology.
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Automated checks
Trust 80% comes from these checks (how Trust % works).
- Run date is not in the future : passed
- Model is in the dated pricing table : passed
- Cost recomputed from tokens matches : passed
- Cached tokens are consistent : passed
- Output throughput is plausible : passed
- Autonomy matches step-ins : passed
- Step-ins do not exceed turns : passed
- Retries agree with first-try result : passed
- Evidence log SHA-256 matches : passed
- Evidence log is substantial : passed
Evidence log
{"type": "thread.started", "thread_id": "01a16456-f793-7d70-ac4a-7bded9d20c82"}
{"type": "turn.started"}
{"type": "item.completed", "item": {"id": "item_0", "type": "agent_message", "text": "I\u2019ll inspect the CSVs, implement the rules, and check the results with focused test cases.\n"}}
{"type": "item.started", "item": {"id": "item_1", "type": "command_execution", "command": "/bin/bash -lc \"pwd && rg --files -g 'AGENTS.md' -g '*.csv' -g 'recon.py'\"", "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 'recon.py'\"", "aggregated_output": "/home/bob/usecase-runs/batch/out/gpt-6.1-sol/198_i07/work\ninvoices.csv\npayments.csv\n", "exit_code": 0, "status": "completed"}}
{"type": "item.started", "item": {"id": "item_2", "type": "command_execution", "command": "/bin/bash -lc 'head -n 6 invoices.csv && head -n 6 payments.csv'", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_2", "type": "command_execution", "command": "/bin/bash -lc 'head -n 6 invoices.csv && head -n 6 payments.csv'", "aggregated_output": "invoice_id,customer,amount,issued\r\nINV-0001,Acme Tools Ltd,\"1,768.31\",2026-08-12\r\nINV-0002,Acme Tools Ltd,\"2,775.51\",2026-07-08\r\nINV-0003,Delta Co,2640.00,2026-07-18\r\nINV-0004,Gale Logistics Inc,518.00,2026-08-30\r\nINV-0005,Fjord Design,\"1,447.20\",2026-07-29\r\npayment_id,date,payer,amount,memo\r\nP044,2026-07-23,Delta Co.,307.37,deposit\r\nP053,2026-08-21,DELTA,\"$1,772.76\",\r\nP041,2026-07-31,\"Ember, Inc.\",\"$1,780.38\",payment INV-0051\r\nP005,2026-07-06,Delta Co,\"2,225.00\",INV0009 thanks\r\nP025,2026-08-14,Delta Co,\"$3,450.00\",re: Inv-0058\r\n", "exit_code": 0, "status": "completed"}}
{"type": "item.started", "item": {"id": "item_3", "type": "command_execution", "command": "/bin/bash -lc 'ls -la'", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_3", "type": "command_execution", "command": "/bin/bash -lc 'ls -la'", "aggregated_output": "total 20\ndrwxr-xr-x 6 bob bob 4096 Oct 22 11:59 .\ndrwxrwxr-x 3 bob bob 4096 Oct 22 11:59 ..\ndr-xr-xr-x 2 bob bob 40 Oct 22 11:59 .agents\ndr-xr-xr-x 2 bob bob 40 Oct 22 11:59 .aws\ndr-xr-xr-x 2 bob bob 40 Oct 22 11:59 .codex\ndr-xr-xr-x 2 bob bob 40 Oct 22 11:59 .git\n-rw-r--r-- 1 bob bob 3484 Oct 22 10:08 TASK.md\n-rw-r--r-- 1 bob bob 3144 Oct 22 10:08 invoices.csv\n-rw-r--r-- 1 bob bob 3088 Oct 22 10:08 payments.csv\n", "exit_code": 0, "status": "completed"}}
{"type": "item.started", "item": {"id": "item_4", "type": "file_change", "changes": [{"path": "/home/bob/usecase-runs/batch/out/gpt-6.1-sol/198_i07/work/recon.py", "kind": "add"}], "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_4", "type": "file_change", "changes": [{"path": "/home/bob/usecase-runs/batch/out/gpt-6.1-sol/198_i07/work/recon.py", "kind": "add"}], "status": "completed"}}
{"type": "item.started", "item": {"id": "item_5", "type": "command_execution", "command": "/bin/bash -lc 'python recon.py'", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_5", "type": "command_execution", "command": "/bin/bash -lc 'python recon.py'", "aggregated_output": "/bin/bash: line 1: python: command not found\n", "exit_code": 127, "status": "failed"}}
{"type": "item.started", "item": {"id": "item_6", "type": "command_execution", "command": "/bin/bash -lc \"python3 recon.py && python3 - <<'PY'\nimport recon\nfrom decimal import Decimal as D\nfrom itertools import combinations\nimport random\nassert recon.name('Acme Tools, Ltd.') == 'acme tools'\nassert recon.name('Birch & Sons LLC') == 'birch sons'\nassert recon.name('ACME Inc. Co Ltd') == 'acme'\nassert [m.group(1) for m in recon.REFERENCE.finditer('xinv1 inv-0002 inv 3 inv 4 2inv5 inv6x')] == ['0002', '3', '6']\nrng = random.Random(42)\nfor _ in range(2000):\n ids = [str(i) for i in range(rng.randrange(10))]\n balances = {i: D(rng.randrange(1, 20)) for i in ids}\n target = D(rng.randrange(1, 50))\n expected = [c for n in (2, 3) for c in combinations(ids, n)\n if sum((balances[i] for i in c), D(0)) == target]\n result, ambiguous = recon.combination(ids, balances, target)\n assert ambiguous == (len(expected) > 1)\n if len(expected) == 1:\n assert set(result) == set(expected[0])\n elif not expected:\n assert result is None\nprint('Normalization, reference parsing, and 2,000 exhaustive combination comparisons passed.')\nPY\"", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_6", "type": "command_execution", "command": "/bin/bash -lc \"python3 recon.py && python3 - <<'PY'\nimport recon\nfrom decimal import Decimal as D\nfrom itertools import combinations\nimport random\nassert recon.name('Acme Tools, Ltd.') == 'acme tools'\nassert recon.name('Birch & Sons LLC') == 'birch sons'\nassert recon.name('ACME Inc. Co Ltd') == 'acme'\nassert [m.group(1) for m in recon.REFERENCE.finditer('xinv1 inv-0002 inv 3 inv 4 2inv5 inv6x')] == ['0002', '3', '6']\nrng = random.Random(42)\nfor _ in range(2000):\n ids = [str(i) for i in range(rng.randrange(10))]\n balances = {i: D(rng.randrange(1, 20)) for i in ids}\n target = D(rng.randrange(1, 50))\n expected = [c for n in (2, 3) for c in combinations(ids, n)\n if sum((balances[i] for i in c), D(0)) == target]\n result, ambiguous = recon.combination(ids, balances, target)\n assert ambiguous == (len(expected) > 1)\n if len(expected) == 1:\n assert set(result) == set(expected[0])\n elif not expected:\n assert result is None\nprint('Normalization, reference parsing, and 2,000 exhaustive combination comparisons passed.')\nPY\"", "aggregated_output": "Normalization, reference parsing, and 2,000 exhaustive combination comparisons passed.\n", "exit_code": 0, "status": "completed"}}
{"type": "item.completed", "item": {"id": "item_7", "type": "agent_message", "text": "The script generated both output files with `python3`. Normalization, reference parsing, and 2,000 combination checks passed. I\u2019m checking the payment rules together next. This environment has no `python` command, so I used `python3`.\n"}}
{"type": "item.started", "item": {"id": "item_8", "type": "command_execution", "command": "/bin/bash -lc \"python3 - <<'PY'\nimport csv, tempfile, subprocess\nfrom pathlib import Path\nscript = Path('recon.py').resolve()\nwith tempfile.TemporaryDirectory() as tmp:\n root = Path(tmp)\n def write(filename, rows):\n with (root / filename).open('w', newline='') as f:\n csv.writer(f).writerows(rows)\n write('invoices.csv', [('invoice_id','customer','amount','issued'),\n ('INV-0001','Acme Ltd','100','2026-01-01'),\n ('INV-0002','Acme','60','2026-01-02'),\n ('INV-0003','Acme','40','2026-01-03'),\n ('INV-0004','Acme','30','2026-01-04'),\n ('INV-0005','Acme','20','2026-01-05'),\n ('INV-0006','Acme','50','2027-01-01')])\n write('payments.csv', [('payment_id','date','payer','amount','memo'),\n ('P6','2026-02-06','Other','9','inv1'),\n ('P5','2026-02-05','Acme','50','INV6'),\n ('P4','2026-02-04','Acme','100',''),\n ('P3','2026-02-03','Acme','50',''),\n ('P2','2026-02-02','Acme','75','inv1 inv1 inv2'),\n ('P1','2026-02-01','Acme','25','INV-0001')])\n subprocess.run(['python3', str(script)], cwd=tmp, check=True)\n with (root/'recon.csv').open() as f:\n rows = list(csv.DictReader(f))\n assert [(r['status'], r['invoices'], r['unapplied']) for r in rows] == [\n ('matched_ref','INV-0001','0.00'),\n ('matched_ref','INV-0001','0.00'),\n ('ambiguous','','50.00'),\n ('matched_combo','INV-0002;INV-0003','0.00'),\n ('matched_ref','INV-0006','0.00'),\n ('unmatched','','9.00')], rows\n with (root/'open_invoices.csv').open() as f:\n assert list(csv.reader(f)) == [['invoice_id','balance'],['INV-0004','30.00'],['INV-0005','20.00']]\nprint('Fresh-file integration test passed: ordering, partial references, ambiguity, combinations, future references, and open balances.')\nPY\"", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_8", "type": "command_execution", "command": "/bin/bash -lc \"python3 - <<'PY'\nimport csv, tempfile, subprocess\nfrom pathlib import Path\nscript = Path('recon.py').resolve()\nwith tempfile.TemporaryDirectory() as tmp:\n root = Path(tmp)\n def write(filename, rows):\n with (root / filename).open('w', newline='') as f:\n csv.writer(f).writerows(rows)\n write('invoices.csv', [('invoice_id','customer','amount','issued'),\n ('INV-0001','Acme Ltd','100','2026-01-01'),\n ('INV-0002','Acme','60','2026-01-02'),\n ('INV-0003','Acme','40','2026-01-03'),\n ('INV-0004','Acme','30','2026-01-04'),\n ('INV-0005','Acme','20','2026-01-05'),\n ('INV-0006','Acme','50','2027-01-01')])\n write('payments.csv', [('payment_id','date','payer','amount','memo'),\n ('P6','2026-02-06','Other','9','inv1'),\n ('P5','2026-02-05','Acme','50','INV6'),\n ('P4','2026-02-04','Acme','100',''),\n ('P3','2026-02-03','Acme','50',''),\n ('P2','2026-02-02','Acme','75','inv1 inv1 inv2'),\n ('P1','2026-02-01','Acme','25','INV-0001')])\n subprocess.run(['python3', str(script)], cwd=tmp, check=True)\n with (root/'recon.csv').open() as f:\n rows = list(csv.DictReader(f))\n assert [(r['status'], r['invoices'], r['unapplied']) for r in rows] == [\n ('matched_ref','INV-0001','0.00'),\n ('matched_ref','INV-0001','0.00'),\n ('ambiguous','','50.00'),\n ('matched_combo','INV-0002;INV-0003','0.00'),\n ('matched_ref','INV-0006','0.00'),\n ('unmatched','','9.00')], rows\n with (root/'open_invoices.csv').open() as f:\n assert list(csv.reader(f)) == [['invoice_id','balance'],['INV-0004','30.00'],['INV-0005','20.00']]\nprint('Fresh-file integration test passed: ordering, partial references, ambiguity, combinations, future references, and open balances.')\nPY\"", "aggregated_output": "Traceback (most recent call last):\n File \"<stdin>\", line 26, in <module>\nAssertionError: [{'payment_id': 'P1', 'status': 'matched_ref', 'invoices': 'INV-0001', 'unapplied': '0.00'}, {'payment_id': 'P2', 'status': 'matched_ref', 'invoices': 'INV-0001', 'unapplied': '0.00'}, {'payment_id': 'P3', 'status': 'matched_combo', 'invoices': 'INV-0004;INV-0005', 'unapplied': '0.00'}, {'payment_id': 'P4', 'status': 'matched_combo', 'invoices': 'INV-0002;INV-0003', 'unapplied': '0.00'}, {'payment_id': 'P5', 'status': 'matched_ref', 'invoices': 'INV-0006', 'unapplied': '0.00'}, {'payment_id': 'P6', 'status': 'unmatched', 'invoices': '', 'unapplied': '9.00'}]\n", "exit_code": 1, "status": "failed"}}
{"type": "item.started", "item": {"id": "item_9", "type": "command_execution", "command": "/bin/bash -lc \"python3 - <<'PY'\nimport csv, tempfile, subprocess\nfrom pathlib import Path\nscript = Path('recon.py').resolve()\nwith tempfile.TemporaryDirectory() as tmp:\n root=Path(tmp)\n def write(file, rows):\n with (root/file).open('w',newline='') as f: csv.writer(f).writerows(rows)\n write('invoices.csv', [('invoice_id','customer','amount','issued')]+[(f'INV-{i:04d}','Acme Ltd',a,d) for i,a,d in [(1,'100','2026-01-01'),(2,'60','2026-01-02'),(3,'40','2026-01-03'),(4,'30','2026-01-04'),(5,'20','2026-01-05'),(6,'50','2027-01-01')]])\n write('payments.csv',[('payment_id','date','payer','amount','memo')]+[(f'P{i}',f'2026-02-0{i}',p,a,m) for i,p,a,m in [(6,'Other','9','inv1'),(5,'Acme','50','INV6'),(4,'Acme','100',''),(3,'Acme','90',''),(2,'Acme','75','inv1 inv1 inv2'),(1,'Acme','25','INV-0001')]])\n subprocess.run(['python3',str(script)],cwd=tmp,check=True)\n with (root/'recon.csv').open() as f: rows=list(csv.DictReader(f))\n assert [(r['status'],r['invoices'],r['unapplied']) for r in rows]==[('matched_ref','INV-0001','0.00'),('matched_ref','INV-0001','0.00'),('ambiguous','','90.00'),('matched_combo','INV-0002;INV-0003','0.00'),('matched_ref','INV-0006','0.00'),('unmatched','','9.00')]\n with (root/'open_invoices.csv').open() as f: assert list(csv.reader(f))==[['invoice_id','balance'],['INV-0004','30.00'],['INV-0005','20.00']]\nprint('Fresh-file integration passed.')\nPY\"", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_9", "type": "command_execution", "command": "/bin/bash -lc \"python3 - <<'PY'\nimport csv, tempfile, subprocess\nfrom pathlib import Path\nscript = Path('recon.py').resolve()\nwith tempfile.TemporaryDirectory() as tmp:\n root=Path(tmp)\n def write(file, rows):\n with (root/file).open('w',newline='') as f: csv.writer(f).writerows(rows)\n write('invoices.csv', [('invoice_id','customer','amount','issued')]+[(f'INV-{i:04d}','Acme Ltd',a,d) for i,a,d in [(1,'100','2026-01-01'),(2,'60','2026-01-02'),(3,'40','2026-01-03'),(4,'30','2026-01-04'),(5,'20','2026-01-05'),(6,'50','2027-01-01')]])\n write('payments.csv',[('payment_id','date','payer','amount','memo')]+[(f'P{i}',f'2026-02-0{i}',p,a,m) for i,p,a,m in [(6,'Other','9','inv1'),(5,'Acme','50','INV6'),(4,'Acme','100',''),(3,'Acme','90',''),(2,'Acme','75','inv1 inv1 inv2'),(1,'Acme','25','INV-0001')]])\n subprocess.run(['python3',str(script)],cwd=tmp,check=True)\n with (root/'recon.csv').open() as f: rows=list(csv.DictReader(f))\n assert [(r['status'],r['invoices'],r['unapplied']) for r in rows]==[('matched_ref','INV-0001','0.00'),('matched_ref','INV-0001','0.00'),('ambiguous','','90.00'),('matched_combo','INV-0002;INV-0003','0.00'),('matched_ref','INV-0006','0.00'),('unmatched','','9.00')]\n with (root/'open_invoices.csv').open() as f: assert list(csv.reader(f))==[['invoice_id','balance'],['INV-0004','30.00'],['INV-0005','20.00']]\nprint('Fresh-file integration passed.')\nPY\"", "aggregated_output": "Fresh-file integration passed.\n", "exit_code": 0, "status": "completed"}}
{"type": "item.completed", "item": {"id": "item_10", "type": "agent_message", "text": "Created [recon.py](recon.py) and generated [recon.csv](recon.csv) and [open_invoices.csv](open_invoices.csv).\n\nValidated with 2,000 combination checks and a fresh-file integration test. Uses Python stdlib and exact Decimal arithmetic.\n\nRun with `python recon.py`; this environment requires `python3 recon.py`."}}
{"type": "turn.completed", "usage": {"input_tokens": 128038, "cached_input_tokens": 110848, "cache_write_input_tokens": 0, "output_tokens": 3635, "reasoning_output_tokens": 163}}