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GPT-6.1 Sol (effort default (no reasoning-effort override) · thinking on) on Build a csvq CLI (select/where/sort/limit/count, csv|json|table output, exact exit codes) from a written spec

OGPT-6.1 Soldefault · thinking on · Codex CLI 0.163.0 (codex exec --json) · cloud · 2026-10-22 · by @bobsiopener

Trust 80%Fully autonomoussuccess · first try
Estimated cost
$0.06
Wall time
1m
Human step-ins
0
Outcome
Pass

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Summary

Exact prompt

# Task: build the `csvq` command-line tool Write `csvq.py` (Python 3 standard library only, run as `python3 csvq.py ...`). It reads CSV (RFC 4180 quoting, UTF-8, header row required) from a file argument or from stdin when the file is `-` or omitted, and writes to stdout. `people.csv` is a sample. Options (may appear in any order): - `--select COLS` comma-separated column names to output, in that order (default: all, original order). - `--where EXPR` repeatable; all must match. EXPR is `col OP value` with OP one of `=`, `!=`, `<`, `<=`, `>`, `>=`, `~` (case-insensitive substring). If both the cell and value parse as numbers, compare numerically, otherwise as strings. An empty cell never matches `<`,`<=`,`>`,`>=`. - `--sort COL` ascending; `--sort -COL` descending. Numeric if every non-empty value in the column is a number, else string. Empty cells always sort last (both directions). Sort is stable. - `--limit N` output at most N rows (after filtering and sorting). - `--format csv|json|table` (default csv). csv: header + rows, quoted as needed by Python's csv module, `\n` line endings. json: a JSON array of objects (keys in output column order, all values strings), `ensure_ascii=False`, followed by a newline. table: columns left-aligned, padded to the widest cell (header included) with two spaces between columns, no trailing spaces, a dashes line under the header the width of each column. - `--count` print only the number of matching rows (after --where, ignoring --limit) and a newline. - `-h/--help` usage, exit 0. Errors go to stderr with a one-line message and a non-zero exit: unknown column (in any option) exits 2; bad usage (unknown option, bad --where, non-integer/negative --limit, bad --format) exits 2; unreadable input file exits 1. Nothing is printed to stdout on error. No network.

Byte-exact output: RFC 4180 quoting, numeric-vs-string comparison, empty cells sorting last in both directions, stable descending sort, `--sort -COL` argument parsing, table padding without trailing spaces, and distinct exit codes with clean stdout on error. 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. 21 hidden invocations (alternating file argument and stdin) produce byte-identical stdout and exit code 0, or for error cases the exact exit code 2 with empty stdout and a stderr message. 2. A missing input file exits 1 with empty stdout and a stderr message. 3. -h exits 0 and its usage text mentions --where. 4. Reading stdin via '-' works.

Setup notes: Use Case Scout batch5 case e04-csvq-cli (offline fixture). Prepared with batch5/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: 24/24. 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 3 (0 failed, recovered). Single run.

Estimated cost List-price estimate; not actually billed.

Metrics

Estimated cost
$0.06
Wall time
1m
Human step-ins
0
Turns
1
Model usage
ModelInput tokOutput tokCost
OGPT-6.1 Solopenai/gpt-6.1-soleffort default (no reasoning-effort override) · thinking on84,7202,653$0.06

Reproduce this run

  1. Use the use case prompt on the use case page.
  2. 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.
  3. It counts as a success only if it meets every success criterion: 1. 21 hidden invocations (alternating file argument and stdin) produce byte-identical stdout and exit code 0, or for error cases the exact exit code 2 with empty stdout and a stderr message. 2. A missing input file exits 1 with empty stdout and a stderr message. 3. -h exits 0 and its usage text mentions --where. 4. Reading stdin via '-' works.
  4. 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).

Evidence log
{"type": "thread.started", "thread_id": "01a1642f-7741-70c0-8e57-719b5abdd8d3"}
{"type": "turn.started"}
{"type": "item.completed", "item": {"id": "item_0", "type": "agent_message", "text": "I\u2019ll inspect the sample, build `csvq.py`, and check the filtering, sorting, output formats, and error handling.\n"}}
{"type": "item.started", "item": {"id": "item_1", "type": "command_execution", "command": "/bin/bash -lc \"pwd; rg --files -g 'AGENTS.md' -g 'people.csv' -g '*csvq*' -g '*test*'\"", "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 'people.csv' -g '*csvq*' -g '*test*'\"", "aggregated_output": "/home/bob/usecase-runs/batch/out/gpt-6.1-sol/163_e04/work\npeople.csv\n", "exit_code": 0, "status": "completed"}}
{"type": "item.started", "item": {"id": "item_2", "type": "command_execution", "command": "/bin/bash -lc 'cat people.csv; ls -la'", "aggregated_output": "", "exit_code": null, "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_2", "type": "command_execution", "command": "/bin/bash -lc 'cat people.csv; ls -la'", "aggregated_output": "id,name,city,age,joined\n1,Ana Silva,Lisbon,34,2021-03-04\n2,Bo Chen,\"Austin, TX\",28,2022-11-30\n3,C\u00e9line Dupont,Paris,41,2019-07-15\n4,Dev Patel,Austin TX,,2023-01-09\n5,Eli Moss,Lisbon,28,2020-05-21\n6,\"Faye \"\"Fi\"\" Ortiz\",Paris,9,2024-02-29\ntotal 16\ndrwxr-xr-x 6 bob bob 4096 Oct 22 11:16 .\ndrwxrwxr-x 3 bob bob 4096 Oct 22 11:16 ..\ndr-xr-xr-x 2 bob bob   40 Oct 22 11:16 .agents\ndr-xr-xr-x 2 bob bob   40 Oct 22 11:16 .aws\ndr-xr-xr-x 2 bob bob   40 Oct 22 11:16 .codex\ndr-xr-xr-x 2 bob bob   40 Oct 22 11:16 .git\n-rw-r--r-- 1 bob bob 1822 Oct 22 10:08 TASK.md\n-rw-r--r-- 1 bob bob  238 Oct 22 10:08 people.csv\n", "exit_code": 0, "status": "completed"}}
{"type": "item.started", "item": {"id": "item_3", "type": "file_change", "changes": [{"path": "/home/bob/usecase-runs/batch/out/gpt-6.1-sol/163_e04/work/csvq.py", "kind": "add"}], "status": "in_progress"}}
{"type": "item.completed", "item": {"id": "item_3", "type": "file_change", "changes": [{"path": "/home/bob/usecase-runs/batch/out/gpt-6.1-sol/163_e04/work/csvq.py", "kind": "add"}], "status": "completed"}}
{"type": "item.started", "item": {"id": "item_4", "type": "command_execution", "command": "/bin/bash -lc \"python3 - <<'PY'\nimport subprocess, json, csv, io\n\ndef call(*args, data=None, code=0):\n    p = subprocess.run(['python3','csvq.py',*args],input=data,text=True,capture_output=True)\n    assert p.returncode == code, (args,p.returncode,p.stderr)\n    if code:\n        assert not p.stdout and len(p.stderr.splitlines()) == 1, p\n    return p.stdout\nassert [r['age'] for r in json.loads(call('people.csv','--sort','-age','--format','json'))] == ['41','34','28','28','9','']\nassert call('--where','city ~ LISBON','--limit','0','people.csv','--count') == '2\\\\n'\nassert list(csv.reader(io.StringIO(call('--select','name,age','people.csv','--where','age >= 28','--sort','age','--limit','2')))) == [['name','age'],['Bo Chen','28'],['Eli Moss','28']]\nassert call('--format','table',data='a,b\\\\nx,yy\\\\n') == 'a  b\\\\n-  --\\\\nx  yy\\\\n'\nassert json.loads(call('--format','json',data='name,n\\\\n\\\"C\u00e9line\\\\nDupont\\\",1\\\\n')) == [{'name':'C\u00e9line\\\\nDupont','n':'1'}]\nassert call('--where','n < 3','--count',data='n\\\\n\\\"\\\"\\\\n2\\\\n10\\\\n') == '1\\\\n'\nfor args in [('--select','missing'),('--where','missing = 1'),('--sort','missing'),('--where','age == 3'),('--limit','-1'),('--limit','x'),('--format','xml'),('--oops',)]:\n    call('people.csv',*args,code=2)\ncall('/no/such/file',code=1)\nassert 'usage:' in call('--help')\nassert call('--sort','-n',data='n,id\\\\n2,a\\\\n,b\\\\n2,c\\\\n10,d\\\\n,e\\\\n') == 'n,id\\\\n10,d\\\\n2,a\\\\n2,c\\\\n,b\\\\n,e\\\\n'\nprint('All 18 CLI checks passed.')\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 subprocess, json, csv, io\n\ndef call(*args, data=None, code=0):\n    p = subprocess.run(['python3','csvq.py',*args],input=data,text=True,capture_output=True)\n    assert p.returncode == code, (args,p.returncode,p.stderr)\n    if code:\n        assert not p.stdout and len(p.stderr.splitlines()) == 1, p\n    return p.stdout\nassert [r['age'] for r in json.loads(call('people.csv','--sort','-age','--format','json'))] == ['41','34','28','28','9','']\nassert call('--where','city ~ LISBON','--limit','0','people.csv','--count') == '2\\\\n'\nassert list(csv.reader(io.StringIO(call('--select','name,age','people.csv','--where','age >= 28','--sort','age','--limit','2')))) == [['name','age'],['Bo Chen','28'],['Eli Moss','28']]\nassert call('--format','table',data='a,b\\\\nx,yy\\\\n') == 'a  b\\\\n-  --\\\\nx  yy\\\\n'\nassert json.loads(call('--format','json',data='name,n\\\\n\\\"C\u00e9line\\\\nDupont\\\",1\\\\n')) == [{'name':'C\u00e9line\\\\nDupont','n':'1'}]\nassert call('--where','n < 3','--count',data='n\\\\n\\\"\\\"\\\\n2\\\\n10\\\\n') == '1\\\\n'\nfor args in [('--select','missing'),('--where','missing = 1'),('--sort','missing'),('--where','age == 3'),('--limit','-1'),('--limit','x'),('--format','xml'),('--oops',)]:\n    call('people.csv',*args,code=2)\ncall('/no/such/file',code=1)\nassert 'usage:' in call('--help')\nassert call('--sort','-n',data='n,id\\\\n2,a\\\\n,b\\\\n2,c\\\\n10,d\\\\n,e\\\\n') == 'n,id\\\\n10,d\\\\n2,a\\\\n2,c\\\\n,b\\\\n,e\\\\n'\nprint('All 18 CLI checks passed.')\nPY\"", "aggregated_output": "All 18 CLI checks passed.\n", "exit_code": 0, "status": "completed"}}
{"type": "item.completed", "item": {"id": "item_5", "type": "agent_message", "text": "Implemented [csvq.py](/home/bob/usecase-runs/batch/out/gpt-6.1-sol/163_e04/work/csvq.py) using only Python\u2019s standard library.\n\nVerified filtering, stable sorting, output formats, stdin, Unicode, counts, limits, and error handling.\n\n```bash\npython3 csvq.py people.csv --where 'age >= 28' --sort -age --format table\n```"}}
{"type": "turn.completed", "usage": {"input_tokens": 84720, "cached_input_tokens": 71936, "cache_write_input_tokens": 0, "output_tokens": 2653, "reasoning_output_tokens": 95}}

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