The Prompting Company

Benchmark report

Task verified

2m 24s elapsed

The saved attempt met the documented success criterion.

Experience score

98/ 100

Agent-Ready
  • AInstall
  • SAuth
  • SExecute
  • SDocs
  • SCurrent
Experience measures friction in the tested task. The verdict says whether it succeeded.
Agent profile for this run: Install A, Auth S, Execute S, Docs S, Current SAInstallSAuthSExecuteSDocsSCurrent
Agent profile · this run
Judge's note · what slowed the agent most
The PEP 668 externally-managed-environment error on `pip install duckdb`, which cost one extra step to work around with a venv.

Where the time went

2:24 agent time
  • Starting0:02
  • Research0:18
  • Attempt1:16
  • Verify0:47
2m 24sTotal elapsed
0:57Time to first success
0:00Waited on the owner

Judge reason

Saved artifacts prove the full planned DuckDB workflow ran via the real duckdb Python package (1.5.6, installed in a venv after PEP 668 blocked system pip). duckdb_run.log shows DESCRIBE SELECT * FROM read_csv('sales.csv') auto-detecting exactly 4 columns region/product/units/price with units=BIGINT and price=DOUBLE; the GROUP BY region aggregation returned exactly two rows, north 9 / 37.5 and south 6 / 22.5 (matching the CSV in /workspace/home/sales.csv: north 3+2+4=9, 7.5+20+10=37.5; south 5+1=6, 12.5+10=22.5); COPY (...) TO 'region_totals.parquet' (FORMAT parquet) produced a 469-byte file (ls -la and sha256 in evidence.json), and read_parquet('region_totals.parquet') read back the same two rows (9.0/37.5, 6.0/22.5). A separate verification script printed PASS for all 9 criterion checks with no errors in the final run. DuckDB is an embedded keyless library, so no credentials were involved.

Attempt record

  1. —First success verified

Attempt artifacts saved.