cookbook/environments/_01_first_environment/TEST_LOG.md
2.8.0 defines the learning zone as 0 < pass_rate < 1 (mixed pass/fail), so a k=4
file whose one hard task can land 4/4 saturates on unlucky runs.
Fix: chained-product-c (which shared the edge with chained-product-a and
saturated together this run) replaced with a second, independent calibrated chain
(chained-product-b, expected 10481347), so a zone row is reliable at k=4.
Grid (k=4): easy-product 4/4; chained-product-a 3/4 (0.75, zone);
chained-product-b 4/4.
basic.py (chained-product-a 2/4, zone) and with_fingerprints.py (a=2/4, b=3/4,
two zones) re-ran clean and unchanged.
Tested 2026-07-20 against gpt-5.5 through OpenAIResponses, Agno 2.7.4.
Status: PASS
Description: First typed-output environment with an easy anchor and two calibrated chained products at K=4.
Result: Live run completed with 12/12 scored attempts and no unscored attempts. Observed rates: easy-product 4/4 (1.00), chained-product-a 2/4 (0.50), chained-product-b 2/4 (0.50). Both chained rows landed in the true partial pass-rate learning zone.
Status: PASS
Description: Reads overall and per-task statistics from summary().
Result: Live run completed with 12/12 scored attempts and no unscored attempts. Observed rates: easy-product 4/4 (1.00), chained-product-a 3/4 (0.75), chained-product-c 4/4 (1.00). summary() reported an overall pass rate of 11/12 and correctly marked only chained-product-a as the learning-zone row.
Status: PASS
Description: Shows the environment and policy fingerprints retained on the result.
Result: Final live run completed with 12/12 scored attempts and no unscored attempts. Observed rates: easy-product 4/4 (1.00), chained-product-a 2/4 (0.50), chained-product-b 3/4 (0.75). The result matched the environment fingerprint. The first calibration used two different chained products and saturated at 4/4 on all three rows; those tasks were replaced before this passing run.