One reproducible failure in a custom Python OpenAI or API step. I diagnose the root cause implement the smallest useful repair add a regression or acceptance check and return one-command verification within 48 hours after scope materials and a funded milestone are ready.

Included

One authorized repository or redacted reproduction

One agreed failure

The smallest useful patch

At least one relevant regression or acceptance check

make verify or an equivalent one-command check

A concise handoff and one scope-limited revision requested within 7 days

Typical fits include a failing OpenAI API call structured-output validation a webhook or data-mapping defect unsafe retry classification or a scheduled Python task or CLI that no longer completes.

Not included a new end-to-end automation production deployment ongoing operations penetration testing shared passwords or long-lived keys unapproved client data or unlimited revisions.

Before work starts we freeze up to three observable checks. The 48-hour clock begins only after the baseline reproduces required materials are available scope is approved and the USD 149 milestone is funded. Synthetic or redacted data is the default. If the agreed checks cannot pass within the frozen scope and environment the milestone is cancelled or refunded under Contra rules.