Read the artifact before you adopt the procedure. In the published `triage_gate.py`, `fixture_hash()` returns the first twelve characters of the sha256 of the test id, with a comment saying a real setup would hash the fixture files for that test [15]. Follow that into `classify()`. The recorded hash defaults to the current one when the test id is absent from the ledger [16], and every non-flake verdict writes the hash back under the same key [17]. Substitute the stub into the comparison and `current != recorded` is false on both paths: a new test is compared against itself, and a known test is compared against a value computed from the same string [3]. Class B is unreachable as shipped, so drift lands in the bucket the script labels deterministic regression [3]. That function is the line to write before you switch the gate on.
`RETRIES` is a module constant set to 3, and `QUARANTINE_DAYS` to 7 [14]. Three is generous for the cheap case and thin for the interesting one. A test that fails half the time comes up red three times running with probability 0.5 cubed, or 12.5 percent [2]. One coin-flip flake in eight therefore clears the re-run stage, clears the fixture check, and gets written down as a regression in the agent's code. Five re-runs would take that to 3.1 percent [4] and cost two more executions. Which of those you want depends on how long the test takes and how much you trust a verdict that sends work back to a model.
The quarantine entry carries a first-seen timestamp, a reason, and an expiry [10], seven days out by default [14]. Nothing in the script reads the expiry back, and the skipping of quarantined tests belongs to a pipeline the script does not include [18]. A timestamp no job ever reads is a to-do list with better formatting.
The other adoption cost is enumeration. Step two hashes the fixtures a test loads and compares them against the value at the last green commit [8], which assumes you can name those fixtures per test. Where snapshots and seeds are generated at session scope, that mapping is the project and the script is the easy part.
I would still take this trade in my context, which is a hosted pipeline where agent patches arrive faster than anyone reads logs. The value is not the code; it is that an unlabeled red build becomes one of three named jobs, which is impossible from the first log line alone [6]. I would build it in roughly the reverse of the article's order: real fixture hashing first, then the ledger and its reader, then tuning the retry count.
