Four probes were written from a blank file and each re-learned the same lessons
by losing a run: that a flat run cannot be told from a frozen guest without a
stall witness, that results held to the end of a run are destroyed by a turn
timeout, that a roster count which is not the stage's member count means a
different stage loaded and must be discarded, and that a run's witness state has
to be read before its numbers. Writing each lesson down did not stop the next
probe repeating it, because each probe started from nothing.
probeharness.py makes them structural. Probe(baseline=N) discovers the roster,
rescans up to five times and refuses to start if the count never reaches the
baseline. The witness is calibrated on construction, sampled by tick() and
reported by status() and summary(), so a probe cannot forget it, and when no
witness is found it reports UNVALIDATED rather than zero stalls. emit() flushes
on every line. craft(), strengths(), alive() and heap() supply the
roster-to-craft link, per-record liveness and the raw heap, so a new probe
writes only its own logic.
Verified rather than asserted: deploy_probe.py reimplements the per-record
deployment watch on top of it in about forty lines against wave7_probe's
hundred and fifty, and its first live run was clean -- 116 roster records, 32
witnesses at 10/s, zero stalled samples, seven losses tracked, and the TSV
written incrementally. Nothing about the result is new, which is the point: the
harness reproduces a known-good measurement.
The existing probes are deliberately not ported. They work, and rewriting them
would risk changing results other documents cite. New probes should use the
harness; old ones should be ported when they next need a change.
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