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evals/postmortem/ turns the one-off audit behind tracking issue #103563 into something anyone with a Hermes state.db copy (and optionally rotated agent.log*) can run on their own fan-out: forensics/ common.py discovers the run tree (root = most descendants, compression-rollover children excluded so cost buckets stay disjoint), fits pricing from estimated_cost_usd, and five lanes recompute the OBSERVED figures: tokens (buckets, depth/duration shares, context reconstruction, excess-cache-write proxy, cap replay), logcalls (per-call cache behaviour from agent.log with coverage printed first; strict and loose plateau definitions reported separately), delegation (timeouts, orphaned children, polling hours, batch-join withheld child-hours, truncated summaries), tools (hardline blocks, foreground refusals, whole-file rewrites), goal_loop (nudges, parked barrier), rework (public-surface drop at PR open + post-open commit inventory). Every figure is labeled OBSERVED or MODELED. live_ab/ the per-PR A/Bs (real code paths, fake providers, temp HERMES_HOME), paths from argv. review_probes/ the independent /review's probes, credited and adapted; each reproduced a round-1 defect and the fixed head must pass it. run.py runs the offline probes against one or two checkouts and prints PASS/FAIL side by side (--live adds the ones that spend cents). tests/ synthetic-DB smoke test for the lanes and runner. On the run's DB the lanes reproduce the tracking issue's population exactly (1,394 sessions, 93,284 calls, $19,302.59; cache_write $11,159.76) and on main vs an integration checkout of the 13 PRs the runner shows every probe FAIL -> PASS (two guard-only probes pass on both, noted in run.py). The trajectories are deliberately not shipped: the DB holds 51,956 home paths, 5,341 e-mails, private IPs, chat ids and real-shaped credentials in tool output. The lane reports and recomputed JSON are in a secret gist linked from #103563.
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