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lukaszraczylo
d929101af4
Two issues surfaced by running ADAM's /reflect loop on a large real journal
(4015 entries, 119 sessions) — both caused false/broken auto-apply behavior.
1. A/B over-reported regressions (adam-ab-measure.mjs).
Regressions were measured on RAW originating-signal counts pre vs post. On a
busy, growing journal almost every signal count rises post-apply regardless
of whether the proposal helped — so the loop flagged 9 false "regressions"
(and would auto-roll-back good proposals). Now the delta is computed on the
signal's SHARE of total activity (rate = count / window-total). Falls back to
the raw-count delta when the signal is the only activity in the window
(preserves prior behavior + all existing A/B tests). Output adds
raw_delta_pct, pre_total, post_total, normalized for transparency.
2. Memory frontmatter drift (agents/adam.md, SKILL.md).
The drafting protocol emitted flat `type:`/`originSessionId:` with a prose
`name`, but the live auto-memory store uses `name` = slug plus a
`metadata: {node_type, type, originSessionId}` block. Auto-applied memories
could fail to load/categorize. Protocol + apply-time validation now require
the live metadata.* schema and cross-checking against an existing file.
Tests: 132 -> 134. New: volume growth (raw +200%) with flat activity-share
classifies neutral, not regressed; a genuine share increase still classifies
regressed.