Audit prospective comparison readiness and retain effort gaps
Assistant: codex Assistant-Model: gpt-6.1-sol Assistant-Session: 01a1045b-933d-7aa1-b2db-104557487a79
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@ -66,6 +66,9 @@ renew them. Historical snapshots retain their original schema-v1 assessments.
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undermine their scope. Never promote automatically from metric thresholds.
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Commands: `make evolution-report`, `make evolution-check`, `make evolution-test`.
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Generation writes both EvolutionReport.md and the machine-readable
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[ComparisonWindows.json](ComparisonWindows.json); checking rejects stale output
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in either artifact.
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The check rejects stale candidate hashes, missing references, inventory drift,
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invalid provenance, unknown identities, corrupted baseline candidate hashes and stale
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generated output. It does not
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@ -112,6 +115,21 @@ baseline or the selected retrospective entries. Prefer more independent validati
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when beliefs stabilize; broaden when new contexts expose missing decisions; repair
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structure when ambiguity prevents use. Low novelty alone is not a stopping rule.
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The window audit groups prospective entries by declared stream and comparison-group
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label, orders them by date/identity, and retains links to every registered protocol.
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Its three-cycle qualitative review trigger does not verify comparability: review
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evidence tier, question granularity, evaluation and accounting against those protocols
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first. Retrospective entries never join a window, even if later assigned effort or
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a matching label. Outcomes include corroboration and inconclusive work.
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The audit distinguishes positive research time, unknown time and recorded zero time.
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Unknown or zero effort permits qualitative discussion with limits but prevents
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effort comparison of the complete declared window. Do not silently discard those
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cycles or reconstruct their time from commits. A narrower window needs an explicit
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review explaining its boundary and retained exclusions. Readiness does not calculate
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a trend, declare a plateau or complete WP-0006 T03; that task needs an evidence-bearing
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review of useful comparable research, not a generated count.
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Keep both the unchanged candidate cohort and additions/removals visible when
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comparing snapshots. A growing inventory must not hide weakening evidence for old
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claims. Learning continues after milestones; finite workplans carry the next bounded
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