Design for making the brain governance observer rich enough for real
factor analysis. Surfaced during a discussion with the owner: the
observer is "paper-complete" but episodes lack the data factor analysis
needs — the outcome is a hardcoded "success", there is no decision
provenance (who chose the node — Claude autonomously, or the owner
forcing a method), no environment factors, no task grouping.
4-layer architecture:
- Layer 1 — episode schema v2: decision_provenance (+ counterfactual),
environment block, task_size, real outcome enum, task_ref.
- Layer 2 — capture: deterministic transcript parsing for all factors +
a one-line routing tag (owner-forced-method only).
- Layer 3 — two-sided enforcement: 3a routing-gate (Stop-hook blocks the
turn until the tag is present — unbypassable by Claude); 3b observer
self-discipline (silent failures become recorded observer_error
markers; coverage + registration verified by a controller).
- Layer 4 — analysis: /brain-retro infers real outcome from the next
episode's opening prompt, groups episodes into tasks, correlates
causal chains, builds the factor matrix.
Scope: everything except an independent agent-judge — that, plus
confusion_marker as a real judgment and real-time friction flags, is
phase 2 (separate spec).
Brainstormed via superpowers:brainstorming. Next: writing-plans.
Refs: ADR-011, spec 2026-05-19-brain-governance-design.md, Pravila §16.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Дмитрий
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