[Feature]: Persist Momus review verdicts to disk

[francisfuzz]

Prerequisites

• I will write this issue in English (see our Language Policy)
• I have searched existing issues and discussions to avoid duplicates
• This feature request is specific to oh-my-opencode (not OpenCode core)
• I have read the documentation or asked an AI coding agent with this project's GitHub URL loaded and couldn't find the answer

Problem Description

Momus reviews are expensive (1-2 min on gpt-5.4 xhigh, 32k thinking budget) but ephemeral. Once the session ends, the verdict is gone — no record of what was checked, what was flagged, or how many cycles a plan went through before approval.

This means no audit trail when approved plans fail during execution, no revision history for debugging multi-cycle review loops, and wasted cost when sessions compact and Momus re-reviews from scratch.

Proposed Solution

Write verdicts alongside plans. Momus stays read-only — the orchestrator writes the artifact after receiving the result.

.sisyphus/plans/
    implement-auth.md
    implement-auth.reviews/
      001-reject.md
      002-okay.md

Each file captures verdict, timestamp, model, plan hash (to detect changes between reviews), duration, and a summary of references checked.

Integration point: After task(subagent_type="momus") returns, either in the Sisyphus prompt path or as a lightweight hook. Momus needs zero changes — no new tools, no prompt modifications.

Reusable infra: Boulder state (src/features/boulder-state/storage.ts) already reads/writes .sisyphus/ to disk. Plans already live at .sisyphus/plans/*.md, so .reviews/ is a natural sibling.

Alternatives Considered

boulder.json — Compact but not human-readable. Developers want to glance at review history in their editor, not parse JSON. Markdown is git-friendly and mirrors the plan format.

Additional Context

Complementary to #1013 (parallel reviews), #1152 (multi-model quorum), and #2290 (compound learning) — faster or more accurate reviews are still ephemeral without persistence.

Feature Type

New Hook

Contribution

• I'm willing to submit a PR for this feature
• I can help with testing
• I can help with documentation