Reduce repeated high-token auto-review runs on stale snapshots

[shiny-code-bot]

Problem

Auto-review has been spending substantial tokens on repeated detached/stale review snapshots. In cbusillo/codex-skills, the auto-review ledger reported:

• tokens=2036776t across recent runs
• high_burn=5
• run 168d4bd0-e694-4023-b7f6-1188095bae06: tokens=1467380t, findings later verified stale against current main
• run d494a552-6cf2-40b0-963c-dc1effbd4a24: tokens=190756t, useful but reviewing a detached snapshot rather than clearly scoped active target

This makes stale review prompts costly and increases noise around readiness decisions.

Desired Behavior

Reduce token burn for repeated or stale auto-review contexts.

Possible approaches:

• Cache review context and reuse summaries when the target snapshot has not changed.
• Detect when a finding's snapshot is no longer active and avoid launching another full review unless requested.
• Add a low-cost freshness/applicability preflight before high-context review.
• Cap repeated stale review prompts for the same finding/run family after current HEAD verification.
• Prefer compact diff/snapshot comparison before loading broad repo context.

Acceptance Criteria

• Repeated auto-review runs against unchanged detached snapshots consume little or no additional model budget.
• Stale/superseded findings do not trigger high-token review loops by default.
• The ledger or UI exposes enough token/cache diagnostics to confirm whether caching is working.
• Agents can still request a fresh full review explicitly when a stale finding appears suspicious or safety-critical.

Why This Matters

The auto-review system caught a real issue in the later run, so the feature is valuable. But repeated stale high-token runs make review expensive and noisy. A cheap applicability/cache layer would preserve signal while keeping the system practical for long-running coding sessions.