Dispatch fresh reviewer agents with clean contexts. Reviewers have no shared state — they find what the coding agent missed.

Distinct from audit-code: audit-code is self-review (internal). This skill dispatches external agents.

Solo developer note: Reviewer agents replace the human reviewer.

Run audit-code first. Don’t waste reviewer attention on hygiene issues you could have caught yourself.

Use two independent reviewers (Reviewer A and Reviewer B) with no shared context between them or the coding agent.

Iteration loop (max MAX_REVIEW_ITERATIONS):

1. Dispatch Reviewer A and Reviewer B in parallel with identical briefs but separate contexts.
2. Collect both reports. Each categorizes findings: must-fix / should-fix / consider.
3. AND-gate: If either reviewer has must-fix findings → FAIL round. Run respond-review, fix, re-dispatch both reviewers.
4. If both pass (zero must-fix, score ≥ 94% each) → review complete.
5. After 5 iterations without dual pass → stop; report “Review cap exhausted (5/5). Human decision required.” Do not merge.

HARD GATE — Single-reviewer pass is insufficient. Partial agreement does not satisfy the AND-gate.

Write a self-contained brief for each reviewer. Include:

• What was built (feature description, not implementation)
• Which files changed (the diff context)
• What specs/ artifacts are relevant (active epics/eNN-*.yaml, requirements/SCOPE_LATEST.yaml, bugs/BUG-*.md)
• What CONVENTIONS.md requires
• What the verify command is
• What you’re most uncertain about (where you want fresh eyes)
• Security focus — If the epic has a specs/security/epics/<id>/THREAT_MODEL.md, include the relevant vulnerability categories as reviewer focal points. Also include the false-positive exclusion rules so the reviewer avoids known-safe patterns. Tag the review as security-sensitive: true if THREAT_MODEL risk is HIGH+.

Beyond the mandatory dual-blind pair (e45s07), optionally dispatch N dimension-specific subagents in one message — one check per agent for broader coverage (OpenAI Codex code-review-* pattern):

Santa Method still applies: each agent is blind; AND-gate uses Reviewer A + B scores. Fan-out agents feed findings into respond-review but do not replace the dual-blind pair.

Use the Agent tool twice with completely fresh contexts. Each prompt must be self-contained — no references to “our conversation” or “what we discussed.”

You are code reviewer [A|B]. Review the following code changes independently.

Context: [feature description]
CONVENTIONS.md rules: [paste relevant sections]
Active epic shard: [paste or summarize from specs/epics/]

Diff: [paste git diff or describe changed files]

Verify command: [runnable command]

Review for:
1. Correctness — does the code do what was intended?
2. CONVENTIONS.md compliance — are all rules followed?
3. Test quality — do tests verify behavior (not implementation)?
4. Design — are there simpler or more robust approaches?
5. Edge cases — what inputs or states could cause failures?
6. Security — any injection, auth, or data exposure risks?

For each finding, categorize as: must-fix / should-fix / consider.
Run the verify command and report the result.

When reviewers return:

• Read every finding from both reports before acting on any
• Note each verify command result
• Compute quality score per reviewer: 100 × (total_items − must_fix − should_fix) / total_items
• AND-gate check: both scores ≥ 94% and zero must-fix from both?

HARD GATE — If either score < 94% or either has must-fix → FAIL round. Run respond-review first. The 94% threshold also applies to npm run compliance (scripts/audit-compliance.sh).

Pass combined findings to respond-review to categorize and apply fixes. Increment iteration counter. Re-dispatch both reviewers until AND-gate passes or iteration 3 exhausted.

Report to user: “Review round [N/3]. Reviewer A: [score], Reviewer B: [score]. AND-gate: [PASS|FAIL].”

→ verify: grep -q 'AND-gate' skills/request-review/SKILL.md && grep -q 'max 3' skills/request-review/SKILL.md && echo OK