Multi-Review Aggregation

Dispatch N independent code reviews and aggregate findings. Each reviewer catches different bugs -- union preserves the long tail that single-shot misses.

Research basis: SWR-Bench (arXiv 2509.01494) -- N independent reviews: 43.67% F1 improvement, 118.83% recall improvement. Diminishing returns past N=5; N=3 captures most improvement.

Core principle: Independence via separate Task dispatches -- same base prompt, no shared context.

N Selection by Tier

Tier	N Reviews	Rationale
max-20x	3	Quality priority -- full aggregation
max-5x	3	Balanced -- same recall benefit
pro/api	1	Budget priority -- single review

When N=1, skip this skill -- use standard single code review.

Parallel Dispatch Pattern

After spec review passes, dispatch N independent reviews (run_in_background=True, each gets "Reviewer i of N"). If all approve with 0 Critical/Important: fast path, skip aggregation. Otherwise dispatch aggregator (haiku model).

Full dispatch code: see references/dispatch-code.md. Aggregator prompt: see ./aggregator-prompt.md.

Aggregation Algorithm

Fast Path

ALL N reviewers return VERDICT: APPROVE with CRITICAL: 0 and IMPORTANT: 0 -> skip aggregation. Unanimous clean = review output.

Severity Voting (When Any Reviewer Raises Issues)

Condition	Result
All reviewers agree on severity	Keep that severity
Reviewers disagree	Use highest severity
Lone finding Critical or Important	Keep original severity (no downgrade)
Lone finding Minor	Downgrade to Suggestion
Lone finding BUT security or data-loss	Keep original severity (no downgrade)

Severity levels: Critical > Important > Minor > Suggestion

Verdict

"Ready to merge: Yes" -- zero Critical AND zero Important AND majority approved
"Ready to merge: With fixes" -- only Minor/Suggestion after aggregation
"Ready to merge: No" -- any Critical or Important remain

Full deduplication/merging rules: see references/aggregation-details.md.

Output Format

## Strengths
- [strength] [Reviewers: 1, 2, 3]

## Issues
### Critical / Important / Minor / Suggestion
- [issue] [Reviewers: N, N] -- file:line
  (note downgrade/security provenance as applicable)

## Assessment
Ready to merge: [Yes/With fixes/No]
Reviewers: X/N approved, Y requested changes

Full format spec: see references/output-provenance.md.

Red Flags

Never:

Share context between reviewers (defeats independence)
Use N>1 for pro/api tier (budget constraint)
Skip aggregation when reviewers disagree
Downgrade security findings even as lone findings

Always:

Dispatch all N reviews in parallel
Include reviewer number in each dispatch prompt
Use haiku for aggregation
Record per-reviewer metrics separately

Reference Files

references/dispatch-code.md: Full dispatch flow with on_spec_review_pass handler
references/aggregation-details.md: Deduplication, strengths merging, malformed output, timeout recovery
references/output-provenance.md: Provenance annotation rules and full output format spec
references/metrics-and-cost.md: Per-reviewer metric keys, cost impact, per-tier breakdown
aggregator-prompt.md: Aggregator Task dispatch prompt template

multi-review-aggregation