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Get Started Free →Fresh adversarial code review with binary PASS/FAIL verdicts, evidence citations, and anchoring bias prevention via fresh reviewer spawning.
.claude/skills/a5c-ai-adversarial-review/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | -9% | 0% |
| case-02 | ✗→✓ | ▲ Improved | -22% | 0% |
| case-03 | ✗→✓ | ▲ Improved | -29% | 0% |
| case-04 | ✗→✓ | ▲ Improved | -63% | 0% |
| case-05 | ✗→✓ | ▲ Improved | -49% | 0% |
| Aspect | Collaborative | Adversarial | |--------|--------------|-------------| | Goal | Help improve code | Verify spec compliance | | Verdict | Suggestions | Binary PASS/FAIL | | Evidence | Optional | Required (file:line) | | Reviewer | Can be reused | Must be fresh | | Context | Shared | Independent |
On re-review after FAIL, a NEW reviewer instance spawns with no memory of the previous review. This prevents anchoring bias where a reviewer fixates on previously identified issues.
Invoke as part of: methodologies/metaswarm/metaswarm-execution-loop (Phase 3)
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 7,035 | 5,478 | -22% | 1 | 1 | 0% | 1,171 | 1,060 | -9% | 0 | 0 | — |
case-02 | fail→pass | 6,718 | 3,933 | -41% | 1 | 1 | 0% | 1,109 | 862 | -22% | 0 | 0 | — |
case-03 | fail→pass | 10,325 | 5,828 | -44% | 1 | 1 | 0% | 1,766 | 1,247 | -29% | 0 | 0 | — |
case-04 | fail→pass | 10,523 | 2,729 | -74% | 1 | 1 | 0% | 1,747 | 645 | -63% | 0 | 0 | — |
case-05 | fail→pass | 11,911 | 4,012 | -66% | 1 | 1 | 0% | 1,879 | 953 | -49% | 0 | 0 | — |
case-06 | fail→pass | 9,113 | 2,992 | -67% | 1 | 1 | 0% | 1,477 | 718 | -51% | 0 | 0 | — |
case-07 | fail→pass | 8,444 | 4,066 | -52% | 1 | 1 | 0% | 1,357 | 982 | -28% | 0 | 0 | — |
case-08 | fail→pass | 11,183 | 1,961 | -82% | 1 | 1 | 0% | 1,856 | 504 | -73% | 0 | 0 | — |
case-09 | pass→pass | 13,465 | 5,777 | -57% | 1 | 1 | 0% | 1,993 | 1,173 | -41% | 0 | 0 | — |
case-10 | fail→fail | 11,140 | 8,168 | -27% | 1 | 1 | 0% | 1,689 | 1,410 | -17% | 0 | 0 | — |
case-11 | fail→fail | 9,482 | 2,417 | -75% | 1 | 1 | 0% | 1,546 | 539 | -65% | 0 | 0 | — |
case-12 | fail→pass | 14,472 | 9,483 | -34% | 1 | 1 | 0% | 2,537 | 1,966 | -23% | 0 | 0 | — |
case-13 | fail→pass | 14,752 | 3,602 | -76% | 1 | 1 | 0% | 2,353 | 799 | -66% | 0 | 0 | — |
case-14 | fail→pass | 11,875 | 2,700 | -77% | 1 | 1 | 0% | 1,777 | 644 | -64% | 0 | 0 | — |
case-15 | fail→fail | 7,271 | 4,781 | -34% | 1 | 1 | 0% | 1,177 | 935 | -21% | 0 | 0 | — |
case-16 | fail→pass | 9,540 | 1,534 | -84% | 1 | 1 | 0% | 1,420 | 454 | -68% | 0 | 0 | — |
case-17 | fail→pass | 17,529 | 5,207 | -70% | 1 | 1 | 0% | 2,817 | 1,005 | -64% | 0 | 0 | — |
case-18 | fail→fail | 13,035 | 2,711 | -79% | 1 | 1 | 0% | 2,105 | 561 | -73% | 0 | 0 | — |
case-19 | fail→pass | 8,560 | 3,024 | -65% | 1 | 1 | 0% | 1,444 | 707 | -51% | 0 | 0 | — |
case-20 | fail→fail | 12,917 | 6,661 | -48% | 1 | 1 | 0% | 2,169 | 1,285 | -41% | 0 | 0 | — |
case-21 | fail→fail | 11,081 | 8,405 | -24% | 1 | 1 | 0% | 1,884 | 1,625 | -14% | 0 | 0 | — |
case-22 | fail→fail | 10,811 | 8,143 | -25% | 1 | 1 | 0% | 1,800 | 1,463 | -19% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +64 percentage points is the difference between those two pass rates over the 22 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.