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Get Started Free →Coordinate multi-layer security scanning and hardening across application, infrastructure, and compliance controls.
.claude/skills/dokhacgiakhoa-security-scanning-security-hardening/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 47% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 19% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 7% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 1% | 0% |
| case-16 | ✗→✓ | ▲ Improved | 43% | 0% |
Implement comprehensive security hardening with defense-in-depth strategy through coordinated multi-agent orchestration:
Extended thinking: This workflow implements a defense-in-depth security strategy across all application layers. It coordinates specialized security agents to perform comprehensive assessments, implement layered security controls, and establish continuous security monitoring. The approach follows modern DevSecOps principles with shift-left security, automated scanning, and compliance validation. Each phase builds upon previous findings to create a resilient security posture that addresses both current vulnerabilities and future threats.]
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 34,419 | 51,856 | +51% | 1 | 1 | 0% | 5,934 | 8,716 | +47% | 0 | 0 | — |
case-02 | pass→pass | 20,075 | 23,990 | +20% | 1 | 1 | 0% | 3,334 | 4,613 | +38% | 0 | 0 | — |
case-03 | fail→pass | 16,466 | 14,898 | -10% | 1 | 1 | 0% | 2,664 | 3,176 | +19% | 0 | 0 | — |
case-04 | fail→fail | 17,334 | 22,486 | +30% | 1 | 1 | 0% | 1,835 | 2,897 | +58% | 0 | 0 | — |
case-05 | pass→pass | 17,436 | 17,604 | +1% | 1 | 1 | 0% | 2,708 | 3,639 | +34% | 0 | 0 | — |
case-06 | pass→fail | 18,730 | 24,372 | +30% | 1 | 1 | 0% | 2,952 | 4,520 | +53% | 0 | 0 | — |
case-07 | fail→pass | 25,260 | 22,430 | -11% | 1 | 1 | 0% | 3,856 | 4,135 | +7% | 0 | 0 | — |
case-08 | pass→pass | 18,054 | 17,676 | -2% | 1 | 1 | 0% | 3,012 | 3,843 | +28% | 0 | 0 | — |
case-09 | pass→pass | 25,214 | 31,453 | +25% | 1 | 1 | 0% | 3,942 | 5,342 | +36% | 0 | 0 | — |
case-10 | fail→pass | 18,439 | 14,589 | -21% | 1 | 1 | 0% | 3,194 | 3,241 | +1% | 0 | 0 | — |
case-11 | pass→pass | 20,901 | 22,942 | +10% | 1 | 1 | 0% | 3,373 | 4,084 | +21% | 0 | 0 | — |
case-12 | pass→pass | 20,045 | 18,441 | -8% | 1 | 1 | 0% | 2,951 | 3,921 | +33% | 0 | 0 | — |
case-13 | pass→pass | 18,490 | 14,966 | -19% | 1 | 1 | 0% | 2,773 | 3,001 | +8% | 0 | 0 | — |
case-14 | pass→pass | 18,373 | 22,512 | +23% | 1 | 1 | 0% | 3,068 | 4,695 | +53% | 0 | 0 | — |
case-15 | pass→pass | 17,191 | 20,134 | +17% | 1 | 1 | 0% | 2,784 | 3,952 | +42% | 0 | 0 | — |
case-16 | fail→pass | 18,299 | 25,910 | +42% | 1 | 1 | 0% | 3,375 | 4,818 | +43% | 0 | 0 | — |
case-17 | fail→fail | 17,516 | 15,140 | -14% | 1 | 1 | 0% | 2,790 | 3,412 | +22% | 0 | 0 | — |
case-18 | pass→pass | 21,703 | 20,069 | -8% | 1 | 1 | 0% | 3,251 | 4,198 | +29% | 0 | 0 | — |
case-19 | fail→fail | 21,000 | 19,428 | -7% | 1 | 1 | 0% | 2,955 | 3,839 | +30% | 0 | 0 | — |
case-20 | fail→fail | 9,348 | 16,754 | +79% | 1 | 1 | 0% | 844 | 2,160 | +156% | 0 | 0 | — |
case-21 | pass→fail | 8,471 | 6,631 | -22% | 1 | 1 | 0% | 1,124 | 1,235 | +10% | 0 | 0 | — |
case-22 | pass→pass | 16,654 | 24,065 | +44% | 1 | 1 | 0% | 2,267 | 2,530 | +12% | 0 | 0 | — |
case-23 | pass→pass | 14,803 | 19,075 | +29% | 1 | 1 | 0% | 2,498 | 3,655 | +46% | 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. 23 cases were attempted. The headline lift of +13 percentage points is the difference between those two pass rates over the 23 comparable cases. 2 cases got worse with the skill loaded, and they are included in that figure.
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.