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Get Started Free →This skill should be used when the user asks to "intercept HTTP traffic", "modify web requests", "use Burp Suite for testing", "perform web vulnerability scanning", "test with Burp Repeater", "analyze HTTP history", or "configure proxy for web testing". It provides comprehensive guidance for using Burp Suite's core features for web application security testing.
.claude/skills/dokhacgiakhoa-burp-suite-web-application-testing/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 27% | 0% |
| case-16 | ✓→✗ | ▼ Worse | 9% | 0% |
| case-02 | ✓→✓ | ＝ Same ✓ | 8% | 0% |
| case-03 | ✓→✓ | ＝ Same ✓ | 53% | 0% |
| case-04 | ✓→✓ | ＝ Same ✓ | 51% | 0% |
Execute comprehensive web application security testing using Burp Suite's integrated toolset, including HTTP traffic interception and modification, request analysis and replay, automated vulnerability scanning, and manual testing workflows. This skill enables systematic discovery and exploitation of web application vulnerabilities through proxy-based testing methodology.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 16,356 | 41,648 | +155% | 1 | 1 | 0% | 3,121 | 3,963 | +27% | 0 | 0 | — |
case-02 | pass→pass | 8,383 | 5,651 | -33% | 1 | 1 | 0% | 1,497 | 1,619 | +8% | 0 | 0 | — |
case-03 | pass→pass | 6,165 | 4,925 | -20% | 1 | 1 | 0% | 1,045 | 1,603 | +53% | 0 | 0 | — |
case-04 | pass→pass | 8,915 | 11,293 | +27% | 1 | 1 | 0% | 1,065 | 1,603 | +51% | 0 | 0 | — |
case-05 | pass→pass | 4,330 | 6,987 | +61% | 1 | 1 | 0% | 832 | 1,269 | +53% | 0 | 0 | — |
case-06 | pass→pass | 9,940 | 6,693 | -33% | 1 | 1 | 0% | 1,805 | 1,807 | +0% | 0 | 0 | — |
case-07 | pass→pass | 9,414 | 5,494 | -42% | 1 | 1 | 0% | 1,790 | 1,750 | -2% | 0 | 0 | — |
case-08 | pass→pass | 6,473 | 6,618 | +2% | 1 | 1 | 0% | 1,226 | 1,695 | +38% | 0 | 0 | — |
case-09 | pass→pass | 4,771 | 5,612 | +18% | 1 | 1 | 0% | 749 | 1,685 | +125% | 0 | 0 | — |
case-10 | pass→pass | 5,533 | 4,956 | -10% | 1 | 1 | 0% | 979 | 1,430 | +46% | 0 | 0 | — |
case-11 | pass→pass | 6,664 | 6,072 | -9% | 1 | 1 | 0% | 1,294 | 1,877 | +45% | 0 | 0 | — |
case-12 | pass→pass | 5,690 | 6,827 | +20% | 1 | 1 | 0% | 995 | 1,829 | +84% | 0 | 0 | — |
case-13 | pass→pass | 7,977 | 11,939 | +50% | 1 | 1 | 0% | 1,399 | 1,925 | +38% | 0 | 0 | — |
case-14 | pass→pass | 15,126 | 9,066 | -40% | 1 | 1 | 0% | 2,628 | 2,303 | -12% | 0 | 0 | — |
case-15 | pass→pass | 9,218 | 6,313 | -32% | 1 | 1 | 0% | 1,658 | 1,755 | +6% | 0 | 0 | — |
case-16 | pass→fail | 11,151 | 6,512 | -42% | 1 | 1 | 0% | 1,632 | 1,777 | +9% | 0 | 0 | — |
case-17 | pass→pass | 17,625 | 6,928 | -61% | 1 | 1 | 0% | 1,494 | 1,885 | +26% | 0 | 0 | — |
case-18 | pass→pass | 11,445 | 17,584 | +54% | 1 | 1 | 0% | 1,248 | 2,322 | +86% | 0 | 0 | — |
case-19 | pass→pass | 14,214 | 8,679 | -39% | 1 | 1 | 0% | 2,336 | 2,143 | -8% | 0 | 0 | — |
case-20 | pass→pass | 19,784 | 24,230 | +22% | 1 | 1 | 0% | 3,338 | 4,338 | +30% | 0 | 0 | — |
case-21 | pass→pass | 16,343 | 12,902 | -21% | 1 | 1 | 0% | 2,429 | 3,097 | +28% | 0 | 0 | — |
case-22 | pass→pass | 14,394 | 18,195 | +26% | 1 | 1 | 0% | 2,557 | 3,089 | +21% | 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 0 percentage points is the difference between those two pass rates over the 22 comparable cases. 1 case got worse with the skill loaded, and it is 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.