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Get Started Free →Masscan Integration - High-Speed Port Scanner
.claude/skills/shadd0wtaka-masscan/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 25% | 0% |
| case-02 | ✗→✓ | ▲ Improved | 68% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 31% | 0% |
| case-04 | ✗→✓ | ▲ Improved | -65% | 0% |
| case-06 | ✗→✓ | ▲ Improved | -44% | 0% |
Masscan Integration - High-Speed Port Scanner
Category: scanning — Port & Service Scanning
Masscan Integration - High-Speed Port Scanner Schneller als Nmap für große Netzwerke
python# Auto-registered in tool_registry under "scanning" result = await tool_orchestrator.execute("masscan_integration", target="example.com")
bashmasscan --help
deep-recon --tool masscan_integration --target example.comscanningzen-agents_agent_run agent_type=scanning tool=masscan_integrationPOST /tools/execute with {"tool_name": "masscan_integration", "target": "example.com"}| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 9,205 | 9,817 | +7% | 1 | 1 | 0% | 1,674 | 2,094 | +25% | 0 | 0 | — |
case-02 | fail→pass | 8,408 | 12,531 | +49% | 1 | 1 | 0% | 1,473 | 2,478 | +68% | 0 | 0 | — |
case-03 | fail→pass | 10,061 | 10,269 | +2% | 1 | 1 | 0% | 1,580 | 2,067 | +31% | 0 | 0 | — |
case-04 | fail→pass | 21,384 | 2,807 | -87% | 1 | 1 | 0% | 1,804 | 637 | -65% | 0 | 0 | — |
case-05 | fail→fail | 7,982 | 8,736 | +9% | 1 | 1 | 0% | 722 | 1,009 | +40% | 0 | 0 | — |
case-06 | fail→pass | 8,537 | 2,910 | -66% | 1 | 1 | 0% | 1,234 | 690 | -44% | 0 | 0 | — |
case-07 | pass→pass | 8,494 | 2,071 | -76% | 1 | 1 | 0% | 1,200 | 478 | -60% | 0 | 0 | — |
case-08 | pass→pass | 10,467 | 1,505 | -86% | 1 | 1 | 0% | 1,842 | 379 | -79% | 0 | 0 | — |
case-09 | fail→pass | 8,073 | 4,009 | -50% | 1 | 1 | 0% | 1,441 | 654 | -55% | 0 | 0 | — |
case-10 | fail→pass | 8,870 | 4,999 | -44% | 1 | 1 | 0% | 1,551 | 1,101 | -29% | 0 | 0 | — |
case-11 | fail→pass | 8,796 | 1,962 | -78% | 1 | 1 | 0% | 1,411 | 485 | -66% | 0 | 0 | — |
case-12 | fail→pass | 7,754 | 2,954 | -62% | 1 | 1 | 0% | 1,275 | 660 | -48% | 0 | 0 | — |
case-13 | pass→pass | 13,022 | 7,008 | -46% | 1 | 1 | 0% | 1,972 | 1,317 | -33% | 0 | 0 | — |
case-14 | pass→pass | 4,551 | 1,636 | -64% | 1 | 1 | 0% | 690 | 435 | -37% | 0 | 0 | — |
case-15 | pass→pass | 13,424 | 8,678 | -35% | 1 | 1 | 0% | 2,239 | 1,717 | -23% | 0 | 0 | — |
case-16 | fail→pass | 5,170 | 3,736 | -28% | 1 | 1 | 0% | 915 | 964 | +5% | 0 | 0 | — |
case-17 | pass→pass | 8,833 | 2,221 | -75% | 1 | 1 | 0% | 1,473 | 588 | -60% | 0 | 0 | — |
case-18 | pass→pass | 7,191 | 2,826 | -61% | 1 | 1 | 0% | 1,358 | 765 | -44% | 0 | 0 | — |
case-19 | pass→pass | 12,629 | 11,850 | -6% | 1 | 1 | 0% | 2,023 | 2,174 | +7% | 0 | 0 | — |
case-20 | pass→pass | 14,019 | 16,690 | +19% | 1 | 1 | 0% | 2,354 | 1,558 | -34% | 0 | 0 | — |
case-21 | pass→pass | 11,655 | 8,723 | -25% | 1 | 1 | 0% | 2,160 | 1,982 | -8% | 0 | 0 | — |
case-22 | pass→pass | 13,808 | 8,152 | -41% | 1 | 1 | 0% | 2,335 | 1,689 | -28% | 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 +45 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.