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Get Started Free →Expert skill in alarm focusing on security-systems domain applications. Covers 40 topics across security-systems domain. Includes 40 skill files covering ASPICE Level 3, AUTOSAR 4.4, ISO 21434, ISO 26262.
.claude/skills/pangzhenying2025-automotive-security-systems/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-15 | ✗→✓ | ▲ Improved | 150% | 0% |
| case-02 | ✓→✓ | ＝ Same ✓ | 167% | 0% |
| case-03 | ✓→✓ | ＝ Same ✓ | 137% | 0% |
| case-04 | ✓→✓ | ＝ Same ✓ | 209% | 0% |
| case-05 | ✓→✓ | ＝ Same ✓ | 219% | 0% |
40 skill files covering security-systems domain for automotive software engineering.
Expert in alarm for automotive security-systems systems.
Expert in alarm for automotive security-systems systems.
Expert in alarm for automotive security-systems systems.
Expert in alarm for automotive security-systems systems.
Expert in alarm for automotive security-systems systems.
Expert in alarm for automotive security-systems systems.
Expert in alarm for automotive security-systems systems.
Expert in alarm for automotive security-systems systems.
Expert in alarm for automotive security-systems systems.
Expert in alarm for automotive security-systems systems.
Expert in geofencing for automotive security-systems systems.
Expert in geofencing for automotive security-systems systems.
Expert in geofencing for automotive security-systems systems.
Expert in geofencing for automotive security-systems systems.
Expert in geofencing for automotive security-systems systems.
Expert in geofencing for automotive security-systems systems.
Expert in geofencing for automotive security-systems systems.
Expert in geofencing for automotive security-systems systems.
Expert in geofencing for automotive security-systems systems.
Expert in geofencing for automotive security-systems systems.
Expert in immobilizer for automotive security-systems systems.
Expert in immobilizer for automotive security-systems systems.
Expert in immobilizer for automotive security-systems systems.
Expert in immobilizer for automotive security-systems systems.
Expert in immobilizer for automotive security-systems systems.
Expert in immobilizer for automotive security-systems systems.
Expert in immobilizer for automotive security-systems systems.
Expert in immobilizer for automotive security-systems systems.
Expert in immobilizer for automotive security-systems systems.
Expert in immobilizer for automotive security-systems systems.
Expert in tracking for automotive security-systems systems.
Expert in tracking for automotive security-systems systems.
Expert in tracking for automotive security-systems systems.
Expert in tracking for automotive security-systems systems.
Expert in tracking for automotive security-systems systems.
Expert in tracking for automotive security-systems systems.
Expert in tracking for automotive security-systems systems.
Expert in tracking for automotive security-systems systems.
Expert in tracking for automotive security-systems systems.
Expert in tracking for automotive security-systems systems.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 27,832 | 28,544 | +3% | 1 | 1 | 0% | 6,210 | 10,534 | +70% | 0 | 0 | — |
case-02 | pass→pass | 14,399 | 34,206 | +138% | 1 | 1 | 0% | 2,599 | 6,945 | +167% | 0 | 0 | — |
case-03 | pass→pass | 18,406 | 10,748 | -42% | 1 | 1 | 0% | 2,648 | 6,280 | +137% | 0 | 0 | — |
case-04 | pass→pass | 12,499 | 10,469 | -16% | 1 | 1 | 0% | 1,980 | 6,115 | +209% | 0 | 0 | — |
case-05 | pass→pass | 16,575 | 34,960 | +111% | 1 | 1 | 0% | 3,297 | 10,503 | +219% | 0 | 0 | — |
case-06 | pass→pass | 15,510 | 24,454 | +58% | 1 | 1 | 0% | 3,003 | 8,552 | +185% | 0 | 0 | — |
case-07 | pass→pass | 8,126 | 10,660 | +31% | 1 | 1 | 0% | 1,571 | 6,427 | +309% | 0 | 0 | — |
case-08 | pass→pass | 9,419 | 5,473 | -42% | 1 | 1 | 0% | 1,826 | 5,252 | +188% | 0 | 0 | — |
case-09 | pass→pass | 12,457 | 7,561 | -39% | 1 | 1 | 0% | 2,386 | 5,697 | +139% | 0 | 0 | — |
case-10 | pass→pass | 14,452 | 12,117 | -16% | 1 | 1 | 0% | 2,227 | 6,458 | +190% | 0 | 0 | — |
case-11 | pass→pass | 12,823 | 15,276 | +19% | 1 | 1 | 0% | 2,289 | 6,940 | +203% | 0 | 0 | — |
case-12 | pass→pass | 11,491 | 4,452 | -61% | 1 | 1 | 0% | 1,970 | 5,017 | +155% | 0 | 0 | — |
case-13 | pass→pass | 9,159 | 6,822 | -26% | 1 | 1 | 0% | 1,345 | 5,506 | +309% | 0 | 0 | — |
case-14 | pass→pass | 13,093 | 14,372 | +10% | 1 | 1 | 0% | 2,320 | 7,224 | +211% | 0 | 0 | — |
case-15 | fail→pass | 11,156 | 6,051 | -46% | 1 | 1 | 0% | 2,129 | 5,317 | +150% | 0 | 0 | — |
case-16 | pass→pass | 11,674 | 2,929 | -75% | 1 | 1 | 0% | 2,095 | 4,875 | +133% | 0 | 0 | — |
case-17 | pass→pass | 9,103 | 7,635 | -16% | 1 | 1 | 0% | 1,425 | 5,439 | +282% | 0 | 0 | — |
case-18 | pass→pass | 11,043 | 5,608 | -49% | 1 | 1 | 0% | 1,710 | 5,224 | +205% | 0 | 0 | — |
case-19 | pass→pass | 13,927 | 8,646 | -38% | 1 | 1 | 0% | 1,757 | 5,533 | +215% | 0 | 0 | — |
case-20 | pass→pass | 11,394 | 9,606 | -16% | 1 | 1 | 0% | 1,764 | 5,868 | +233% | 0 | 0 | — |
case-21 | pass→pass | 11,300 | 13,154 | +16% | 1 | 1 | 0% | 2,030 | 6,510 | +221% | 0 | 0 | — |
case-22 | pass→pass | 11,502 | 11,681 | +2% | 1 | 1 | 0% | 2,059 | 6,360 | +209% | 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 +5 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.