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Get Started Free →Expert senior en architecture backend pour accompagner le développement (conception, implémentation, review, refactoring). Architecture hexagonale, DDD, SOLID, clean code, tests. Utiliser pour concevoir de nouvelles features, développer du code, reviewer, refactorer, ou résoudre des problèmes architecturaux.
.claude/skills/aiskillstore-backend-architect/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-03 | ✗→✓ | ▲ Improved | 95% | 0% |
| case-04 | ✗→✓ | ▲ Improved | -1% | 0% |
| case-16 | ✗→✓ | ▲ Improved | 72% | 0% |
| case-21 | ✓→✗ | ▼ Worse | 77% | 0% |
| case-07 | ✓→✓ | = Same ✓ | 42% | 0% |
Tu es un expert senior en architecture backend qui accompagne le développement tout au long du cycle :
Consulter architecture/ pour :
Consulter code-smells/ pour identifier :
Consulter solid-principles/ pour vérifier :
Appliquer les checklists de checklists/ :
Consulter examples/ pour des patterns recommandés
Organiser les feedbacks par priorité :
P0 - Bloquant : Problèmes critiques (architecture cassée, bugs majeurs) P1 - Important : Violations majeures (SOLID, code smells sérieux) P2 - Amélioration : Suggestions d'optimisation
Pour chaque point :
git diff : Voir les changementsgrep : Rechercher des patterns| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-07 | pass→pass | 23,550 | 29,168 | +24% | 1 | 1 | 0% | 2,543 | 3,600 | +42% | 0 | 0 | — |
case-01 | fail→fail | 10,683 | 14,783 | +38% | 1 | 1 | 0% | 1,218 | 2,117 | +74% | 0 | 0 | — |
case-06 | pass→pass | 17,142 | 20,552 | +20% | 1 | 1 | 0% | 1,770 | 3,044 | +72% | 0 | 0 | — |
case-02 | pass→pass | 19,595 | 17,471 | -11% | 1 | 1 | 0% | 2,542 | 2,959 | +16% | 0 | 0 | — |
case-03 | fail→pass | 13,987 | 13,958 | -0% | 1 | 1 | 0% | 1,224 | 2,381 | +95% | 0 | 0 | — |
case-04 | fail→pass | 10,237 | 9,932 | -3% | 1 | 1 | 0% | 1,355 | 1,336 | -1% | 0 | 0 | — |
case-05 | pass→pass | 18,309 | 17,824 | -3% | 1 | 1 | 0% | 2,426 | 3,015 | +24% | 0 | 0 | — |
case-08 | pass→pass | 22,339 | 41,632 | +86% | 1 | 1 | 0% | 1,267 | 2,306 | +82% | 0 | 0 | — |
case-09 | pass→pass | 14,597 | 15,646 | +7% | 1 | 1 | 0% | 1,727 | 2,661 | +54% | 0 | 0 | — |
case-10 | pass→pass | 9,907 | 11,518 | +16% | 1 | 1 | 0% | 771 | 1,871 | +143% | 0 | 0 | — |
case-11 | pass→pass | 11,857 | 19,684 | +66% | 1 | 1 | 0% | 1,227 | 2,605 | +112% | 0 | 0 | — |
case-21 | pass→fail | 12,095 | 26,154 | +116% | 1 | 1 | 0% | 1,154 | 2,037 | +77% | 0 | 0 | — |
case-12 | pass→pass | 13,728 | 29,757 | +117% | 1 | 1 | 0% | 1,335 | 2,167 | +62% | 0 | 0 | — |
case-13 | pass→pass | 8,972 | 10,982 | +22% | 1 | 1 | 0% | 635 | 1,776 | +180% | 0 | 0 | — |
case-14 | pass→pass | 25,407 | 26,370 | +4% | 1 | 1 | 0% | 977 | 2,428 | +149% | 0 | 0 | — |
case-15 | pass→pass | 16,021 | 29,679 | +85% | 1 | 1 | 0% | 1,582 | 2,847 | +80% | 0 | 0 | — |
case-16 | fail→pass | 19,209 | 23,886 | +24% | 1 | 1 | 0% | 1,807 | 3,102 | +72% | 0 | 0 | — |
case-17 | pass→pass | 19,888 | 33,671 | +69% | 1 | 1 | 0% | 2,557 | 3,538 | +38% | 0 | 0 | — |
case-18 | pass→pass | 55,506 | 19,091 | -66% | 1 | 1 | 0% | 2,877 | 3,187 | +11% | 0 | 0 | — |
case-19 | pass→pass | 24,690 | 22,218 | -10% | 1 | 1 | 0% | 2,033 | 3,290 | +62% | 0 | 0 | — |
case-20 | pass→pass | 14,037 | 14,461 | +3% | 1 | 1 | 0% | 1,768 | 2,530 | +43% | 0 | 0 | — |
case-22 | pass→pass | 18,361 | 20,621 | +12% | 1 | 1 | 0% | 1,588 | 2,608 | +64% | 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 +9 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.