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Get Started Free →Use when you need data access with Quarkus Hibernate ORM Panache — including PanacheEntity / PanacheEntityBase, PanacheRepository, named queries, JPQL, native SQL, DTO projections (project(Class)), pagination (Page.of()), N+1 avoidance (JOIN FETCH), optimistic locking (@Version / OptimisticLockException), @NamedQuery for validated reusable queries, transactions, @TestTransaction for test isolation, and immutable-friendly patterns. This is the Quarkus analogue to Spring Data for relational persis
.claude/skills/jabrena-412-frameworks-quarkus-panache/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-02 | ✓→✗ | ▼ Worse | -83% | 0% |
| case-09 | ✓→✗ | ▼ Worse | -45% | 0% |
| case-17 | ✓→✗ | ▼ Worse | -37% | 0% |
| case-21 | ✓→✗ | ▼ Worse | -63% | 0% |
| case-03 | ✓→✓ | = Same ✓ | 26% | 0% |
Apply Panache patterns for Hibernate ORM in Quarkus.
What is covered in this Skill?
@411 for JDBC when bypassing Hibernate at the boundaryScope: Apply recommendations based on the reference rules and good/bad code examples.
Compile before persistence changes; verify after.
./mvnw compile or mvn compile before applying any change./mvnw clean verify or mvn clean verify after applying improvementsRead references/412-frameworks-quarkus-panache.md and inspect the current project setup before proposing changes.
Identify requested outcomes, constraints, and the minimum safe set of changes to apply.
Implement or refactor configuration/code following the reference patterns and project conventions.
Execute appropriate build/tests and summarize what changed, what was verified, and any follow-up actions.
For detailed guidance, examples, and constraints, see references/412-frameworks-quarkus-panache.md.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-03 | pass→pass | 12,226 | 11,192 | -8% | 1 | 1 | 0% | 2,066 | 2,611 | +26% | 0 | 0 | — |
case-01 | pass→pass | 19,085 | 16,179 | -15% | 1 | 1 | 0% | 3,612 | 3,249 | -10% | 0 | 0 | — |
case-02 | pass→fail | 25,359 | 4,802 | -81% | 1 | 1 | 0% | 4,897 | 819 | -83% | 0 | 0 | — |
case-04 | pass→pass | 11,004 | 10,011 | -9% | 1 | 1 | 0% | 1,752 | 2,357 | +35% | 0 | 0 | — |
case-05 | pass→pass | 11,296 | 8,858 | -22% | 1 | 1 | 0% | 2,000 | 2,228 | +11% | 0 | 0 | — |
case-06 | pass→pass | 18,084 | 11,552 | -36% | 1 | 1 | 0% | 3,142 | 2,648 | -16% | 0 | 0 | — |
case-07 | pass→pass | 17,262 | 7,710 | -55% | 1 | 1 | 0% | 2,743 | 1,898 | -31% | 0 | 0 | — |
case-08 | pass→pass | 12,557 | 9,091 | -28% | 1 | 1 | 0% | 2,219 | 2,184 | -2% | 0 | 0 | — |
case-09 | pass→fail | 8,616 | 13,238 | +54% | 1 | 1 | 0% | 1,479 | 814 | -45% | 0 | 0 | — |
case-10 | pass→pass | 14,759 | 14,045 | -5% | 1 | 1 | 0% | 2,634 | 3,240 | +23% | 0 | 0 | — |
case-11 | pass→pass | 11,869 | 9,090 | -23% | 1 | 1 | 0% | 1,886 | 2,191 | +16% | 0 | 0 | — |
case-12 | pass→pass | 17,180 | 14,082 | -18% | 1 | 1 | 0% | 2,694 | 2,817 | +5% | 0 | 0 | — |
case-13 | pass→pass | 10,229 | 11,745 | +15% | 1 | 1 | 0% | 1,718 | 2,602 | +51% | 0 | 0 | — |
case-14 | pass→pass | 17,499 | 8,170 | -53% | 1 | 1 | 0% | 2,838 | 2,070 | -27% | 0 | 0 | — |
case-15 | pass→pass | 6,726 | 3,996 | -41% | 1 | 1 | 0% | 1,178 | 1,248 | +6% | 0 | 0 | — |
case-16 | pass→pass | 15,799 | 8,062 | -49% | 1 | 1 | 0% | 2,513 | 1,485 | -41% | 0 | 0 | — |
case-17 | pass→fail | 20,774 | 8,541 | -59% | 1 | 1 | 0% | 3,742 | 2,341 | -37% | 0 | 0 | — |
case-18 | pass→pass | 9,896 | 4,822 | -51% | 1 | 1 | 0% | 1,717 | 1,499 | -13% | 0 | 0 | — |
case-19 | pass→pass | 9,277 | 6,697 | -28% | 1 | 1 | 0% | 1,630 | 1,712 | +5% | 0 | 0 | — |
case-20 | pass→pass | 6,420 | 6,903 | +8% | 1 | 1 | 0% | 1,355 | 2,029 | +50% | 0 | 0 | — |
case-21 | pass→fail | 14,529 | 5,672 | -61% | 1 | 1 | 0% | 2,801 | 1,032 | -63% | 0 | 0 | — |
case-22 | pass→pass | 8,090 | 7,782 | -4% | 1 | 1 | 0% | 1,669 | 2,081 | +25% | 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, and 19 counted toward the lift figure. The other 3 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of -100 percentage points is the difference between those two pass rates over the 19 comparable cases. 4 cases got worse with the skill loaded, and they are included in that figure.
Other measured skills in the registry, with their headline benchmark lift.