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Get Started Free →Use when you need to run lint, format, or clippy checks in flutter_rust_bridge
.claude/skills/fzyzcjy-frb-lint/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-04 | ✗→✓ | ▲ Improved | -62% | 0% |
| case-05 | ✗→✓ | ▲ Improved | -72% | 0% |
| case-10 | ✗→✓ | ▲ Improved | -83% | 0% |
| case-11 | ✗→✓ | ▲ Improved | -55% | 0% |
| case-12 | ✗→✓ | ▲ Improved | -62% | 0% |
> Note: Read frb-dev-env before running commands and follow the active user's environment rules.
| Command | Description | |---------|-------------| | ./frb_internal lint --fix | Run all lints and auto-fix (recommended) | | ./frb_internal lint | Run all lints | | ./frb_internal lint-dart | Dart only | | ./frb_internal lint-rust | Rust only |
It contains:
dart analyzedart formatcargo clippycargo fmt| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 12,975 | 12,372 | -5% | 1 | 1 | 0% | 2,066 | 495 | -76% | 0 | 0 | — |
case-02 | fail→fail | 12,592 | 6,544 | -48% | 1 | 1 | 0% | 965 | 401 | -58% | 0 | 0 | — |
case-03 | fail→fail | 10,909 | 34,405 | +215% | 1 | 1 | 0% | 694 | 357 | -49% | 0 | 0 | — |
case-04 | fail→pass | 16,940 | 4,845 | -71% | 1 | 1 | 0% | 1,672 | 629 | -62% | 0 | 0 | — |
case-05 | fail→pass | 17,359 | 3,806 | -78% | 1 | 1 | 0% | 1,413 | 399 | -72% | 0 | 0 | — |
case-06 | pass→pass | 10,608 | 7,551 | -29% | 1 | 1 | 0% | 836 | 485 | -42% | 0 | 0 | — |
case-07 | pass→pass | 12,678 | 8,409 | -34% | 1 | 1 | 0% | 955 | 622 | -35% | 0 | 0 | — |
case-08 | pass→pass | 15,042 | 10,123 | -33% | 1 | 1 | 0% | 1,290 | 693 | -46% | 0 | 0 | — |
case-09 | pass→pass | 26,214 | 8,904 | -66% | 1 | 1 | 0% | 2,156 | 666 | -69% | 0 | 0 | — |
case-10 | fail→pass | 20,369 | 42,128 | +107% | 1 | 1 | 0% | 2,646 | 450 | -83% | 0 | 0 | — |
case-11 | fail→pass | 15,994 | 8,578 | -46% | 1 | 1 | 0% | 1,615 | 719 | -55% | 0 | 0 | — |
case-12 | fail→pass | 15,891 | 3,393 | -79% | 1 | 1 | 0% | 1,633 | 624 | -62% | 0 | 0 | — |
case-13 | fail→pass | 17,405 | 8,426 | -52% | 1 | 1 | 0% | 2,023 | 528 | -74% | 0 | 0 | — |
case-14 | pass→pass | 12,682 | 3,481 | -73% | 1 | 1 | 0% | 983 | 602 | -39% | 0 | 0 | — |
case-15 | pass→pass | 7,133 | 9,656 | +35% | 1 | 1 | 0% | 1,006 | 769 | -24% | 0 | 0 | — |
case-16 | pass→pass | 18,650 | 8,052 | -57% | 1 | 1 | 0% | 1,871 | 529 | -72% | 0 | 0 | — |
case-17 | fail→pass | 21,414 | 7,974 | -63% | 1 | 1 | 0% | 2,948 | 540 | -82% | 0 | 0 | — |
case-18 | fail→pass | 26,564 | 7,598 | -71% | 1 | 1 | 0% | 4,005 | 446 | -89% | 0 | 0 | — |
case-19 | pass→pass | 11,227 | 7,877 | -30% | 1 | 1 | 0% | 1,604 | 551 | -66% | 0 | 0 | — |
case-20 | pass→pass | 14,236 | 7,519 | -47% | 1 | 1 | 0% | 1,313 | 446 | -66% | 0 | 0 | — |
case-21 | fail→pass | 22,923 | 7,501 | -67% | 1 | 1 | 0% | 2,330 | 467 | -80% | 0 | 0 | — |
case-22 | fail→fail | 18,036 | 13,152 | -27% | 1 | 1 | 0% | 2,084 | 1,315 | -37% | 0 | 0 | — |
case-23 | fail→fail | 11,970 | 3,976 | -67% | 1 | 1 | 0% | 1,184 | 705 | -40% | 0 | 0 | — |
case-24 | fail→fail | 25,329 | 17,927 | -29% | 1 | 1 | 0% | 3,000 | 2,310 | -23% | 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. 24 cases were attempted, and 21 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 +38 percentage points is the difference between those two pass rates over the 21 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.
| Model | Method | Date | Lift |
|---|---|---|---|
| gemini-3.6-flash | verified | 8/9/2026 | +55% |
Other measured skills in the registry, with their headline benchmark lift.