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Get Started Free →Build AppImage bundles with AppDir structure for portable Linux applications
.claude/skills/a5c-ai-appimage-builder/SKILL.md| Model | Eval pass | Runs |
|---|---|---|
| gemini-3.6-flash | 93% | 18 |
| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-16 | ✗→✓ | ▲ Improved | 4% | 0% |
| case-19 | ✓→✓ | ＝ Same ✓ | 36% | 0% |
| case-03 | ✓→✓ | ＝ Same ✓ | -24% | 0% |
| case-04 | ✓→✓ | ＝ Same ✓ | 16% | 0% |
| case-05 | ✓→✓ | ＝ Same ✓ | -34% | 0% |
Build AppImage bundles for portable Linux application distribution that runs on most distributions.
json{ "type": "object", "properties": { "projectPath": { "type": "string" }, "appName": { "type": "string" }, "executablePath": { "type": "string" }, "iconPath": { "type": "string" }, "updateUrl": { "type": "string" } }, "required": ["projectPath", "appName", "executablePath"] }
MyApp.AppDir/
├── AppRun
├── myapp.desktop
├── myapp.png
└── usr/
├── bin/
│ └── myapp
└── lib/
└── [bundled libraries]bash# Using appimagetool ARCH=x86_64 appimagetool MyApp.AppDir MyApp-x86_64.AppImage # Using linuxdeploy linuxdeploy --appdir MyApp.AppDir --output appimage
deb-package-builderflatpak-manifest-generator| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-19 | pass→pass | 4,574 | 4,282 | -6% | 1 | 1 | 0% | 723 | 980 | +36% | 0 | 0 | — |
case-03 | pass→pass | 6,328 | 3,605 | -43% | 1 | 1 | 0% | 1,228 | 937 | -24% | 0 | 0 | — |
case-04 | pass→pass | 3,546 | 1,934 | -45% | 1 | 1 | 0% | 612 | 711 | +16% | 0 | 0 | — |
case-05 | pass→pass | 9,548 | 4,212 | -56% | 1 | 1 | 0% | 1,641 | 1,078 | -34% | 0 | 0 | — |
case-06 | pass→pass | 2,482 | 2,214 | -11% | 1 | 1 | 0% | 413 | 651 | +58% | 0 | 0 | — |
case-07 | pass→pass | 1,930 | 2,549 | +32% | 1 | 1 | 0% | 355 | 610 | +72% | 0 | 0 | — |
case-08 | pass→pass | 3,572 | 2,577 | -28% | 1 | 1 | 0% | 589 | 585 | -1% | 0 | 0 | — |
case-09 | pass→pass | 5,211 | 2,450 | -53% | 1 | 1 | 0% | 968 | 812 | -16% | 0 | 0 | — |
case-10 | pass→pass | 6,167 | 4,215 | -32% | 1 | 1 | 0% | 1,165 | 1,157 | -1% | 0 | 0 | — |
case-11 | pass→pass | 4,929 | 2,764 | -44% | 1 | 1 | 0% | 901 | 770 | -15% | 0 | 0 | — |
case-12 | pass→pass | 6,596 | 4,721 | -28% | 1 | 1 | 0% | 1,224 | 1,148 | -6% | 0 | 0 | — |
case-13 | pass→pass | 5,013 | 4,923 | -2% | 1 | 1 | 0% | 900 | 1,237 | +37% | 0 | 0 | — |
case-14 | pass→pass | 4,551 | 3,134 | -31% | 1 | 1 | 0% | 826 | 790 | -4% | 0 | 0 | — |
case-15 | pass→pass | 14,926 | 13,404 | -10% | 1 | 1 | 0% | 2,656 | 2,839 | +7% | 0 | 0 | — |
case-16 | fail→pass | 7,202 | 6,344 | -12% | 1 | 1 | 0% | 1,183 | 1,226 | +4% | 0 | 0 | — |
case-17 | pass→pass | 2,953 | 2,979 | +1% | 1 | 1 | 0% | 447 | 602 | +35% | 0 | 0 | — |
case-01 | pass→pass | 5,156 | 3,903 | -24% | 1 | 1 | 0% | 965 | 1,025 | +6% | 0 | 0 | — |
case-02 | pass→pass | 3,623 | 3,609 | -0% | 1 | 1 | 0% | 642 | 967 | +51% | 0 | 0 | — |
case-18 | pass→pass | 6,886 | 4,500 | -35% | 1 | 1 | 0% | 1,156 | 1,062 | -8% | 0 | 0 | — |
case-20 | pass→pass | 19,067 | 6,252 | -67% | 1 | 1 | 0% | 1,785 | 1,562 | -12% | 0 | 0 | — |
case-21 | pass→pass | 7,006 | 4,923 | -30% | 1 | 1 | 0% | 1,335 | 1,238 | -7% | 0 | 0 | — |
case-22 | pass→pass | 9,207 | 5,894 | -36% | 1 | 1 | 0% | 2,007 | 1,481 | -26% | 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.