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Get Started Free →Enhanced `uname` command with colorized, structured output. Shows hostname, OS, kernel, architecture. **Dependency**: This is an x-cmd module. Install x-cmd first (see x-cmd skill for installation options). see x-cmd skill for installation.
.claude/skills/x-cmd-x-uname/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 8% | 0% |
| case-03 | ✗→✓ | ▲ Improved | -27% | 0% |
| case-07 | ✗→✓ | ▲ Improved | -62% | 0% |
| case-09 | ✗→✓ | ▲ Improved | -45% | 0% |
| case-10 | ✗→✓ | ▲ Improved | -16% | 0% |
> Enhanced uname command with colorized, structured output.
bash# Display system information x uname
| Field | Description | Example | |-------|-------------|---------| | hostname | System hostname | myserver | | osname | Operating system name | Linux, Darwin | | kernel | Kernel version | 5.15.0-91-generic | | machine | Hardware architecture | x86_64, arm64 | | version | Full OS version string | #101-Ubuntu SMP... |
bash# Default - colorful structured output x uname # Output example: # hostname : myserver # osname : Linux # kernel : 5.15.0-91-generic # machine : x86_64 # version : #101-Ubuntu SMP Tue Nov 14 13:29:11 UTC 2023
Colors are automatically disabled when output is piped:
bash# No colors in piped output x uname | cat # Parse with awk x uname | awk -F': ' '/kernel/{print $2}'
| Command | Output Style | |---------|--------------| | uname -a | Single line, space-separated | | x uname | Multi-line, key-value format |
bash# Native uname $ uname -a Linux myserver 5.15.0-91-generic #101-Ubuntu SMP ... x86_64 x86_64 x86_64 GNU/Linux # x uname $ x uname hostname : myserver osname : Linux kernel : 5.15.0-91-generic machine : x86_64 version : #101-Ubuntu SMP Tue Nov 14 13:29:11 UTC 2023
uname(1) manual page| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 7,505 | 4,494 | -40% | 1 | 1 | 0% | 1,068 | 1,155 | +8% | 0 | 0 | — |
case-02 | pass→pass | 9,672 | 5,052 | -48% | 1 | 1 | 0% | 1,607 | 1,314 | -18% | 0 | 0 | — |
case-03 | fail→pass | 9,612 | 3,652 | -62% | 1 | 1 | 0% | 1,532 | 1,113 | -27% | 0 | 0 | — |
case-04 | pass→pass | 4,950 | 5,273 | +7% | 1 | 1 | 0% | 734 | 1,338 | +82% | 0 | 0 | — |
case-05 | pass→pass | 9,729 | 10,192 | +5% | 1 | 1 | 0% | 1,549 | 1,638 | +6% | 0 | 0 | — |
case-06 | pass→pass | 11,195 | 6,375 | -43% | 1 | 1 | 0% | 1,573 | 1,675 | +6% | 0 | 0 | — |
case-07 | fail→pass | 41,435 | 5,039 | -88% | 1 | 1 | 0% | 3,334 | 1,271 | -62% | 0 | 0 | — |
case-08 | pass→pass | 13,107 | 6,487 | -51% | 1 | 1 | 0% | 2,014 | 1,612 | -20% | 0 | 0 | — |
case-09 | fail→pass | 13,516 | 3,431 | -75% | 1 | 1 | 0% | 2,037 | 1,111 | -45% | 0 | 0 | — |
case-10 | fail→pass | 16,883 | 3,333 | -80% | 1 | 1 | 0% | 1,183 | 995 | -16% | 0 | 0 | — |
case-11 | fail→pass | 10,711 | 2,919 | -73% | 1 | 1 | 0% | 1,771 | 941 | -47% | 0 | 0 | — |
case-12 | fail→pass | 7,769 | 3,201 | -59% | 1 | 1 | 0% | 1,209 | 1,013 | -16% | 0 | 0 | — |
case-13 | pass→pass | 19,376 | 5,121 | -74% | 1 | 1 | 0% | 1,417 | 1,239 | -13% | 0 | 0 | — |
case-14 | pass→pass | 26,647 | 4,989 | -81% | 1 | 1 | 0% | 2,274 | 1,496 | -34% | 0 | 0 | — |
case-15 | fail→pass | 14,097 | 4,261 | -70% | 1 | 1 | 0% | 1,854 | 1,277 | -31% | 0 | 0 | — |
case-16 | pass→pass | 8,121 | 3,487 | -57% | 1 | 1 | 0% | 1,254 | 928 | -26% | 0 | 0 | — |
case-17 | fail→pass | 30,373 | 12,459 | -59% | 1 | 1 | 0% | 2,278 | 2,267 | -0% | 0 | 0 | — |
case-18 | pass→pass | 4,448 | 2,839 | -36% | 1 | 1 | 0% | 604 | 885 | +47% | 0 | 0 | — |
case-19 | fail→pass | 8,885 | 2,408 | -73% | 1 | 1 | 0% | 1,212 | 847 | -30% | 0 | 0 | — |
case-20 | pass→pass | 6,821 | 4,520 | -34% | 1 | 1 | 0% | 1,051 | 1,136 | +8% | 0 | 0 | — |
case-21 | pass→pass | 11,150 | 3,240 | -71% | 1 | 1 | 0% | 1,759 | 1,037 | -41% | 0 | 0 | — |
case-22 | fail→pass | 4,658 | 2,951 | -37% | 1 | 1 | 0% | 728 | 953 | +31% | 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 +50 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.