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Get Started Free →Handle issue/PR work items with worktree isolation. Triggered by "/work [issue_link|description]" to start focused work.
.claude/skills/x-cmd-work/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-04 | ✗→✓ | ▲ Improved | 51% | 0% |
| case-09 | ✗→✓ | ▲ Improved | -11% | 0% |
| case-10 | ✗→✓ | ▲ Improved | -6% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 31% | 0% |
| case-14 | ✗→✓ | ▲ Improved | -30% | 0% |
Use when:
/work with an issue/PR link or description/work [issue_link or pr_link or natural_description]bashgh issue view <number> --json title,body,labels gh pr view <number> --json title,body,labels,files
bashSLUG="$(echo "$TITLE" | tr '[:upper:]' '[:lower:]' | tr ' ' '-' | tr -cd 'a-z0-9_-')" BRANCH_NAME="work/$(date +%Y%m%d)-${SLUG}" git worktree add -b "$BRANCH_NAME" "$WORKTREE_PATH"
Created worktree: $BRANCH_NAME
Location: $WORKTREE_PATH
Issue: $TITLE (#$NUMBER)When work done:
git commit in worktreegit worktree removework/YYYYMMDD-short-description| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 9,517 | 8,057 | -15% | 1 | 1 | 0% | 428 | 635 | +48% | 0 | 0 | — |
case-02 | fail→fail | 5,060 | 10,985 | +117% | 1 | 1 | 0% | 468 | 1,010 | +116% | 0 | 0 | — |
case-03 | fail→fail | 9,016 | 11,294 | +25% | 1 | 1 | 0% | 1,531 | 914 | -40% | 0 | 0 | — |
case-04 | fail→pass | 6,474 | 7,817 | +21% | 1 | 1 | 0% | 987 | 1,488 | +51% | 0 | 0 | — |
case-05 | fail→fail | 9,071 | 5,657 | -38% | 1 | 1 | 0% | 1,253 | 1,292 | +3% | 0 | 0 | — |
case-06 | pass→pass | 12,243 | 7,575 | -38% | 1 | 1 | 0% | 2,002 | 1,633 | -18% | 0 | 0 | — |
case-07 | fail→fail | 12,332 | 6,641 | -46% | 1 | 1 | 0% | 1,929 | 1,226 | -36% | 0 | 0 | — |
case-08 | fail→fail | 11,609 | 16,754 | +44% | 1 | 1 | 0% | 1,892 | 1,074 | -43% | 0 | 0 | — |
case-09 | fail→pass | 9,507 | 5,315 | -44% | 1 | 1 | 0% | 1,238 | 1,099 | -11% | 0 | 0 | — |
case-10 | fail→pass | 11,333 | 8,729 | -23% | 1 | 1 | 0% | 1,944 | 1,824 | -6% | 0 | 0 | — |
case-11 | fail→pass | 11,651 | 11,718 | +1% | 1 | 1 | 0% | 1,836 | 2,410 | +31% | 0 | 0 | — |
case-12 | fail→fail | 10,759 | 15,127 | +41% | 1 | 1 | 0% | 1,683 | 1,873 | +11% | 0 | 0 | — |
case-13 | fail→fail | 9,963 | 11,433 | +15% | 1 | 1 | 0% | 1,620 | 1,936 | +20% | 0 | 0 | — |
case-14 | fail→pass | 11,538 | 6,052 | -48% | 1 | 1 | 0% | 1,821 | 1,267 | -30% | 0 | 0 | — |
case-15 | fail→pass | 9,598 | 11,688 | +22% | 1 | 1 | 0% | 1,675 | 2,507 | +50% | 0 | 0 | — |
case-16 | fail→pass | 12,919 | 3,941 | -69% | 1 | 1 | 0% | 2,004 | 814 | -59% | 0 | 0 | — |
case-17 | pass→pass | 9,938 | 5,455 | -45% | 1 | 1 | 0% | 1,241 | 1,046 | -16% | 0 | 0 | — |
case-18 | fail→pass | 10,399 | 7,013 | -33% | 1 | 1 | 0% | 1,534 | 1,255 | -18% | 0 | 0 | — |
case-19 | fail→fail | 10,707 | 3,899 | -64% | 1 | 1 | 0% | 1,674 | 875 | -48% | 0 | 0 | — |
case-20 | fail→fail | 6,627 | 5,416 | -18% | 1 | 1 | 0% | 843 | 846 | +0% | 0 | 0 | — |
case-21 | pass→pass | 8,032 | 5,624 | -30% | 1 | 1 | 0% | 1,130 | 585 | -48% | 0 | 0 | — |
case-22 | pass→pass | 11,457 | 8,297 | -28% | 1 | 1 | 0% | 1,765 | 1,474 | -16% | 0 | 0 | — |
case-23 | pass→pass | 6,650 | 5,569 | -16% | 1 | 1 | 0% | 1,213 | 1,248 | +3% | 0 | 0 | — |
case-24 | pass→pass | 7,708 | 6,499 | -16% | 1 | 1 | 0% | 992 | 917 | -8% | 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 20 counted toward the lift figure. The other 4 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 +33 percentage points is the difference between those two pass rates over the 20 comparable cases. 2 cases got worse with the skill loaded, and they are 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.