Install any skill in seconds. Free to start, no credit card required.
Get Started Free →Scaffold an explicit one-shot workflow
.claude/skills/boshu2-workflow-builder/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-11 | ✗→✓ | ▲ Improved | -50% | 0% |
| case-09 | ✗→✓ | ▲ Improved | -35% | 0% |
| case-10 | ✗→✓ | ▲ Improved | -26% | 0% |
| case-12 | ✗→✓ | ▲ Improved | -28% | 0% |
| case-13 | ✗→✓ | ▲ Improved | -31% | 0% |
Build a thin adapter only when a caller needs to dispatch an explicit set of independent operations. A workflow is convenience code, never a correctness or lifecycle authority.
At-most-once dispatch over explicit inputs is the whole safety argument: a workflow that cannot retry or select work cannot compound a failure, so the worst case is one reported error per operation.
Named failure mode — framework gravity: a one-shot script growing config files, plugin hooks, and a state store until it is an unrequested orchestrator.
Anti-pattern: adding retry-on-failure "just for robustness". Corrective: report the per-operation error and stop; the caller owns whether anything runs again.
integration, closure, release, or delivery logic.
Prefer the smallest script supported by the target runtime. Include a dry-run or fixture demonstrating exact dispatch count and failure reporting. Do not create a new framework or SDK abstraction unless the caller explicitly requests one.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-11 | fail→pass | 26,798 | 11,678 | -56% | 1 | 1 | 0% | 5,491 | 2,761 | -50% | 0 | 0 | — |
case-02 | fail→fail | 8,391 | 11,048 | +32% | 1 | 1 | 0% | 1,554 | 2,450 | +58% | 0 | 0 | — |
case-03 | fail→fail | 12,982 | 10,869 | -16% | 1 | 1 | 0% | 2,875 | 2,560 | -11% | 0 | 0 | — |
case-04 | pass→fail | 24,057 | 13,437 | -44% | 1 | 1 | 0% | 4,587 | 2,599 | -43% | 0 | 0 | — |
case-01 | fail→fail | 15,272 | 11,161 | -27% | 1 | 1 | 0% | 3,299 | 2,427 | -26% | 0 | 0 | — |
case-05 | pass→fail | 17,832 | 8,615 | -52% | 1 | 1 | 0% | 3,128 | 1,822 | -42% | 0 | 0 | — |
case-06 | pass→pass | 25,776 | 13,737 | -47% | 1 | 1 | 0% | 4,548 | 2,942 | -35% | 0 | 0 | — |
case-07 | fail→fail | 12,645 | 9,819 | -22% | 1 | 1 | 0% | 2,441 | 2,209 | -10% | 0 | 0 | — |
case-08 | fail→fail | 24,845 | 12,157 | -51% | 1 | 1 | 0% | 4,651 | 2,556 | -45% | 0 | 0 | — |
case-09 | fail→pass | 18,637 | 10,704 | -43% | 1 | 1 | 0% | 3,648 | 2,371 | -35% | 0 | 0 | — |
case-10 | fail→pass | 16,850 | 11,730 | -30% | 1 | 1 | 0% | 3,457 | 2,562 | -26% | 0 | 0 | — |
case-12 | fail→pass | 18,000 | 11,673 | -35% | 1 | 1 | 0% | 3,536 | 2,545 | -28% | 0 | 0 | — |
case-13 | fail→pass | 20,314 | 12,684 | -38% | 1 | 1 | 0% | 3,891 | 2,679 | -31% | 0 | 0 | — |
case-14 | fail→fail | 20,625 | 13,227 | -36% | 1 | 1 | 0% | 4,138 | 2,750 | -34% | 0 | 0 | — |
case-15 | fail→fail | 6,905 | 8,001 | +16% | 1 | 1 | 0% | 1,297 | 1,784 | +38% | 0 | 0 | — |
case-16 | fail→pass | 12,815 | 10,898 | -15% | 1 | 1 | 0% | 2,426 | 2,384 | -2% | 0 | 0 | — |
case-17 | fail→pass | 22,085 | 16,744 | -24% | 1 | 1 | 0% | 4,272 | 3,446 | -19% | 0 | 0 | — |
case-18 | fail→fail | 21,947 | 13,034 | -41% | 1 | 1 | 0% | 4,220 | 2,783 | -34% | 0 | 0 | — |
case-19 | fail→fail | 14,649 | 12,311 | -16% | 1 | 1 | 0% | 2,649 | 2,556 | -4% | 0 | 0 | — |
case-20 | fail→fail | 15,969 | 15,469 | -3% | 1 | 1 | 0% | 3,060 | 3,240 | +6% | 0 | 0 | — |
case-21 | fail→fail | 16,571 | 11,050 | -33% | 1 | 1 | 0% | 3,335 | 2,348 | -30% | 0 | 0 | — |
case-22 | fail→pass | 27,453 | 12,345 | -55% | 1 | 1 | 0% | 5,220 | 2,649 | -49% | 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 +27 percentage points is the difference between those two pass rates over the 22 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.