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Get Started Free →Capacity-gated sprint planning — runs capacity math, carry-over check, and a definition-of-ready gate before committing scope. Usage: /sprint-plan <goal> [capacity]
.claude/skills/alirezarezvani-sprint-plan/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 3% | 0% |
| case-02 | ✗→✓ | ▲ Improved | 52% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 30% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 20% | 0% |
| case-12 | ✗→✓ | ▲ Improved | -17% | 0% |
Create a sprint plan for $ARGUMENTS with explicit capacity math, a carry-over check, and a definition-of-ready gate. The first token(s) of $ARGUMENTS are the sprint goal; a trailing number is treated as team capacity (story points or person-days). If no capacity is given, compute it in Phase 1 — never invent it.
bash/sprint-plan <goal> [capacity] # e.g. /sprint-plan "Checkout v2 ready for beta" 34
Output a small table: raw → deductions → net capacity → trailing velocity → planning number.
A story may enter the committed scope only if all of these hold — otherwise it goes to "needs refinement", not the sprint:
Generate INVEST-checked stories from an epic with:
bashpython3 product-team/agile-product-owner/skills/agile-product-owner/scripts/user_story_generator.py
product-team/agile-product-owner/skills/agile-product-owner/SKILL.mdproduct-team/agile-product-owner/skills/agile-product-owner/assets/sprint_planning_template.mdproduct-team/agile-product-owner/skills/agile-product-owner/references/sprint-planning-guide.mdproduct-team/agile-product-owner/skills/agile-product-owner/scripts/user_story_generator.py/sprint-health — mid-sprint health check/user-story — single-story generation with INVEST checks| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 18,032 | 12,934 | -28% | 1 | 1 | 0% | 3,245 | 3,353 | +3% | 0 | 0 | — |
case-02 | fail→pass | 17,423 | 20,289 | +16% | 1 | 1 | 0% | 3,223 | 4,910 | +52% | 0 | 0 | — |
case-03 | fail→pass | 17,971 | 19,005 | +6% | 1 | 1 | 0% | 3,464 | 4,507 | +30% | 0 | 0 | — |
case-04 | pass→pass | 13,771 | 14,555 | +6% | 1 | 1 | 0% | 2,206 | 3,164 | +43% | 0 | 0 | — |
case-05 | pass→pass | 14,146 | 11,731 | -17% | 1 | 1 | 0% | 2,589 | 2,938 | +13% | 0 | 0 | — |
case-06 | pass→pass | 13,257 | 12,275 | -7% | 1 | 1 | 0% | 2,236 | 2,849 | +27% | 0 | 0 | — |
case-07 | pass→pass | 10,084 | 4,399 | -56% | 1 | 1 | 0% | 1,686 | 1,751 | +4% | 0 | 0 | — |
case-08 | pass→pass | 9,795 | 3,970 | -59% | 1 | 1 | 0% | 1,585 | 1,504 | -5% | 0 | 0 | — |
case-09 | pass→pass | 10,143 | 5,422 | -47% | 1 | 1 | 0% | 1,751 | 1,898 | +8% | 0 | 0 | — |
case-10 | fail→pass | 11,397 | 7,876 | -31% | 1 | 1 | 0% | 1,947 | 2,339 | +20% | 0 | 0 | — |
case-11 | pass→pass | 11,746 | 4,511 | -62% | 1 | 1 | 0% | 2,042 | 1,687 | -17% | 0 | 0 | — |
case-12 | fail→pass | 9,547 | 3,404 | -64% | 1 | 1 | 0% | 1,656 | 1,373 | -17% | 0 | 0 | — |
case-13 | pass→pass | 7,695 | 4,922 | -36% | 1 | 1 | 0% | 1,286 | 1,704 | +33% | 0 | 0 | — |
case-14 | fail→pass | 3,915 | 1,696 | -57% | 1 | 1 | 0% | 501 | 1,152 | +130% | 0 | 0 | — |
case-15 | pass→pass | 9,671 | 6,541 | -32% | 1 | 1 | 0% | 1,494 | 1,778 | +19% | 0 | 0 | — |
case-16 | pass→pass | 13,471 | 10,829 | -20% | 1 | 1 | 0% | 1,944 | 2,519 | +30% | 0 | 0 | — |
case-17 | fail→pass | 11,117 | 7,437 | -33% | 1 | 1 | 0% | 1,931 | 2,093 | +8% | 0 | 0 | — |
case-18 | pass→pass | 7,989 | 6,735 | -16% | 1 | 1 | 0% | 1,375 | 2,062 | +50% | 0 | 0 | — |
case-19 | fail→pass | 11,434 | 12,659 | +11% | 1 | 1 | 0% | 1,724 | 3,210 | +86% | 0 | 0 | — |
case-20 | fail→pass | 8,080 | 6,031 | -25% | 1 | 1 | 0% | 1,372 | 1,979 | +44% | 0 | 0 | — |
case-21 | pass→pass | 12,348 | 14,202 | +15% | 1 | 1 | 0% | 2,273 | 3,605 | +59% | 0 | 0 | — |
case-22 | pass→pass | 7,819 | 4,456 | -43% | 1 | 1 | 0% | 1,254 | 1,582 | +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 +41 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.