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Get Started Free →Break a stuck, stalled week with three tiny wins sequenced for momentum — because motion creates motivation, not the other way around. Use when asked I'm in a rut, help me get unstuck this week, I've stalled on everything, or I need momentum. Produces three small, genuinely-achievable wins ordered so each fuels the next, a deliberately easy first one to prove motion is possible, the dopamine logic behind the sequence, and a reframe that you don't need motivation to start — starting creates it —
.claude/skills/mohitagw15856-momentum-map/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-03 | ✗→✓ | ▲ Improved | 12% | 0% |
| case-01 | ✗→✓ | ▲ Improved | 4% | 0% |
| case-02 | ✗→✓ | ▲ Improved | 24% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 15% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 31% | 0% |
Waiting to feel motivated before you act is backwards — motion creates motivation, not the reverse. When you've stalled on everything, the fix isn't a big push, it's a small win that proves movement is possible, then another, then another. This maps three tiny, achievable wins sequenced so each one fuels the next — a dopamine ladder out of the rut, starting with something so easy you can't fail.
Ask for these if not provided:
The reframe: you don't need to feel motivated first — moving is what creates it.
Your momentum map
After three: momentum may carry you on — or stop here, having genuinely moved. Either is a win.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-03 | fail→pass | 17,328 | 12,864 | -26% | 1 | 1 | 0% | 1,959 | 2,197 | +12% | 0 | 0 | — |
case-01 | fail→pass | 18,170 | 13,578 | -25% | 1 | 1 | 0% | 1,935 | 2,017 | +4% | 0 | 0 | — |
case-02 | fail→pass | 18,318 | 14,625 | -20% | 1 | 1 | 0% | 1,989 | 2,470 | +24% | 0 | 0 | — |
case-04 | pass→pass | 16,553 | 14,455 | -13% | 1 | 1 | 0% | 1,783 | 2,270 | +27% | 0 | 0 | — |
case-05 | pass→pass | 8,146 | 14,293 | +75% | 1 | 1 | 0% | 1,313 | 2,250 | +71% | 0 | 0 | — |
case-06 | fail→pass | 15,693 | 11,092 | -29% | 1 | 1 | 0% | 1,693 | 1,953 | +15% | 0 | 0 | — |
case-07 | pass→pass | 12,902 | 7,320 | -43% | 1 | 1 | 0% | 1,287 | 2,149 | +67% | 0 | 0 | — |
case-08 | fail→pass | 16,625 | 8,839 | -47% | 1 | 1 | 0% | 1,840 | 2,407 | +31% | 0 | 0 | — |
case-09 | fail→fail | 13,093 | 7,252 | -45% | 1 | 1 | 0% | 1,372 | 2,028 | +48% | 0 | 0 | — |
case-10 | fail→pass | 7,740 | 12,099 | +56% | 1 | 1 | 0% | 1,194 | 1,952 | +63% | 0 | 0 | — |
case-11 | pass→pass | 15,693 | 14,270 | -9% | 1 | 1 | 0% | 1,668 | 2,494 | +50% | 0 | 0 | — |
case-12 | pass→pass | 15,769 | 7,403 | -53% | 1 | 1 | 0% | 1,650 | 2,141 | +30% | 0 | 0 | — |
case-13 | pass→pass | 12,043 | 13,051 | +8% | 1 | 1 | 0% | 2,010 | 2,215 | +10% | 0 | 0 | — |
case-14 | pass→pass | 12,703 | 12,772 | +1% | 1 | 1 | 0% | 1,309 | 2,161 | +65% | 0 | 0 | — |
case-15 | pass→pass | 12,970 | 8,151 | -37% | 1 | 1 | 0% | 1,291 | 2,166 | +68% | 0 | 0 | — |
case-16 | fail→pass | 13,534 | 6,676 | -51% | 1 | 1 | 0% | 1,379 | 2,035 | +48% | 0 | 0 | — |
case-17 | pass→pass | 14,138 | 13,529 | -4% | 1 | 1 | 0% | 1,496 | 2,438 | +63% | 0 | 0 | — |
case-18 | fail→fail | 8,662 | 15,259 | +76% | 1 | 1 | 0% | 1,449 | 2,653 | +83% | 0 | 0 | — |
case-19 | fail→pass | 13,217 | 6,932 | -48% | 1 | 1 | 0% | 1,432 | 2,168 | +51% | 0 | 0 | — |
case-20 | pass→fail | 25,487 | 19,588 | -23% | 1 | 1 | 0% | 3,478 | 3,470 | -0% | 0 | 0 | — |
case-21 | fail→fail | 8,873 | 11,916 | +34% | 1 | 1 | 0% | 1,256 | 2,782 | +121% | 0 | 0 | — |
case-22 | pass→fail | 21,525 | 14,613 | -32% | 1 | 1 | 0% | 2,655 | 2,508 | -6% | 0 | 0 | — |
case-23 | pass→fail | 25,180 | 25,128 | -0% | 1 | 1 | 0% | 3,059 | 4,515 | +48% | 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. 23 cases were attempted. The headline lift of +22 percentage points is the difference between those two pass rates over the 23 comparable cases. 4 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.