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Get Started Free →Creates product strategies using Crossing the Chasm, Playing to Win, and strategic canvas frameworks. Use when defining where to play and how to win, choosing beachhead markets, or connecting tactics to strategy.
.claude/skills/bilal140202-strategy-frameworks/SKILL.md| Model | Eval pass | Runs |
|---|---|---|
| gemini-3.6-flash | 91% | 22 |
| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | -28% | 0% |
| case-02 | ✗→✓ | ▲ Improved | -12% | 0% |
| case-04 | ✗→✓ | ▲ Improved | -42% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 16% | 0% |
| case-08 | ✗→✓ | ▲ Improved | -4% | 0% |
Claude uses this skill when:
Five Choices:
Beachhead Strategy:
markdown# Product Strategy: [Product] ## Winning Aspiration [What does winning look like in 3-5 years?] ## Where to Play **Target Market:** - Segment: [specific] - Size: [TAM/SAM/SOM] - Beachhead: [first segment to dominate] **Not Playing:** - [Segments we're avoiding and why] ## How to Win **Competitive Advantage:** - [What we do better than anyone] - [Why customers choose us] - [Our defensible moat] ## Capabilities Required - [Capability 1 we need] - [Capability 2 we need] - [Capability 3 we need] ## Strategic Roadmap **Now (0-6 months):** - [Initiative] **Next (6-18 months):** - [Initiative] **Later (18+ months):** - [Initiative]
Define:
Execute:
Geoffrey Moore: > "The number one reason startups fail is premature scaling. Pick a beachhead and dominate it."
Playing to Win: > "Strategy is about choice. What will we do and what will we NOT do?"
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-11 | pass→fail | 14,907 | 11,428 | -23% | 1 | 1 | 0% | 2,167 | 2,169 | +0% | 0 | 0 | — |
case-01 | fail→pass | 26,159 | 16,350 | -37% | 1 | 1 | 0% | 4,499 | 3,221 | -28% | 0 | 0 | — |
case-02 | fail→pass | 21,513 | 15,855 | -26% | 1 | 1 | 0% | 3,411 | 2,986 | -12% | 0 | 0 | — |
case-03 | fail→fail | 22,847 | 22,355 | -2% | 1 | 1 | 0% | 3,595 | 3,828 | +6% | 0 | 0 | — |
case-04 | fail→pass | 29,813 | 15,245 | -49% | 1 | 1 | 0% | 5,223 | 3,022 | -42% | 0 | 0 | — |
case-22 | pass→pass | 11,742 | 12,549 | +7% | 1 | 1 | 0% | 2,448 | 2,779 | +14% | 0 | 0 | — |
case-05 | pass→pass | 19,311 | 21,470 | +11% | 1 | 1 | 0% | 3,349 | 3,970 | +19% | 0 | 0 | — |
case-06 | pass→pass | 17,670 | 18,052 | +2% | 1 | 1 | 0% | 2,928 | 3,370 | +15% | 0 | 0 | — |
case-07 | fail→pass | 13,384 | 11,224 | -16% | 1 | 1 | 0% | 2,012 | 2,330 | +16% | 0 | 0 | — |
case-08 | fail→pass | 16,097 | 12,413 | -23% | 1 | 1 | 0% | 2,511 | 2,421 | -4% | 0 | 0 | — |
case-09 | pass→pass | 17,289 | 11,844 | -31% | 1 | 1 | 0% | 2,660 | 2,300 | -14% | 0 | 0 | — |
case-10 | fail→pass | 18,584 | 12,716 | -32% | 1 | 1 | 0% | 2,775 | 2,416 | -13% | 0 | 0 | — |
case-12 | fail→pass | 18,525 | 14,875 | -20% | 1 | 1 | 0% | 2,747 | 2,911 | +6% | 0 | 0 | — |
case-13 | fail→pass | 15,160 | 13,543 | -11% | 1 | 1 | 0% | 2,523 | 2,663 | +6% | 0 | 0 | — |
case-14 | fail→pass | 10,232 | 8,551 | -16% | 1 | 1 | 0% | 1,750 | 1,943 | +11% | 0 | 0 | — |
case-15 | fail→pass | 12,155 | 2,716 | -78% | 1 | 1 | 0% | 1,953 | 1,047 | -46% | 0 | 0 | — |
case-16 | pass→pass | 16,408 | 15,603 | -5% | 1 | 1 | 0% | 2,721 | 3,215 | +18% | 0 | 0 | — |
case-17 | pass→pass | 13,190 | 10,337 | -22% | 1 | 1 | 0% | 2,174 | 2,082 | -4% | 0 | 0 | — |
case-18 | pass→pass | 13,150 | 15,309 | +16% | 1 | 1 | 0% | 2,162 | 2,970 | +37% | 0 | 0 | — |
case-19 | pass→pass | 9,159 | 6,816 | -26% | 1 | 1 | 0% | 1,618 | 1,665 | +3% | 0 | 0 | — |
case-20 | pass→pass | 18,148 | 11,551 | -36% | 1 | 1 | 0% | 3,327 | 3,110 | -7% | 0 | 0 | — |
case-21 | pass→fail | 7,098 | 4,865 | -31% | 1 | 1 | 0% | 1,065 | 1,293 | +21% | 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 +36 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.