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Get Started Free →Craft a sharp value proposition that says who it's for, the outcome, and why you over the alternative. Use when asked to write a value prop, a value proposition, a one-liner, or to clarify 'what do we even say we do?'. Produces a primary value-prop statement, a plain-language one-liner, 3 benefit-led variations, and the before→after transformation it promises — ready to headline a landing page.
.claude/skills/mohitagw15856-value-proposition/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 7% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 15% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 17% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 61% | 0% |
| case-12 | ✗→✓ | ▲ Improved | 72% | 0% |
A value proposition is the single sentence that makes someone think "that's for me." Most are vague feature-soup ("the all-in-one platform for modern teams"). This skill writes one that names the audience, the outcome they actually want, and why you beat the alternative — the foundation every landing page, ad, and pitch is built on. (For the category/competitive frame, pair with product-positioning-doc; this writes the words.)
Ask for these only if they aren't already provided:
1. Primary statement — the canonical form: > For audience] who need/struggle], product] is the category] that key outcome]. Unlike alternative], it differentiator].
2. One-liner — the plain-language version a customer would say to a friend (≤12 words, no jargon). This is the headline candidate.
3. Three variations — benefit-led alternates in different angles (outcome-led, pain-led, identity-led), so you can A/B them.
4. Before → After — the transformation in two columns (their world without you → with you). This is what the copy dramatizes.
| Without product] | With product] | |---|---| | the painful status quo] | the better state] |
5. What to avoid — the generic phrasings to cut (e.g. "all-in-one", "seamless", "next-generation") because they say nothing.
Value-proposition design (Osterwalder) + April Dunford positioning as the upstream frame.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 18,177 | 18,121 | -0% | 1 | 1 | 0% | 2,414 | 2,595 | +7% | 0 | 0 | — |
case-02 | fail→fail | 27,528 | 16,246 | -41% | 1 | 1 | 0% | 3,118 | 2,752 | -12% | 0 | 0 | — |
case-03 | fail→pass | 24,988 | 18,170 | -27% | 1 | 1 | 0% | 2,668 | 3,055 | +15% | 0 | 0 | — |
case-04 | pass→pass | 68,869 | 23,939 | -65% | 1 | 1 | 0% | 8,226 | 3,667 | -55% | 0 | 0 | — |
case-05 | pass→pass | 35,657 | 41,100 | +15% | 1 | 1 | 0% | 6,103 | 6,067 | -1% | 0 | 0 | — |
case-06 | pass→pass | 23,974 | 37,871 | +58% | 1 | 1 | 0% | 4,338 | 5,087 | +17% | 0 | 0 | — |
case-07 | fail→pass | 20,602 | 18,998 | -8% | 1 | 1 | 0% | 2,527 | 2,944 | +17% | 0 | 0 | — |
case-08 | fail→pass | 11,302 | 19,771 | +75% | 1 | 1 | 0% | 1,639 | 2,641 | +61% | 0 | 0 | — |
case-09 | fail→fail | 17,520 | 15,640 | -11% | 1 | 1 | 0% | 1,951 | 2,376 | +22% | 0 | 0 | — |
case-10 | fail→fail | 16,622 | 11,869 | -29% | 1 | 1 | 0% | 1,820 | 2,760 | +52% | 0 | 0 | — |
case-11 | pass→pass | 12,560 | 22,032 | +75% | 1 | 1 | 0% | 1,880 | 2,903 | +54% | 0 | 0 | — |
case-12 | fail→pass | 15,069 | 17,553 | +16% | 1 | 1 | 0% | 1,492 | 2,566 | +72% | 0 | 0 | — |
case-13 | fail→pass | 14,162 | 13,911 | -2% | 1 | 1 | 0% | 1,385 | 2,844 | +105% | 0 | 0 | — |
case-14 | fail→fail | 11,982 | 25,718 | +115% | 1 | 1 | 0% | 942 | 2,489 | +164% | 0 | 0 | — |
case-15 | pass→pass | 16,429 | 21,478 | +31% | 1 | 1 | 0% | 2,103 | 3,119 | +48% | 0 | 0 | — |
case-16 | fail→pass | 16,414 | 24,643 | +50% | 1 | 1 | 0% | 1,597 | 2,860 | +79% | 0 | 0 | — |
case-17 | pass→pass | 10,601 | 9,840 | -7% | 1 | 1 | 0% | 1,625 | 2,144 | +32% | 0 | 0 | — |
case-18 | pass→pass | 19,979 | 16,250 | -19% | 1 | 1 | 0% | 2,236 | 2,627 | +17% | 0 | 0 | — |
case-19 | pass→pass | 19,157 | 18,133 | -5% | 1 | 1 | 0% | 2,105 | 2,349 | +12% | 0 | 0 | — |
case-20 | pass→pass | 19,711 | 17,434 | -12% | 1 | 1 | 0% | 2,142 | 2,614 | +22% | 0 | 0 | — |
case-21 | fail→pass | 9,358 | 19,952 | +113% | 1 | 1 | 0% | 1,399 | 2,864 | +105% | 0 | 0 | — |
case-22 | fail→fail | 12,511 | 14,884 | +19% | 1 | 1 | 0% | 1,106 | 2,234 | +102% | 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.
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.