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Get Started Free →Apply Service-Dominant Logic (Vargo and Lusch, 2004) and value co-creation principles to reframe exchange and value creation. Use this skill when the user needs to redesign value propositions around service exchange, analyze co-creation dynamics between firms and customers, shift from goods-dominant to service-dominant thinking, or when they ask 'how is value created with customers', 'what is our service logic', or 'how do we enable co-creation'.
.claude/skills/asgard-ai-platform-grad-sd-logic/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-07 | ✗→✓ | ▲ Improved | 56% | 0% |
| case-12 | ✗→✓ | ▲ Improved | 47% | 0% |
| case-13 | ✗→✓ | ▲ Improved | 76% | 0% |
| case-22 | ✗→✓ | ▲ Improved | 22% | 0% |
| case-04 | ✓→✓ | = Same ✓ | 8% | 0% |
Service-Dominant Logic reframes marketing from goods-centered (value-in-exchange) to service-centered (value-in-use). Vargo and Lusch (2004, 2008, 2016) articulate foundational premises: service is the fundamental basis of exchange, value is always co-created with beneficiaries, and all economic actors are resource integrators.
IRON LAW: Value is ALWAYS co-created. The firm can only offer value
propositions, not deliver value. Value is uniquely and phenomeno-
logically determined by the beneficiary in context of use.Key assumptions:
Evaluate the current business through S-D Logic's key foundational premises (FPs):
| FP | Premise | Diagnostic Question | |----|---------|-------------------| | FP1 | Service is the fundamental basis of exchange | What competence application does our offering enable? | | FP6 | Value is co-created by multiple actors | Who participates in value creation beyond the firm? | | FP7 | Actors cannot deliver value, only offer propositions | Are we assuming value is embedded in the product? | | FP9 | All actors are resource integrators | What resources do customers bring to the exchange? | | FP10 | Value is uniquely determined by the beneficiary | Do we measure value-in-use or only value-in-exchange? |
| Resource Type | Definition | Examples | |--------------|-----------|----------| | Operand | Resources acted upon (static) | Raw materials, equipment, money | | Operant | Resources that act on others (dynamic) | Knowledge, skills, technology, relationships |
Shift strategic focus from operand to operant resources.
Identify all actors, institutions, and resource flows in the value co-creation network:
Reframe offerings as value propositions that enable beneficiary value creation:
markdown## S-D Logic Analysis: [Context] ### Current Logic Assessment - Dominant logic: [goods-dominant / transitioning / service-dominant] - Value definition: [value-in-exchange / value-in-use / both] ### Foundational Premise Audit | FP | Current State | Gap | Action | |----|--------------|-----|--------| | FP1 (Service basis) | | | | | FP6 (Co-creation) | | | | | FP10 (Beneficiary value) | | | | ### Service Ecosystem Map - Key actors: ... - Resource flows: ... - Institutional arrangements: ... ### Redesigned Value Propositions 1. [From]: [product-centric statement] → [To]: [service-centric proposition] 2. ...
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 35,600 | 18,628 | -48% | 1 | 1 | 0% | 5,888 | 4,448 | -24% | 0 | 0 | — |
case-02 | fail→fail | 40,804 | 23,694 | -42% | 1 | 1 | 0% | 6,264 | 5,034 | -20% | 0 | 0 | — |
case-03 | fail→fail | 27,356 | 20,533 | -25% | 1 | 1 | 0% | 4,499 | 4,609 | +2% | 0 | 0 | — |
case-04 | pass→pass | 17,820 | 10,572 | -41% | 1 | 1 | 0% | 2,596 | 2,807 | +8% | 0 | 0 | — |
case-05 | pass→pass | 19,318 | 12,188 | -37% | 1 | 1 | 0% | 3,154 | 3,204 | +2% | 0 | 0 | — |
case-06 | pass→pass | 13,668 | 10,979 | -20% | 1 | 1 | 0% | 2,285 | 2,987 | +31% | 0 | 0 | — |
case-07 | fail→pass | 15,715 | 15,701 | -0% | 1 | 1 | 0% | 2,520 | 3,924 | +56% | 0 | 0 | — |
case-08 | pass→pass | 15,124 | 19,143 | +27% | 1 | 1 | 0% | 2,367 | 3,828 | +62% | 0 | 0 | — |
case-09 | pass→pass | 20,399 | 22,708 | +11% | 1 | 1 | 0% | 3,266 | 4,664 | +43% | 0 | 0 | — |
case-10 | pass→pass | 12,069 | 14,094 | +17% | 1 | 1 | 0% | 1,702 | 3,371 | +98% | 0 | 0 | — |
case-11 | pass→pass | 6,162 | 3,838 | -38% | 1 | 1 | 0% | 1,160 | 1,925 | +66% | 0 | 0 | — |
case-12 | fail→pass | 15,532 | 15,475 | -0% | 1 | 1 | 0% | 2,559 | 3,768 | +47% | 0 | 0 | — |
case-13 | fail→pass | 12,998 | 14,732 | +13% | 1 | 1 | 0% | 2,017 | 3,547 | +76% | 0 | 0 | — |
case-14 | pass→pass | 17,000 | 15,280 | -10% | 1 | 1 | 0% | 2,629 | 3,598 | +37% | 0 | 0 | — |
case-15 | pass→pass | 12,604 | 12,545 | -0% | 1 | 1 | 0% | 2,055 | 3,253 | +58% | 0 | 0 | — |
case-16 | fail→fail | 9,304 | 11,155 | +20% | 1 | 1 | 0% | 1,559 | 3,086 | +98% | 0 | 0 | — |
case-17 | pass→pass | 18,577 | 14,172 | -24% | 1 | 1 | 0% | 2,957 | 3,485 | +18% | 0 | 0 | — |
case-18 | pass→pass | 11,857 | 10,997 | -7% | 1 | 1 | 0% | 1,873 | 3,038 | +62% | 0 | 0 | — |
case-19 | pass→pass | 12,076 | 13,984 | +16% | 1 | 1 | 0% | 2,188 | 3,519 | +61% | 0 | 0 | — |
case-20 | pass→pass | 11,880 | 12,173 | +2% | 1 | 1 | 0% | 1,962 | 3,087 | +57% | 0 | 0 | — |
case-21 | pass→pass | 13,537 | 15,930 | +18% | 1 | 1 | 0% | 2,308 | 3,528 | +53% | 0 | 0 | — |
case-22 | fail→pass | 13,779 | 9,991 | -27% | 1 | 1 | 0% | 2,260 | 2,757 | +22% | 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 +18 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.