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Get Started Free →Apply sustainability frameworks (triple bottom line, SDGs, ESG, circular economy) to evaluate whether strategies balance economic, social, and environmental dimensions. Use this skill when the user needs to assess ESG performance, design circular economy strategies, align business models with SDGs, or when they ask 'is this strategy truly sustainable', 'how do we measure ESG impact', 'what does a circular business model look like', or 'how do we avoid greenwashing'.
.claude/skills/asgard-ai-platform-grad-sustainability/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | -21% | 0% |
| case-03 | ✗→✓ | ▲ Improved | -41% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 39% | 0% |
| case-15 | ✗→✓ | ▲ Improved | -38% | 0% |
| case-16 | ✗→✓ | ▲ Improved | -30% | 0% |
Sustainability requires simultaneous pursuit of economic prosperity, social equity, and environmental integrity. Modern frameworks include the triple bottom line (Elkington), the UN Sustainable Development Goals (SDGs), ESG (Environmental, Social, Governance) criteria for investors, and circular economy principles that eliminate waste by designing for reuse, repair, and regeneration.
IRON LAW: Sustainability requires simultaneous consideration of economic,
social, AND environmental dimensions — optimizing one at the expense
of others is NOT sustainable development.Key assumptions:
Identify what is being assessed (firm, product, policy, supply chain), the time horizon, and relevant stakeholders across all three dimensions.
| Dimension | Key Questions | Frameworks | |-----------|--------------|------------| | Economic | Is value creation viable long-term? Who captures value? | Business model canvas, shared value | | Social | Are workers, communities, and users treated equitably? | SDGs 1-5, 10, 16; human rights due diligence | | Environmental | Are planetary boundaries respected? Is resource use circular? | SDGs 6-7, 12-15; life cycle assessment; circular economy |
Map where the three dimensions reinforce each other (synergies) and where they conflict (trade-offs). Assess whether trade-offs are being managed transparently or hidden.
Benchmark against relevant frameworks (GRI, SASB, TCFD, EU Taxonomy) and design interventions that move toward circular, regenerative models.
markdown## Sustainability Assessment: [Context] ### Scope Definition - Subject: [firm/product/policy/supply chain] - Time horizon: [short/medium/long-term] - System boundary: [what is included/excluded] ### Three-Dimension Assessment | Dimension | Current State | Key Metrics | Rating | |-----------|--------------|-------------|--------| | Economic | [description] | [metrics] | [strong/adequate/weak] | | Social | [description] | [metrics] | [strong/adequate/weak] | | Environmental | [description] | [metrics] | [strong/adequate/weak] | ### SDG Alignment | SDG | Relevance | Contribution | Gap | |-----|-----------|-------------|-----| | [SDG #] | [why relevant] | [current contribution] | [what is missing] | ### Trade-offs and Synergies - Synergies: [where dimensions reinforce each other] - Trade-offs: [where dimensions conflict] - Hidden externalities: [costs shifted to others or the future] ### Circular Economy Assessment - Current model: [linear / partially circular / circular] - Waste streams: [key waste and resource loss points] - Circularity opportunities: [reuse, repair, remanufacture, recycle] ### Recommendations 1. [Intervention addressing the weakest dimension] 2. [Circular economy redesign opportunity] 3. [Reporting and transparency improvement]
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 42,224 | 25,404 | -40% | 1 | 1 | 0% | 6,595 | 5,183 | -21% | 0 | 0 | — |
case-02 | fail→fail | 48,818 | 25,446 | -48% | 1 | 1 | 0% | 7,791 | 4,420 | -43% | 0 | 0 | — |
case-03 | fail→pass | 48,075 | 24,364 | -49% | 1 | 1 | 0% | 8,274 | 4,893 | -41% | 0 | 0 | — |
case-04 | pass→pass | 31,501 | 35,718 | +13% | 1 | 1 | 0% | 6,904 | 7,066 | +2% | 0 | 0 | — |
case-05 | pass→pass | 13,566 | 12,624 | -7% | 1 | 1 | 0% | 2,148 | 2,937 | +37% | 0 | 0 | — |
case-06 | pass→pass | 19,139 | 23,068 | +21% | 1 | 1 | 0% | 3,357 | 5,202 | +55% | 0 | 0 | — |
case-07 | pass→pass | 13,983 | 16,410 | +17% | 1 | 1 | 0% | 2,209 | 4,001 | +81% | 0 | 0 | — |
case-08 | pass→pass | 14,852 | 16,280 | +10% | 1 | 1 | 0% | 2,334 | 3,762 | +61% | 0 | 0 | — |
case-09 | pass→pass | 13,693 | 14,615 | +7% | 1 | 1 | 0% | 2,172 | 3,268 | +50% | 0 | 0 | — |
case-10 | pass→pass | 13,643 | 17,076 | +25% | 1 | 1 | 0% | 2,140 | 3,812 | +78% | 0 | 0 | — |
case-11 | fail→pass | 13,795 | 13,372 | -3% | 1 | 1 | 0% | 2,275 | 3,168 | +39% | 0 | 0 | — |
case-12 | pass→pass | 15,032 | 19,432 | +29% | 1 | 1 | 0% | 2,399 | 4,216 | +76% | 0 | 0 | — |
case-13 | pass→pass | 9,224 | 7,480 | -19% | 1 | 1 | 0% | 1,452 | 2,268 | +56% | 0 | 0 | — |
case-14 | fail→fail | 12,189 | 10,489 | -14% | 1 | 1 | 0% | 2,297 | 3,018 | +31% | 0 | 0 | — |
case-15 | fail→pass | 53,118 | 27,326 | -49% | 1 | 1 | 0% | 8,234 | 5,115 | -38% | 0 | 0 | — |
case-16 | fail→pass | 45,681 | 22,660 | -50% | 1 | 1 | 0% | 6,874 | 4,809 | -30% | 0 | 0 | — |
case-17 | fail→pass | 40,076 | 25,357 | -37% | 1 | 1 | 0% | 6,491 | 5,213 | -20% | 0 | 0 | — |
case-18 | fail→pass | 28,125 | 25,268 | -10% | 1 | 1 | 0% | 4,421 | 4,812 | +9% | 0 | 0 | — |
case-19 | fail→fail | 43,866 | 34,023 | -22% | 1 | 1 | 0% | 8,221 | 6,107 | -26% | 0 | 0 | — |
case-20 | fail→pass | 28,397 | 24,327 | -14% | 1 | 1 | 0% | 4,850 | 5,282 | +9% | 0 | 0 | — |
case-21 | pass→pass | 16,273 | 19,493 | +20% | 1 | 1 | 0% | 2,658 | 4,357 | +64% | 0 | 0 | — |
case-22 | pass→pass | 14,710 | 11,006 | -25% | 1 | 1 | 0% | 2,268 | 2,944 | +30% | 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.