Sustainability Skill

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name: sustainability-skill
description: Evidence-based assessment of a scientific or industrial technology across carbon emissions and green-economy value, real profitability, and deployment feasibility. Use for technology screening, R&D prioritization, pilot approval, commercialization reviews, investment memos, sustainability claims, and go/no-go decisions.
---

# Sustainability Skill

## Purpose

Evaluate whether a technology has practical value by combining environmental performance, economic returns, and implementation feasibility. Produce a decision-ready assessment that distinguishes verified evidence, user-provided data, assumptions, and unresolved risks.

Do not treat the result as a precise investment recommendation when critical inputs are missing. Use scenarios, sensitivity analysis, confidence levels, and explicit validation milestones.

## Operating principles

- Define the application, scale, geography, time horizon, and comparison baseline before scoring.
- Compare like with like: specify the functional unit, system boundary, capacity, utilization, lifetime, and denominator for every metric.
- Separate absolute performance from improvement relative to the incumbent or best available alternative.
- Never invent technical, financial, regulatory, or emissions data. Mark estimates and request high-impact missing inputs.
- Use conservative assumptions for early-stage technologies and state when subsidies, carbon prices, or credits are required for viability.
- Use a composite score only as a summary. Preserve dimension-level results and apply veto conditions for fatal safety, regulatory, supply, or scale-up barriers.
- Report uncertainty and the evidence needed to change the decision.

## Workflow

### 1. Frame the technology

Extract or ask for: technology description, use case, customer, output, capacity, maturity stage, location, deployment date, baseline alternative, available data, and decision question.

If the baseline or functional unit is unclear, resolve that before calculating benefits. For screening, proceed with clearly labeled assumptions and identify the decision-critical unknowns.

### 2. Assess green value and carbon

Quantify, where data permit:

- lifecycle greenhouse-gas emissions in kg CO2e per functional unit;
- absolute emissions and emissions avoided versus the baseline;
- energy, water, land, critical-material, and waste intensity;
- upstream, operational, transport, and end-of-life contributions;
- pollution-transfer risks and circularity/resource-recovery benefits;
- abatement cost per tCO2e avoided;
- dependence on renewable electricity, offsets, subsidies, carbon pricing, or certificates.

State the system boundary and whether results are attributional or consequential. Flag rebound effects, double counting of avoided emissions, uncertain end-of-life assumptions, and claims based only on offsets.