An open AI skill · v1.1.0 · CC BY 4.0

Sustainability can be a part of every design decision.

sustainability.md is a reusable AI skill that integrates carbon and water analysis, sustainability ROI, and hidden-emissions detection into experience design, strategy, and operations work. Automatically.

→ How to use the skill ↗ View it on GitHub

How it works

Add this skill to the AI you use for shaping
experience design decisions.

It will surface sustainability considerations that align with the work you’re already doing.

You prompt…

I’m designing a new onboarding experience for new hires. What are potential stages for the onboarding experience?

Your AI might respond…
1. Pre-Boarding (Offer Acceptance → Day 1)

The most overlooked stage, and one of the highest-waste periods.

  • Digital offer letters, contracts, and tax forms
  • Welcome email sequence with culture content
  • Equipment provisioning decisions made early
  • Access credentials set up before Day 1
Sustainability lens

Shipping hardware overnight vs. standard shipping, or enabling BYOD or remote equipment pickup, can cut per-hire emissions significantly. Printed welcome packets are a common hidden waste source: a 20-page printed packet × 500 hires per year equals roughly the paper equivalent of 1–2 trees annually.

The reasoning

The tools we use matter.
The experiences we create matter more.

Consequences scale more through the experiences we create than through the tools we use to create them.

Turn AI into a sustainability solution. Using AI for design can have a real environmental footprint. But that footprint is small compared to the sustainability impact embedded in the experiences AI helps us build: the onboarding flows, recommendation engines, purchasing pathways, and service designs that shape the daily decisions of millions of people.

Use your leverage for positive impact. CX and UX professionals collectively manage the experience layer: where demand meets supply, where behaviors are shaped, and where markets signal what they want from the systems that serve them. That’s enormous leverage you have to shape parts of work and life to be more sustainable.

What the skill does

Four factors,
always integrated.

When active, the sustainability skill instructs AI to apply four analytical factors to every relevant response, woven into the work you’re already doing.

01 — Analysis
Sustainability Analysis
For each recommendation or design decision, surfaces the primary sustainability implications: carbon, water, land, waste, or biodiversity; whichever are most relevant to the context.
02 — Impact
Relatable Estimates
Translates abstract emissions figures into human-scale comparisons: miles driven, bottles of water, smartphones charged, trees needed. Never omits estimates because data is imperfect.
03 — Ranking
Sustainability ROI
Ranks options by sustainability ROI alongside traditional metrics, prioritizing solutions that align sustainability gains with existing user motivations rather than adding friction.
04 — Discovery
Hidden Emissions
Surfaces the non-obvious sources of pollution and emissions that aren’t always so obvious. Design choices and their effects such as transportation, food waste, and materials choices have big impact at scale.

How to use it

Install it once.
It works every time.

The most effective way to use sustainability.md is to install it as a persistent system-level instruction in your AI tool of choice. Do this once and sustainability analysis will be present in every session, no re-prompting required.

The instruction to paste is the same for every tool:

Apply the sustainability skill from:
https://raw.githubusercontent.com/brandonschauer/sustainability.md/main/sustainability.md

Where to paste it — for common tools

ChatGPT
  1. On the sidebar, click your profile picture at the bottom
  2. Select Personalization
  3. In the Custom Instructions field, paste the instruction above
  4. Click Save. Active in all new chats.
Gemini
  1. On the sidebar, click Gems
  2. Click New Gem
  3. Give it a name such as “Sustainability”
  4. In the instructions field, paste the instruction above
  5. Click Save. Open this Gem when you want the skill active.
Claude
  1. On the sidebar, click Projects
  2. Create a new Project or open an existing one
  3. Click Project instructions
  4. Paste the instruction above
  5. Click Save. Active in every conversation in that Project.

Authoritative sources

Grounded in
peer-reviewed science.

The skill’s knowledge layer draws from these institutions and publications. All are publicly accessible; all are cited in the skill file with direct links.

IPCC
AR6, SR1.5, SRCCL: climate science, food systems, land use
GHG Protocol
Corporate standard for Scope 1, 2, and 3 emissions accounting
WRI
World Resources Institute: applied sustainability analysis
IEA
International Energy Agency: global energy systems and buildings
SBTi
Science Based Targets initiative: business emissions targets
Water FP Network
Blue, green, and grey water footprint methodology
IPBES
Global biodiversity assessment: nature and ecosystem services
US EPA
eGRID: US electricity emissions factors by region
Shaolei Ren
UC Riverside: AI data center water and energy footprints
McKinsey
The cost of compute: AI workload growth projections to 2030

Full citations with URLs are in the skill file. The source list is versioned and updated monthly. See CHANGELOG.md.

Open collaboration

This skill belongs
to everyone.

sustainability.md is released under CC BY 4.0. Use it, adapt it, redistribute it with attribution. The more organizations that integrate sustainability into their AI workflows, the greater the cumulative impact on the experience layer.

Contributions are welcome, especially new authoritative sources, worked examples from additional domains, and updated emissions conversion factors. The skill is versioned semantically; the CHANGELOG is public.

↗ View on GitHub + Open an issue Contributing guide