An open AI skill · v1.1.0 · CC BY 4.0

Sustainability belongs
in 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.

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.

AI has 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.

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 — and it's mostly going unused on sustainability.

sustainability.md exists to change that. It's a skill file you install once — in your AI's system prompt, in your team's shared configuration, or in a single conversation — and sustainability analysis joins your work from the start, not as an afterthought.

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Four behaviors,
always integrated.

When active, the sustainability skill instructs AI to apply four analytical behaviors to every relevant response — woven into the work, not appended to it.

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: printed onboarding materials, shipped welcome kits, recommendation algorithms that suppress sustainable options, overproduction defaults in food service, over-provisioned infrastructure.

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

ChatGPT

ChatGPT supports persistent custom instructions that apply to every conversation.

Click your profile picture (bottom-left) → Customize ChatGPT → in the "What would you like ChatGPT to know about you?" or "How would you like ChatGPT to respond?" field, paste the instruction above → click Save. It will be active in all new chats.

Gemini

Gemini supports persistent instructions through Gems — custom AI configurations you save and reuse.

Go to gemini.google.com → click Gems in the left sidebar → click New Gem → give it a name (e.g., "Sustainability") → in the instructions field, paste the instruction above → click Save. Open this Gem whenever you want sustainability analysis active.

Claude

Claude supports persistent instructions through Projects — shared workspaces that retain context across conversations.

Go to claude.ai → click Projects in the left sidebar → create a new Project or open an existing one → click Project instructions → paste the instruction above → click Save. Every conversation inside that Project will have the skill active.

Llama (via local runners)

If you're running Llama locally through Ollama, LM Studio, or a similar tool, paste the instruction into the system prompt field before starting a session.

In Ollama: include it in your Modelfile as a SYSTEM directive. In LM Studio: paste it into the System Prompt field in the Chat panel. For API usage, pass it as the system parameter in your request body.

The skill in action
across domains.

Each example shows how sustainability analysis changes what gets surfaced — and what gets built — when it's integrated from the start rather than bolted on at the end.

CX / UX Design
CX Professionals as Sustainability Multipliers
Three reference cases — LUT University, Klarna, Google Hotels — showing the pattern: experience scale > tool scale, and intention gaps > motivation gaps.
Read example →
HR / L&D
Sustainable New Hire Onboarding
Applying the skill to onboarding experience design: async video vs. live sessions, digital vs. printed materials, shipped kits vs. digital-first welcome.
Read example →
Operations
Food Service and Demand Forecasting
How AI-driven operational experience design reduced food waste by 20% at LUT University — and what this pattern means for any organization running food service at scale.
Read example →

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.

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.