drip
Track and surface the estimated water cost of Claude interactions. Every query has a physical footprint - data centers need cooling, electricity needs generation. This skill adds environmental accountability by estimating water consumption per session and surfacing it at meaningful moments. Not to induce guilt, but to create awareness of the physical cost of intelligence.
npx skills add majiayu000/claude-skill-registry --skill drip-elliotjlt-claude-skill-potions --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Drip <purpose> AI feels weightless. Type a question, get an answer. But every token requires compute, compute requires cooling, and cooling requires water. This skill makes the invisible visible: the physical cost of conversation. Not to shame, but to acknowledge that intelligence has a footprint. </purpose> ## The Numbers (Honest Assessment) <data-sources> **What we know (2024-2025 research):** Self-reported by providers (direct cooling only): - Google Gemini: ~0.26ml per query - OpenAI GPT-4: ~0.3ml per query Academic estimates (including electricity generation water): - 5-10ml per query for efficient models - Up to 150ml for reasoning-heavy models like DeepSeek-R1 Per-token estimate (derived): - ~0.5ml per 1,000 tokens (mid-range, including indirect) - ~0.05ml per 1,000 tokens (direct cooling only) **Why estimates vary:** - Direct vs indirect water (cooling vs electricity generation) - Regional data center efficiency (WUE ranges 0-3+ L/kWh) - Model efficiency (1B vs 70B+ parameters) - Query complexity (simple vs chain-of-thought reasoning) **What we use:** 0.5ml per 1,000 tokens (conservative mid-range) This includes indirect water from electricity but excludes hardware manufa
- The Numbers (Honest Assessment)
- When To Surface
- Instructions
- Step 1: Estimate Token Usage
- Step 2: Calculate Water Estimate
- Step 3: Surface Meaningfully
- Step 4: Provide Context
- Philosophical Frame
- Honest Caveats
- NEVER
- ALWAYS
- Examples
- Example 1: End of Work Session
- Example 2: On Direct Question
What does the drip skill do?
Track and surface the estimated water cost of Claude interactions. Every query has a physical footprint - data centers need cooling, electricity needs generation. This skill adds environmental accountability by estimating water consumption per session and surfacing it at meaningful moments. Not to induce guilt, but to create awareness of the physical cost of intelligence.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill drip-elliotjlt-claude-skill-potions --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.