AI Footprint
io.github.nickjlamb/ai-footprint
Water and energy footprint of AI use: chat prompts, agent sessions, methodology and sources.
This endpoint completed initialize and tools/list. No tool was called.
- Rank
- #1113
- Score
- 82
- Tool tokens
- 952
- Tools
- 4
Tools
Token cost is the o200k count of the tools list JSON, including schemas, before any tool is called.
estimate_ai_footprint
Estimate the water (mL) and energy (Wh) used by chat-style AI prompts (ChatGPT, Claude, Gemini etc.). queries_per_day: prompts per day. usage: 'simple' (text chat, ~0.34 Wh/prompt), 'mixed' (~1 Wh),
get_methodology
Return the per-prompt energy and water figures, accounting boundaries, sources, limitations, a citation line, and the reasons published AI water estimates differ by ~100x (0.3 mL to 50 mL per prompt).
compare_water_use
Convert a volume of water (mL) into everyday comparisons: teaspoons, 500 mL bottles, shower time, and lifecycle items (A4 sheet, almond, cup of tea, beef burger), plus the number of typical AI text pr
estimate_session_footprint
Estimate the water and energy of an AI session (e.g. an agent or coding-assistant run) from its token usage. Pass the SUM across all model calls: input_tokens (uncached prompt tokens), output_tokens (
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