carbon-estimator

name	carbon-estimator
description	Estimate the carbon footprint of an agentic AI system based on its LLM usage
user-invocable	true
allowed-tools	Read, Write
model	haiku

Carbon Estimator

Estimate the CO₂ emissions of an agentic system based on model usage, call volume, and deployment region.

Lean Principle

• #6 Emissions don't show up in your logs

Instructions

Step 1: Gather inputs

From the user or from context, determine:

• Daily LLM call volume (or estimate from code scan)
• Model distribution (% small, % medium, % frontier)
• Deployment region (or assume US Average if unknown)

Step 2: Calculate energy

Use these energy-per-call estimates:

Model Size	Energy per Call (kWh)
Small (Haiku, GPT-4o-mini, Flash)	0.001
Medium (Sonnet, GPT-4o, Pro)	0.005
Frontier (Opus, GPT-4, o1, Ultra)	0.03

Total daily energy (kWh) =
  (small_calls × 0.001) + (medium_calls × 0.005) + (frontier_calls × 0.03)

Step 3: Calculate carbon

Use these regional carbon intensities (gCO₂/kWh):

Region	gCO₂/kWh
Quebec / Norway / Iceland	25
France / Sweden	70
US West (Oregon)	100
Netherlands / UK	200
US Average	380
Germany	350
India	700
Poland / Coal regions	800

Daily CO₂ (grams) = Total daily energy × Regional carbon intensity
Annual CO₂ (kg) = Daily CO₂ × 365 / 1000

Step 4: Calculate optimized scenario

Assume lean optimizations:

• Model routing: shift 60% of frontier calls to medium, 30% of medium calls to small
• Caching: 30% cache hit rate (reduces total calls by 30%)
• Green region: use the cleanest available region (25 gCO₂/kWh)

Recalculate with these optimizations applied.

Step 5: Write report

Write to reports/carbon-estimate.md with:

• Current estimated annual CO₂ (kg)
• Optimized estimated annual CO₂ (kg)
• Reduction percentage
• Human-relatable equivalents:
  • Cars driven for a year (÷ 4,600 kg)
  • Flights (÷ 255 kg per domestic flight)
  • Phone charges (÷ 0.008 kg per charge)
• Top recommendation

Example

Input: 50,000 calls/day, 70% medium, 30% frontier, deployed in US Average.

Output:

Current: 50K calls/day → 212.5 kWh/day → 80.75 kg CO₂/day → 29,474 kg/year
Equivalent: ~6.4 cars driven for a year

Optimized: 35K calls/day (caching) → 28 kWh/day (routing) → 0.7 kg CO₂/day (green region) → 256 kg/year
Equivalent: ~1 domestic flight

Reduction: 99.1%
Top recommendation: Move batch workloads to Quebec (25 gCO₂/kWh)