Play 69
Carbon Footprint Tracker
Real-time carbon accounting across cloud resources and supply chain.
Real-time carbon accounting across cloud resources and supply chain with automated ESG reporting and reduction recommendations. Azure Monitor collects resource consumption metrics, OpenAI calculates carbon equivalents using emission factor databases, Event Hubs processes real-time supply chain events, and Cosmos DB stores historical carbon data for trend analysis. Generates Scope 1/2/3 reports aligned with GHG Protocol.
Architecture Pattern
Event-driven carbon accounting: resource metrics → emission calculation → reporting → optimization
Azure Services
DevKit (.github Agentic OS)
- agent.md — root orchestrator with builder→reviewer→tuner handoffs
- 3 agents — Carbon Builder (gpt-4o), Reviewer (gpt-4o-mini), Tuner (gpt-4o-mini)
- 3 skills — deploy (281 lines), evaluate (113 lines), tune (188 lines)
- 4 prompts — /deploy, /test, /review, /evaluate with agent routing
- .vscode/mcp.json — FrootAI MCP with OpenAI key input + envFile
TuneKit (AI Config)
- config/openai.json — emission factor analysis prompts
- config/carbon.json — emission factors, scope definitions, reporting frameworks
- config/guardrails.json — data accuracy, audit trail
- evaluation/eval.py — Calculation accuracy >95%, Report compliance >90%
Tuning Parameters
Machine evidence
FrootAI evidence lifecycle
This is an internal evidence maturity label, not third-party certification, accreditation, legal compliance, or a production guarantee. Missing or expired evidence demotes automatically; catalog claims cannot promote a play.
This play currently has design evidence only. A runnable scenario, endpoint evaluation, and build receipts are the next contiguous gates.
Repo Intelligence
v1A no-clone, revision-pinned map for agents and humans. Observed evidence is separated from inferred flow so the output stays useful without pretending to be a full call graph.