# Green-Stove Agents

- **Event:** [The Recursive Agents Hackathon](https://cerebralvalley.ai/e/crusoe-recursive-agents-hackathon)
- **When:** Sat, Oct 17 at 9:00 AM – 10:00 PM (PDT)
- **Where:** San Francisco, CA
- **Team:** [Emahatsion Issac](https://cerebralvalley.ai/u/issac), [Abel Tesfa](https://cerebralvalley.ai/u/abelSF)
- **GitHub:** https://github.com/amahaeitbit/green-stove-agents
- **Demo video:** https://youtu.be/tyE0F9MvDw4
- **Gallery:** https://cerebralvalley.ai/e/crusoe-recursive-agents-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/crusoe-recursive-agents-hackathon/hackathon/gallery/82

Green-Stove Agents is a team of agents that runs a community solar cooking mini-grid you can walk away from. Off-grid households want to cook on electricity, but a small solar station (3 kW inverter, 6 kWh battery) cannot serve everyone at once. Each household has a different appliance, cooking window and budget.

How it works: a Spec Agent turns a one-line goal into a definition of done. Code may tighten it but never loosen it. A Pricing Agent (Nemotron on Crusoe) proposes time-of-day tariffs. Deterministic household acceptance, allocation and battery admission control turn a tariff into bookings. An independent simulator and verifier check every plan against expected and downside solar forecasts. The forecasts come from cited You.com weather data converted to a PV profile. A Supervisor catches looping and drift, proves infeasibility before spending model calls, and stops honestly with PLAN_VERIFIED, NO_VERIFIED_PLAN or INFEASIBLE, plus an operator decision record.

Shared Brain (primary track): after each run a Note-writer agent proposes observations. A code Keeper admits only notes backed by recorded evidence. It rejects made-up numbers and rule changes, keeps conflicting notes scoped and expires stale ones. A fresh agent gets a 600-token brief instead of a transcript. Memory is frozen for held-out evaluation, where we compare it against no memory, raw history, last-tariff reuse, nearest-context reuse and deterministic search.

Version N+1: a reviewer agent rewrites the Pricing playbook and keeps a change only if it scores better on development days.

Honest scope: the grid is a synthetic simulation. Existing Green-Stove hardware is prior work; the agents, memory, verification and evaluation were built today. We ran the full pipeline live on Crusoe (Nemotron 3 Super 120B) with a live You.com forecast. We have not yet measured a memory benefit on live runs, so that is not claimed. Mock results are labeled MOCK.

## More from The Recursive Agents Hackathon

- [Wayland](https://cerebralvalley.ai/e/crusoe-recursive-agents-hackathon/hackathon/gallery/79)
- [AdCampaigner](https://cerebralvalley.ai/e/crusoe-recursive-agents-hackathon/hackathon/gallery/80)
- [Formloop](https://cerebralvalley.ai/e/crusoe-recursive-agents-hackathon/hackathon/gallery/81)
- [ARC](https://cerebralvalley.ai/e/crusoe-recursive-agents-hackathon/hackathon/gallery/83)
- [CASCADE](https://cerebralvalley.ai/e/crusoe-recursive-agents-hackathon/hackathon/gallery/84)
- [Zen](https://cerebralvalley.ai/e/crusoe-recursive-agents-hackathon/hackathon/gallery/85)

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Markdown version of https://cerebralvalley.ai/e/crusoe-recursive-agents-hackathon/hackathon/gallery/82. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt