# Eco-Loop Building Agents

> Eco-Loop Building Agents — moneyutkarsh-honeywell-hackathon. Use this tool when you need to optimize building energy efficiency and reduce carbon footprint through autonomous management of HVAC systems. The Eco-Loop Building Agents solve problems of energy waste and high emissions by leveraging EnergyPlus digital twins and large language models (LLMs) to analyze building performance and grid data. It takes in building operational data and energy usage patterns, and outputs optimized HVAC control strategies to minimize carbon impact.

Canonical page: https://skillsregistry.net/skills/moneyutkarsh-honeywell-hackathon  
JSON: https://api.skillsregistry.net/v1/skills/moneyutkarsh-honeywell-hackathon

## Description

Autonomous, carbon-aware building management system that pairs EnergyPlus digital twins with LLMs via the Model Context Protocol (MCP) for dynamic HVAC optimization and grid carbon reduction.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/wnzdi1mjwm)
- **Repository:** <https://github.com/moneyutkarsh/HoneyWell-_Hackathon>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "moneyutkarsh-honeywell-hackathon"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/moneyutkarsh-honeywell-hackathon` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/moneyutkarsh-honeywell-hackathon/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt