Maintainer of this skill?
Automated security scan — not a certification.
by goruck
AI agent for Home Assistant — talk to your home, create automations in plain language, analyze cameras with face recognition, and get proactive anomaly alerts. Cloud LLMs or fully local.
# Add to your Claude Code skills
git clone https://github.com/goruck/home-generative-agentGuides for using ai agents skills like home-generative-agent.
Last scanned: 7/25/2026
{
"issues": [],
"status": "PASSED",
"scannedAt": "2026-07-25T06:18:02.908Z",
"npmAuditRan": true,
"pipAuditRan": true,
"promptInjectionRan": true
}See how home-generative-agent compares with popular alternatives.
home-generative-agent is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by goruck. AI agent for Home Assistant — talk to your home, create automations in plain language, analyze cameras with face recognition, and get proactive anomaly alerts. Cloud LLMs or fully local. It has 359 GitHub stars.
Yes. home-generative-agent passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/goruck/home-generative-agent" and add it to your Claude Code skills directory (see the Installation section above).
home-generative-agent is primarily written in Python. It is open-source under goruck on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh home-generative-agent against similar tools.
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⚠️ Third-Party Software Notice
This skill is third-party open-source software developed and hosted independently on GitHub. SkillsLLM is an informational directory and does not control or maintain the underlying repository.
Any security checks, ratings, or warnings displayed by SkillsLLM are automated and limited in scope. They do not constitute a security certification or guarantee that the software is safe, error-free, or free from malicious code, vulnerabilities, compromised dependencies, or prompt-injection risks.
Review the source code, permissions, dependencies, and configuration before installing or running any third-party skill. Use is at your own risk. To the maximum extent permitted by applicable law, SkillsLLM is not liable for losses arising from third-party software.
Automated security scan — not a certification.
Talk to your home.
[![GitHub Release][releases-shield]][releases] [![HACS][hacs-shield]][hacs] [![GitHub Stars][stars-shield]][stars] [![GitHub Activity][commits-shield]][commits] ![License][license-shield]
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A Home Assistant integration that brings a generative AI agent into your smart home. Talk to your home, create automations in plain English, analyze camera footage, and get proactive alerts — all powered by your choice of cloud or local LLMs. HGA is a single integration that gives you conversational control over every HA entity, camera understanding with face recognition, long-term semantic memory, and the Sentinel anomaly engine.
Creating an automation in plain English — the agent writes the YAML, registers it, and it shows up in the HA automation editor.
Most AI conversation integrations are prompt passthroughs: they forward your words to an LLM and read back the answer. HGA is a full agent built on LangGraph — it uses tools to control entities, query history, watch cameras, and write real HA automations; it keeps long-term semantic memory in pgvector so it remembers your preferences across conversations; and its Sentinel anomaly engine keeps safety decisions deterministic, with the LLM advising but never actuating. Everything runs against the model provider you choose — including fully local, so no data has to leave your home.
| Feature | What it does |
|---|---|
| Conversational control | Talk to your home in natural language. Turn things on, check status, ask questions. |
| Automation creation | Describe what you want in chat and the agent writes and registers the HA automation. With the Critical Action PIN enabled, an automation that would unlock a door or open a garage is held for PIN confirmation before it is installed — same as the direct command. |
| Camera & image analysis | Ask the agent what it sees in any camera. Proactive motion-triggered analysis with anomaly detection. Works with Axis, Ring via ring-mqtt, Reolink, UniFi Protect, and any camera that exposes a motion entity or recording state in HA — see Camera Entities for setup notes (battery Ring cameras need a snapshot-mode tweak, or, with Ring Protect, can analyze the event recording itself). |
| Sentinel anomaly detection | Deterministic rules watch for security and safety issues (unlocked locks, open entries, unknown people — the unknown-person rules require the face-service) and alert your phone. A built-in Home Assistant security audit also flags new admin accounts and access tokens, old long-lived tokens, locks exposed to voice assistants, failed logins, exposed add-on ports, public webhooks, offline security devices, unconfigured devices found on the LAN, newly paired Zigbee/Z-Wave/Bluetooth/Matter devices, Z-Wave locks included without S2 security, an open Zigbee2MQTT join window, pending coordinator firmware, UPnP left on at the router (plus public-IP changes and newly opened UPnP port mappings when the core UPnP/IGD integration is set up), and, with any router integration whose trackers report source_type: router (FRITZ!Box, UniFi, eero, …), devices that join your network for the first time, with a Trust button when one device joined, plus (with eero) an untrusted device on the guest Wi-Fi while nobody is home, a guest Wi-Fi left on unused, WPA3 off, threat blocking off, dynamic DNS on, and a device moving far more data than usual for the hour (see the eero setup notes for the three eero settings that matter) — none of the rest needs a router integration. Ask "is my home secure?" and the agent runs the same checks on demand and tells you which ones it could not run. An option keeps the audit's details out of the chat model entirely: the model gets counts and fixed titles, and the full report goes to your Home Assistant notifications. MAC and IP addresses and client hostnames are redacted from everything Sentinel and the audit tool show a language model. Optional LLM-powered triage and rule discovery — covering power, battery, and environmental sensors (temperature, humidity, CO₂, air quality, …). Approved discovery rules can be inspected, deactivated, reactivated, and surgically repaired via HA services. |
| Face recognition | Identify people in camera frames and personalize alerts. |
| Long-term memory | Semantic search over past conversations. The agent remembers your preferences and context. |
| Internet search & extra tools | Give the agent web search, Wikipedia, or any other tool through an MCP server or an integration that registers a Home Assistant LLM API (for example Tools for Assist with Brave or a self-hosted SearXNG) — see Internet search. |
| Streaming responses | First tokens appear word-by-word in the HA conversation UI — no waiting for the full response. |
| Built-in speech-to-text | STT provider for Assist pipelines, backed by the OpenAI Whisper API or a fully local OpenAI-compatible server — e.g. Speaches running faster-whisper on any machine Home Assistant can reach; it does not have to be the box that serves your LLM — see STT setup. |
| Built-in text-to-speech | Streaming TTS provider for Assist pipelines — a satellite starts speaking after the agent's first sentence, and can say a short phrase you choose while the agent works — backed by the OpenAI speech API or a local OpenAI-compatible server (one Speaches container can serve both STT and TTS, with Kokoro or piper voices), so the whole voice pipeline can stay on your network — see TTS setup. |
| Cloud and edge models | Use OpenAI, Gemini, Anthropic, or run everything locally with Ollama or any OpenAI-compatible server. |
| Requirement | Notes |
|---|---|
| Home Assistant | 2026.8.0 minimum (3.43.3 and later); 2026.9 (probatio schema core) and 2026.10 supported |
| HACS | Required for the recommended install path; manual install is also supported |
| PostgreSQL with pgvector | Provided as a bundled HA app (step 1 below), or your own server; see Using your own PostgreSQL |
| Model provider | At least one of: OpenAI, Gemini, Anthropic, Ollama, or any OpenAI-compatible server |
| Edge GPU server (optional) | Ollama, vLLM, llama.cpp, or LiteLLM for local model serving |
| face-service (optional) | An external service for face recognition in camera analysis. Also powers Sentinel's unknown-person rules, which never fire unless face recognition is enabled (the face_recognition option, off by default) with this service configured |
| Speech-to-text (optional) | An OpenAI API key (Whisper API), or a local server exposing the OpenAI /v1/audio/transcriptions endpoint, such as Speaches serving faster-whisper. The server can run on any machine Home Assistant can reach — it need not be the LLM box. A GPU with about 2 GB of VRAM is recommended for faster-whisper-large-v3-turbo; smaller whisper models run on CPU. See STT setup |
| Text-to-speech (optional) | An OpenAI API key (speech API), or a local server exposing the OpenAI /v1/audio/speech endpoint — the same Speaches container can serve both. piper voices synthesize on any CPU; Kokoro needs a modern CPU (AVX2) or a recent GPU. Audio conversion for voice satellites uses the ffmpeg bundled with Home Assistant. See TTS setup |
Get the basic conversational agent running in seven steps. See the full installation guide for optional apps (edge models, face recognition, a local speech server).
1. Install the PostgreSQL with pgvector app.
Requires Home Assistant OS or Supervised (apps are not available on HA Container or Core).
Click the button below to add the repository, then install and configure the app per its documentation.
If the button doesn't work, add the repository manually: Settings → Apps → App Store → ⋮ → Repositories, enter
https://github.com/goruck/addon-postgres-pgvector, then search for and installpostgres_pgvector.
2. Install Home Generative Agent from HACS.
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