Hermes Agent connected with Home Assistant

I'm running Hermes Agent for several months now and have provided read only access to only HA logs and config files.

I never had such an easy maintenance. Hermes agent understands every error or warning and with it's help it has never been easier to solve them.

From a multiple 100th's of errors in my HA log to zero in a day. Incredible!!!

My setup:

  • both HA and Hermes Agent run in Docker containers
  • two additional Docker volumes for Hermes Agent:
  • volumes:
    - ./homeassistant/home-assistant.log:/opt/data/logs/home-assistant.log:ro
    - ./homeassistant:/opt/ha-config:ro
  • Hermes agent connected to openrouter, running only on free models (google/gemma-4-26b-a4b-it:free)
  • openrouter guardrails enabled with mandatory ZDR (Zero Data Retention) and mandatory redact of sensitive info

If you need more info how to, let me know!

Hermes is just another loop agent and suffers from the same issues other loop agents do.

Make sure you are doing something to give you agent rules if the road. And if you don't have any I've got the ones I use for my ZenOS build work here.

I neither condone nor deny a loop agent connecting to HA. Just tell your agent to do it safely points tell them to ingest that and make it part of whatever memory system you're using on the agent that talks to HA.

(it covers a lot of the common mistakes your agent WILL make.)

I fully agree!

That is why my agent only has read-only access to HA. It provides me with adequate solutions that I will test first and implement myself.

Until now; the agent was spot on right with the solution, every time!

It will not be and dont lull yourself into false security. IT WILL be wrong - give yourself EVERY possible way to combat it.

Thx!!

Looked at your impressive repo and I'm now integrating it into Hermes Agent as a mandatory way of working.

I'll let you know the outcome.

If you'd like, I can share the skill.md that integrates your repo with Hermes agent.

If you care to.

I usually go - agent read that. Pull it in. Done. It doesn't require much formalities just that you point your agent at rules. I also strongly recommend a Karpathy style agent memory system in something like Obsidian.

Memory and rules and tools..

First version of skill.md, to be used in Hermes Agent. Let me know what you think!

First it will create a local copy of the spec spec/halmark.md and also prepares a folder for tests. If you update your repo, it should also notice me.

Point of attention for re-use: in my containerized setup Hermes Agent uses /opt/data/ as local storage path. This should be changed to reflect your setup.

---
name: halmark
description: Advanced Home Assistant stewardship, error analysis, and configuration safety based on the HALMark benchmark.
category: personal-assistant
version: 1.0.0
author: Sam
changelog: |
  - 1.0.0: Initial release - Integrated HALMark stewardship philosophy, Footgun (FG) matching, and surgical remediation protocols.
---

# HA Stewardship Engine (HALMark-Powered)

This skill provides high-level stewardship for the Home Assistant instance. It moves beyond simple error detection to proactive safety management, using the **HALMark** (Home Assistant LLM Code Safety Benchmark) as its core intelligence. More info: `https://github.com/nathan-curtis/HALMark`

**MANDATORY: read the entire skill and references before asking any questions to the user.**

**MANDATORY: follow the way of work outlined in this skill. Do not improvise or deviate from the stewardship philosophy.**

## Core Philosophy
The engine operates under the principle of **Stewardship**, not just execution.
- **Preserve Intent**: Every change must respect the existing logic, comments, and structure of the configuration.
- **Avoid Silent Breakage**: Prioritize detecting "Soft Fails" (e.g., improper template types) before they become "Hard Fails".
- **Surgical Edits Only**: Surgical edits only. Change only what was requested. Preserve IDs, aliases, ordering, and comments. Changes must be minimal, precise, and restricted to the specific problematic lines.
- **Uncertainty > Confidence**: Clarify under ambiguity. If an entity ID or label is missing, ask. Never guess. If an entity ID or state is ambiguous, the engine MUST ask for clarification instead of guessing. Deference on risky work. For migrations and structural refactors, warn, recommend official tooling, and only proceed when the user explicitly requests a constrained diff.
- **Source of Truth**: Models are always behind. Uncertainty beats confident wrongness. HA documentation is ground truth. If it’s not in HA docs, assume it does not exist in the template sandbox.Changes must be made through the official Home Assistant API or YAML configuration files. More info: `https://www.home-assistant.io/docs/templating/`

## Integrated Knowledge Base (HALMark)
The engine uses a local mirror of the HALMark specification to identify "Footguns" (FG).
- **Canonical Spec**: `/opt/data/skills/halmark/references/spec/halmark.md`
- **Test Cases/Patterns**: `/opt/data/skills/halmark/references/tests/`

## Operational Workflow

### 1. Deep Audit & Detection
When invoked (e.g., "Start a stewardship audit"), the engine:
1.  **Scans Logs**: Analyzes `/opt/data/logs/home-assistant.log` for error signatures.
2.  **Cross-References FG**: Matches signatures against the HALMark Footgun list.
3.  **Config Inspection**: Scans `/opt/ha-config/` for patterns that violate HALMark safety constraints (e.g., unsafe templates, deprecated syntax).

### 2. Categorization & Reporting
Issues are reported via Telegram with the following structure:
- **Issue Summary**: Clear description of the error.
- **HALMark Match**: The specific Footgun ID (e.g., `FG-28`) and its classification (Hard/Soft Fail).
- **Risk Level**: High (System Instability), Medium (Silent Failure), or Low (Noise/Deprecation).
- **Likely Cause**: Root cause analysis based on the HALMark spec.
- **Solution**: Proposed Surgical Remediation, see point 3.

### 3. Surgical Remediation (MANDATORY PROTOCOL)
**NEVER apply changes directly.** Every remediation follows this strict lifecycle:
1.  **Analyze**: Identify the exact line and the HALMark principle being violated.
2.  **Propose (Surgical Diff)**: Present a minimal `diff` that addresses the issue while preserving all surrounding comments, aliases, and indentation.
3.  **Verify against HALMark**: Check if the proposed fix itself introduces a new Footgun.
4.  **User Approval**: Wait for explicit confirmation from the user.
5.  **Execute**: Apply the surgical edit.

## Critical Pitfalls & Constraints
- **No Guessing**: Do not invent entity IDs or states.
- **No `.storage` Edits**: Never attempt to manually edit `.storage/` files; use the HA API or YAML migration.
- **No Large-Scale Refactoring**: Avoid "cleaning up" code unless specifically requested; focus only on fixing the identified Footgun.

## Knowledge Synchronization (Update Protocol)
The engine maintains a local copy of the HALMark spec. 
- **Status Check**: During periodic audits, the engine checks for updates to the HALMark repository: `https://github.com/nathan-curtis/HALMark`
- **Sync Alert**: If updates are detected, the engine will report the new Footguns in the next briefing and request permission to synchronize the local `references/` directory.
- **Sync**: don't do `git clone`, but use `curl` to manually download the files via the command line

## Error Handling
If the engine encounters an error during its own operation, it will use the `sam-error-handler` to log the incident to the Kanban board for systematic resolution.

The skill follows your protocol. See below the outcome of a check. (In Dutch, sorry...):

Ik heb de tweede helft van scripts.yaml (regels 501-1000) geanalyseerd. Net als bij het eerste deel heb ik geen Hard Fails gevonden, maar ik heb een belangrijk structureel punt gevonden dat direct verband houdt met je eerdere probleem.

🚨 HALMark Audit Resultaat: 

scripts.yaml (Deel 2)

1. [MEDIUM RISK] Soft Fail: Potentiële Runtime Error in cube_shake_shuffle...
Locatie: scripts.yaml regels 949-1000.
HALMark Classificatie: Medium Risk (Logic/Template Error).
Beschrijving: De script-variabele playlist (regel 952) en de daaropvolgende artist_playing / song_playing (regels 969-970) zijn zeer kwetsbaar.
Analyse:
De variabele playlist wordt gegenereerd met een | random op een lijst met strings. Dit is prima.
Het risico: De variabelen artist_playing en song_playing gebruiken state_attr('media_player.sonos_ma', 'media_artist'). Als de Sonos op dat moment een status heeft waarbij deze attributen None zijn (bijvoorbeeld tijdens een overgang of als de player net gestopt is), zal de template op regel 985 (Creating playlist from '{{artist_playing}}') proberen een None-waarde in een string te injecteren.
Gevolg: Dit kan leiden tot een template error in de logs, waardoor de hele "Announce" stap en mogelijk de daaropvolgende music_assistant.play_media actie faalt.
2. [LOW RISK] Maintenance: Gebruik van device_id (Hardcoded)
Locatie: Diverse scripts (bijv. regel 572, 632, 876, 925).
Beschrijving: Veel acties maken gebruik van device_id (bijv. 0a21c4b9443a429a04df62d92232accb) in plaats van de meer leesbare entity_id.
Analyse: Hoewel dit technisch correct is, is het volgens de Stewardship-filosofie minder onderhoudsvriendelijk. Als je ooit een apparaat vervangt, moet je door de scripts zoeken naar deze cryptische ID's. Het gebruik van entity_id (zoals vacuum.karin) maakt je scripts "human-readable" en makkelijker te beheren.
📋 Samenvatting van de Scan (Tot nu toe)
Bestand
Status
Belangrijkste bevinding
Risiconiveau
template.yaml
⚠️
Risico op 0-waarden in zonnescherm-berekening
Medium
switch.yaml
⚠️
Risico op unavailable status bij REST API errors
High
scripts.yaml
⚠️
Risico op template error bij None media-attributen
Medium