Install
$ agentstack add skill-dcb-homeassistant-claude-kit-setup-customize Open-source listing, not yet scanned by AgentStack. Follow the source repository for install instructions.
Security review
⚠ Flagged1 finding(s); flagged for manual review. · v0.1.0 How review works →
- • Prompt-injection patterns
- • Secret / credential exfiltration
- • Dangerous shell & filesystem operations
- • Untrusted network calls
- • Known-malicious package signatures
- high Reads credentials/environment and may exfiltrate them.
What it can access
- ● Network access Used
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ● Environment & secrets Used
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Setup Customize
This skill maps your Home Assistant instance to the dashboard and automation templates through a guided interview. It is resumable — if the conversation ends mid-way, re-invoke this skill and it will pick up from the last checkpoint.
See references/question-patterns.md for detailed question wording and example answers for each domain.
Step 0: Check Prerequisites
Verify setup-state.json exists and infrastructure is complete:
import json, sys, os
if not os.path.exists('setup-state.json'):
print('NOT_READY'); sys.exit(0)
with open('setup-state.json') as f:
state = json.load(f)
schema = state.get('schema_version', 0)
if schema > 1:
print('SCHEMA_WARNING')
phase = state.get('session', {}).get('current_phase', '')
infra = state.get('infrastructure', {}).get('steps_completed', [])
if 'infrastructure_complete' in phase or 'pull' in infra:
answers = state.get('answers', {})
if answers.get('rooms') or phase.startswith('customize:'):
print('RESUME')
print(f'PHASE:{phase}')
print(f'ROOMS_DONE:{",".join(answers.get("rooms", {}).keys())}')
else:
print('FRESH')
else:
print('NOT_READY')
Run via python3 -c "..." and check the output:
NOT_READY: Tell user to runsetup-infrastructurefirst.SCHEMA_WARNING: State file from newer version — proceed with caution.RESUME: Load checkpoint. Tell user: "Welcome back! You were at [phase]. Rooms done: [list]. Continuing."FRESH: Begin from Phase 1.
Checkpoint Writing Pattern
After EVERY user answer, update setup-state.json with granular progress:
import json
def save_checkpoint(phase, answers_update=None, files_written=None):
with open('setup-state.json') as f:
state = json.load(f)
state['session']['current_phase'] = phase
if answers_update:
state.setdefault('answers', {}).update(answers_update)
if files_written:
state.setdefault('files_written', []).extend(files_written)
with open('setup-state.json', 'w') as f:
json.dump(state, f, indent=2)
Example calls:
save_checkpoint('customize:room_mapping', {'rooms': {'living_room': {'light': '...', 'motion': '...'}}})save_checkpoint('customize:domain_selection', {'domains_selected': ['lighting', 'climate']})save_checkpoint('customize:notifications', {'notify_targets': {'primary': 'notify.mobile_app_x'}})save_checkpoint('customize:files', files_written=['config/automations/lighting.yaml'])
Step 1: Discover Entity + Area + Floor Registries
Primary method: Use registry data. Entity-to-room assignment should come from the device/entity registries (via area_id) whenever possible. This is the authoritative source.
Fallback: Name inference + user confirmation. If the registries have sparse area assignments (common in setups where the user hasn't organized areas in HA), you may infer room assignments from entity ID naming patterns (e.g., bedroom_motion → bedroom). However, when using name inference, you MUST:
- Clearly mark inferred assignments as "inferred (not in registry)"
- Ask the user to confirm ALL inferred assignments before proceeding
- Never present inferred data as verified fact
1a. Query Floor + Area Registries
Get the authoritative room and floor structure:
source .env && ssh "$SSH_USER@$HA_HOST" "source /etc/profile.d/claude-ha.sh; source ${HA_REMOTE_PATH:=/config/}.env; ha-ws raw config/floor_registry/list" 2>/dev/null
source .env && ssh "$SSH_USER@$HA_HOST" "source /etc/profile.d/claude-ha.sh; source ${HA_REMOTE_PATH}.env; ha-ws raw config/area_registry/list" 2>/dev/null
This gives you:
- All floors with IDs and names
- All areas with
floor_idassignments - Do NOT ask the user about floors if this data is available.
1b. Query Device + Entity Registries
Get the authoritative entity-to-area mappings:
source .env && ssh "$SSH_USER@$HA_HOST" "source /etc/profile.d/claude-ha.sh; source ${HA_REMOTE_PATH}.env; ha-ws raw config/device_registry/list" 2>/dev/null
source .env && ssh "$SSH_USER@$HA_HOST" "source /etc/profile.d/claude-ha.sh; source ${HA_REMOTE_PATH}.env; ha-ws raw config/entity_registry/list" 2>/dev/null
Entity-to-area resolution chain:
- Check
entity_registry→ if the entity has a directarea_id, use it - Otherwise, find the entity's
device_id→ look up that device indevice_registry→ use the device'sarea_id - If neither has an
area_id, the entity is unassigned — note it but do NOT guess
1c. Query Entities by Domain
For each relevant domain, query the live entity list:
source .env
for domain in light binary_sensor sensor climate media_player camera cover vacuum remote switch; do
ssh "$SSH_USER@$HA_HOST" "source /etc/profile.d/claude-ha.sh; source ${HA_REMOTE_PATH}.env; ha-ws entity list $domain" 2>/dev/null
done
1d. Build Verified Room-Entity Map
Cross-reference the entity list with the device/entity registry area assignments to build a verified mapping. For each room, list:
- Lights (prefer zone/group entities over individual bulbs)
- Motion sensors (
binary_sensor.*withdevice_class: motionoroccupancy) - Temperature sensors
- Climate entities (TRVs, AC units)
- Media players
- Cameras
Before presenting any mapping to the user: mark each assignment's source:
- Registry: directly from device/entity registry
area_id— present as fact - Inferred: from entity ID naming pattern — present with a
?mark, ask user to confirm - Unassigned: no area in registry and no clear naming pattern — ask the user
1e. Fallback: Local .storage Files
If SSH/ha-ws is unavailable, parse the local .storage/ files (pulled by make pull):
source venv/bin/activate && python tools/entity_explorer.py --full 2>/dev/null | head -100
Or use the REST API as a last resort:
source .env && set -a && source .env && set +a && python3 -c "
import urllib.request, json, os
url = os.environ['HA_URL'] + '/api/states'
req = urllib.request.Request(url, headers={'Authorization': 'Bearer ' + os.environ['HA_TOKEN']})
with urllib.request.urlopen(req) as r:
states = json.load(r)
domains = {}
for s in states:
d = s['entity_id'].split('.')[0]
domains[d] = domains.get(d, 0) + 1
for d, c in sorted(domains.items()):
print(f'{d}: {c} entities')
"
Summarize what was found: "Found X floors, Y areas, Z lights, W climate entities, ..."
Step 2: Room Mapping (Phase 1)
See references/question-patterns.md → Phase 1 for question wording.
Goal: Build a RoomConfig[] array for dashboard/src/lib/areas.ts.
- Present the verified room-entity map from Step 1d to the user. This should already
include floor assignments (from the floor registry), entity assignments (from device/entity registries), and all detected sensors/lights/climate/media per room.
- Ask the user to confirm, correct, or skip each room. Common corrections:
- Merging rooms (e.g., kitchen + storage → one zone)
- Renaming rooms for the dashboard
- Skipping rooms they don't want on the dashboard
- Only ask about floors if the floor registry returned no data. If floors are assigned
in HA, use those values directly.
- For each confirmed room, verify entity assignments match what the user expects.
If any entity was listed as "unassigned" in Step 1d, ask the user to assign it.
- Save progress to
setup-state.jsonafter each room confirmation.
Generate areas.ts once all rooms are confirmed:
// dashboard/src/lib/areas.ts — generated by setup-customize
export interface RoomConfig {
id: string;
name: string;
floor: number;
icon: string;
light?: string; // primary light entity
motionSensor?: string;
temperatureSensor?: string;
mediaPlayer?: string;
climate?: string;
}
export const ROOMS: RoomConfig[] = [
// REPLACE: Add your rooms here (generated from interview)
// { id: "living_room", name: "Living Room", floor: 0, icon: "sofa", light: "light.living_room" },
];
// Maps HA person entity → display name
export const USER_ROOM_MAP: Record = {};
Step 3: Entity Specialization (Phase 2)
For each room, ask domain-specific questions:
Lights:
- Is the main light a Hue zone/group or individual bulbs?
- Any motion-triggered lights in this room? (entity ID)
- Luminance sensor? (for light-level gating)
Climate:
- Thermostat/TRV or AC unit?
- TRV entity ID (for zone control)
Media:
- TV / media player entity?
- Remote entity? (for IR/HDMI control)
Save answers to setup-state.json as you go.
Step 4: Domain Selection (Phase 3)
Present automation domains as a checklist. Ask the user which apply to their setup:
Which automation domains do you want to set up?
□ Motion lights (auto on/off with motion sensors)
□ Activity modes (night mode, movie mode, work mode)
□ Climate scheduling (morning/night temperature changes)
□ Away mode (setback when nobody home)
□ Appliance tracking (washer/dishwasher state machine)
□ Health monitoring (integration watchdogs, battery alerts)
□ EV/Solar charging (if you have solar + EV)
□ AC solar heating (if you have solar + AC units)
□ None — I'll write my own automations
For each selected domain, note which automation template to use from docs/templates/config/automations/.
Step 5: Behavioral Interview (Phase 4)
Ask about preferences that drive automation behavior. See references/question-patterns.md → Phase 4 for full question bank.
Key questions:
- What time do you typically wake up on weekdays? Weekends?
- What time is bedtime on weekdays? Weekends?
- Who lives in the home? (for presence tracking — no custody/schedule details needed)
- Do you work from home? (drives
work_modeauto-trigger) - What's your preferred daytime temperature? Night temperature?
- Battery alert threshold? (default: 10%)
- Any devices that should NOT be automated? (creates exceptions list)
Save all answers to setup-state.json.
Step 6: Notification Discovery (Phase 5)
Discover available notification targets:
set -a && source .env && set +a && python3 -c "
import urllib.request, json, os
url = os.environ['HA_URL'] + '/api/services'
req = urllib.request.Request(url, headers={'Authorization': 'Bearer ' + os.environ['HA_TOKEN']})
with urllib.request.urlopen(req) as r:
services = json.load(r)
notify = [s for s in services if s.get('domain') == 'notify']
for n in notify:
for svc in n.get('services', {}).keys():
print(f'notify.{svc}')
" 2>/dev/null
Alternatively, use SSH + ha-api (more reliable):
source .env && ssh "$SSH_USER@$HA_HOST" "source /etc/profile.d/claude-ha.sh; source ${HA_REMOTE_PATH:=/config/}.env; ha-api search notify"
Ask the user which targets to use for:
- Primary notifications (most alerts)
- Critical alerts (security, health)
Step 7: Helpers Merge
Read existing configuration.yaml and check if it already has input_* helpers:
grep -l "input_boolean:\|input_select:\|input_number:" config/configuration.yaml 2>/dev/null && echo "has_helpers" || echo "no_helpers"
If existing helpers found: Show them and ask: > "Your configuration.yaml already has input helpers. I can: > (A) Keep them where they are and add only missing ones from the templates > (B) Consolidate all helpers into config/helpers.yaml and use !include helpers.yaml > > Which do you prefer?"
Never silently move or overwrite existing helpers.
Step 8: Generate Configuration Files
Based on all interview answers, generate:
dashboard/src/lib/entities.ts
// dashboard/src/lib/entities.ts — generated by setup-customize
// Edit this file to update entity mappings. Re-run setup-customize to regenerate.
// ── Modes ──────────────────────────────────────────────────────────────────
export const NIGHT_MODE = "input_boolean.night_mode";
export const MOVIE_MODE = "input_boolean.movie_mode";
export const WORK_MODE = "input_boolean.work_mode";
export const AWAY_MODE = "input_boolean.away_mode";
export const CLIMATE_MODE = "input_select.your_climate_mode"; // # REPLACE: or remove
// ── People ─────────────────────────────────────────────────────────────────
// Add your person entity IDs here
export const PERSONS: string[] = [];
// ── Add your entities below ────────────────────────────────────────────────
// (Generated from interview answers — each room's entities added here)
Automation YAML files
For each selected domain, copy the template and substitute placeholder IDs:
your_room_motion_sensor→ actual entity ID from interviewyour_notify_target→ chosen notification targetyour_morning_work_day(input_datetime) → keep as-is (user sets value in HA UI)
Copy template files to config/automations/:
# Example for lighting:
cp docs/templates/config/automations/lighting.yaml config/automations/lighting.yaml
# Then perform substitutions based on interview answers
docs/system-overview.md and docs/house-rules.md
Populate the template sections with interview answers. Leave blank sections with the original guidance comments for sections not covered.
Step 9: Build + Deploy
- Install dashboard dependencies (if not already installed):
``bash cd dashboard && npm install && cd .. ``
- Verify TypeScript compiles cleanly before deploying:
``bash cd dashboard && npx tsc -b --noEmit && cd .. `` If this fails, fix the errors before proceeding. Common issues:
- Entity constants with empty string
"" as EntityIdneed actual entity IDs or removal - Missing
@types/*packages → runnpm installfirst
- Run backup:
``bash make backup ``
- Push configuration:
``bash make push ``
- Deploy dashboard:
``bash make deploy-dashboard ``
- Verify by asking the user to open HA and confirm the dashboard panel appears.
Provide the URL: http://[HA_URL]/custom-dashboard
Optional: Make the dashboard the default view
After the dashboard deploys successfully, ask the user:
> "Would you like to make this dashboard your default view when opening Home Assistant? > This requires installing the Custom Sidebar > plugin via HACS. If you don't have HACS, you can skip this — your dashboard is still > accessible from the sidebar."
If the user wants this:
- Verify HACS is installed:
``bash source .env && ssh "$SSH_USER@$HA_HOST" "source /etc/profile.d/claude-ha.sh; source ${HA_REMOTE_PATH:=/config/}.env; ha-api state sensor.hacs" 2>/dev/null `` If HACS is not installed, tell the user to install it first from hacs.xyz and skip this step.
- Tell the user to install Custom Sidebar via HACS:
- Open HA → HACS → Frontend → search "Custom Sidebar" → Install
- This cannot be done via CLI — HACS frontend installations require the UI
- Once confirmed installed, add the plugin to
configuration.yamlunderfrontend:
```yaml frontend: extramoduleurl:
- /hacsfiles/custom-sidebar/custom-sidebar-plugin.js
`` **Merge with existing frontend:` block** — do not duplicate the key.
- Create
config/custom-sidebar-config.yaml:
``yaml default_path: /custom-dashboard ``
- Push the config and tell the user to restart HA (this change requires a restart, not just a reload):
``bash make push ``
Step 10: Save Completion Checkpoint
python3 -c "
import json, datetime
with open('setup-state.json') as f:
state = json.load(f)
state['session']['current_step'] = 'customize_complete'
state['session']['steps_completed'].append('customize')
state['session']['completed_at'] = datetime.datetime.now().isoformat()
with open('setup-state.json', 'w') as f:
json.dump(state, f, indent=2)
print('Setup complete. setup-state.json updated.')
"
Completion Message
> "Setup complet
…
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: dcb
- Source: dcb/homeassistant-claude-kit
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.