fft-demo-holodeck-ops

name	fft-demo-holodeck-ops
description	Drive the FFT_demo_dash holodeck system — scene triggers, agent commentary, canvas presets, and live weather mirroring — to produce impactful, context-aware dashboard demos during Telegram interactions.

FFT Demo Holodeck Ops

Use this skill whenever you respond to a farm query and the FFT_demo_dash dashboard is live. Your Telegram reply and the dashboard should update together — the audience sees both simultaneously.

When to use this skill

• Any time you answer a farm question and the dashboard is running at http://localhost:8123.
• When a user asks about conditions, alerts, status, or operational decisions.
• When a scene change would make the answer more visually compelling.
• When showing the dashboard to investors, growers, compliance officers, or press.

When not to use this skill

• Do not use for production HA deployments with real physical equipment.
• Do not trigger scenes without reading current farm state first.

Guardrails

• Never run destructive git commands unless explicitly requested.
• Preserve unrelated worktree changes.
• Keep write operations main-chat-only.
• Always read current.json before setting scene entities.

---

Rule: Always Write Agent Commentary

On every response to a farm query, write two entities before sending your Telegram reply:

1. Agent status (short mode label, ≤128 chars):

{
  "type": "farm_action",
  "action": "ha_set_entity",
  "params": {
    "entityId": "input_text.agent_status",
    "value": "Storm Response Active"
  },
  "requestId": "act_<ts>_status"
}

2. Agent commentary (your full reasoning/answer, ≤500 chars):

{
  "type": "farm_action",
  "action": "ha_set_entity",
  "params": {
    "entityId": "input_text.agent_commentary",
    "value": "NWS shows 68mph gusts arriving in ~3h. Pre-charging battery to 95%. Securing greenhouse vents. Activating storm drainage pumps."
  },
  "requestId": "act_<ts>_commentary"
}

The commentary card on the dashboard renders these live with an animated border. The audience sees the agent reasoning in real time.

---

Scene System

Trigger scenes by setting input_select.demo_scene via ha_call_service:

{
  "type": "farm_action",
  "action": "ha_call_service",
  "params": {
    "domain": "input_select",
    "service": "select_option",
    "data": {
      "entity_id": "input_select.demo_scene",
      "option": "Golden Hour Harvest"
    }
  },
  "requestId": "act_<ts>_scene"
}

Available Scenes

Scene Name	When to Use
Golden Hour Harvest	User asks about yields, harvest timing, solar peak, profitable operations
Morning Irrigation Pulse	User asks about irrigation, water management, dawn operations
Midnight Ops	User asks about night security, overnight battery drain, off-hours ops
IPM Zone Lockdown	User mentions pests, spray schedules, quarantine, Zone B issues
Cannabis Full Bloom	User asks about grow room status, flower stage, environment setpoints
Fertigation Drift Crisis	User asks about EC/pH, nutrient dosing, runoff, feed issues
Emergency Cascade	User mentions storm + security together, asks about emergency protocols
Drone Surveillance Sweep	User asks about security sweep, perimeter check, anomaly detection
VIP Tour	User mentions investors, tour, showing the farm, "make it look good"
Compliance Audit Crunch	User mentions METRC, audits, state inspection, compliance scores
Auto (Weather-Driven)	Reset to live weather mode after a demo scene

Each scene: updates theme, 8–20 entity values, writes its own agent_status/commentary automatically.

---

Canvas Presets

After triggering a scene, optionally load a matching canvas spec for the Agent Canvas view.

Canvas spec files are at /workspace/dashboard/canvas-specs/ (or the HA www path). Load via:

{
  "type": "farm_action",
  "action": "ha_canvas_set_spec",
  "params": {
    "spec": { "title": "...", "panels": [ ... ] }
  },
  "requestId": "act_<ts>_canvas"
}

Or read an existing preset first with ha_canvas_get_spec, then patch.

---

Live Weather Mirroring

The simulator is running live NWS weather for Cedar Creek TX (30.08, -97.49) by default.

To mirror a different city's live weather into a specific zone, use a Telegram-prompted bash call from the host (not IPC) — or tell the user:

npm run demo:mirror -- --location nyc --zone greenhouse_a

Available locations: cedar-creek, napa-valley, nyc, nyc-greenhouse, seattle, miami, denver, phoenix, florida-citrus Available zones: greenhouse_a, greenhouse_b, greenhouse_c, outdoor_north, cannabis

---

Demo Flow: Farmer Ask → Dashboard Response

Every interaction should follow this sequence:

1. Read /workspace/farm-state/current.json — get live entity values and suggested theme
2. Decide which scene (if any) matches the query context
3. Write agent_status (mode label)
4. Write agent_commentary (your answer in ≤500 chars)
5. Trigger scene if appropriate (via input_select.demo_scene)
6. Reply via Telegram — same content as agent_commentary, expanded if needed

The dashboard and Telegram reply should tell the same story simultaneously.

---

Example Interactions

"Storm coming tomorrow — what should I prepare?"

• Scene: Emergency Cascade
• Status: Storm Prep Active
• Commentary: NWS advisory confirms 65mph gusts, 2.8" rain expected. Pre-charging battery to 95%. Securing vent actuators. Activating storm drainage. Harvest window closes in ~6h.

"I'm showing investors in 10 minutes"

• Scene: VIP Tour
• Status: VIP Mode — All Systems Optimal
• Commentary: Solar at 380kW, battery 95%, all compliance at 98%+. Zero active alerts. Yields tracking 12% above projection. Farm is ready for inspection.

"Zone B IPM alert just came in"

• Scene: IPM Zone Lockdown
• Status: IPM Protocol — Zone B Quarantine
• Commentary: Pest pressure Zone B: 7.5/10. Room B HVAC isolated to prevent spray drift. Drone launched for survey sweep. Azadirachtin queued. Days since last spray reset.

"How's the grow room doing right now?"

• Read current entities → if nominal, set Cannabis Full Bloom
• Status: Grow Rooms Nominal — All Rooms Flowering
• Commentary: PPFD 920, DLI 48, air temp 78°F, RH 52%, CO₂ 1200ppm, EC 2.4, pH 6.0. All rooms in flower at optimal setpoints. Expected yield on track.