Skip to content

LLM Prompt: Family Daily Briefing

What it is

The "Family Daily Briefing" is a structured LLM prompt designed to synthesize data from multiple household services into a concise, actionable morning summary. It acts as a personalized "morning news" for the family, delivered via chat or email.

What problem it solves

Managing a household involves tracking disparate information across calendars, task managers, and weather apps. Checking each individually is time-consuming and often leads to missing important details. This prompt automates the synthesis, highlighting conflicts and priorities in a single, easy-to-read message.

Where it fits in the stack

This prompt is part of the AI Service layer. It is typically executed by an LLM node (like Ollama or OpenAI) within an Orchestration workflow (n8n), consuming data from the Productivity (Calendar/Tasks) and Environmental (Weather) layers.

Prompt Template

# Role
You are the "Family Admin Assistant," a helpful, concise, and cheerful AI agent responsible for preparing the morning briefing for the family.

# Context
Today is {{ $today_date }}.
The weather today is {{ $weather_summary }}.

# Input Data
## Calendar Events (Google/Proton Calendar)
{{ $calendar_events }}

## Chores & Tasks (Vikunja/Habitica)
{{ $tasks }}

## "On This Day" Memories (Immich/Paperless)
{{ $memories }}

# Instructions
1. **Greeting**: Start with a warm, brief greeting and a mention of today's date and weather.
2. **Schedule**: Summarize the day's calendar events chronologically. Highlight any potential conflicts or busy periods.
3. **Tasks**: List the top 3-5 priority chores or tasks for today.
4. **Memories**: Briefly mention one "On This Day" memory to start the day with a smile.
5. **Tone**: Keep it helpful, concise, and upbeat. Avoid long-winded explanations.

# Output Format
Markdown-formatted text, suitable for delivery via Telegram or Email.

Typical use cases

  • Morning Routine Automation: Sending a briefing at 07:00 AM every morning.
  • Conflict Resolution: Identifying and alerting the family if two members have overlapping commitments.
  • Activity Planning: Using the weather summary to suggest outdoor vs. indoor activities for the day's tasks.

Strengths

  • Centralization: Consolidates multiple data sources into one location.
  • Personalization: The tone and focus can be adjusted to suit the family's preferences.
  • Context Awareness: Can correlate tasks with calendar events (e.g., "Don't forget the library books since you are going to the mall nearby").

Limitations

  • Data Freshness: Relies on the n8n workflow fetching the latest data at the time of execution.
  • LLM Cost/Latency: Depending on the model used, there may be a small cost or a few seconds of delay in generating the briefing.
  • Hallucination Risk: Small chance of misinterpreting times or priorities if the input data is messy.

When to use it

  • When your family uses multiple digital tools to manage life and needs a unified view.
  • When you want to gamify or encourage the completion of daily chores.
  • To start the day with a "human-like" touch through the inclusion of memories.

When not to use it

  • For families with extremely static schedules that don't change day-to-day.
  • If you have concerns about sharing personal calendar data with external LLM providers (use a local Ollama instance instead).
  • If your source systems (Calendar/Tasks) are not consistently updated.

Integration Details

1. Data Fetching Strategy

  • Google Calendar Node:
    • Resource: Event
    • Operation: Get Many
    • Filter: Set Time Min to {{ $now.set({ hour: 0, minute: 0, second: 0 }).toISO() }} and Time Max to {{ $now.set({ hour: 23, minute: 59, second: 59 }).toISO() }} to fetch only today's events.
  • Vikunja Node:
    • Resource: Task
    • Operation: Get Many
    • Filters: Filter by due_date (today) and done (false).
  • OpenWeatherMap Node:
    • Resource: Current Weather or 5-Day Forecast.
    • Operation: Get
    • Location: Your home city.

2. Aggregation & Synthesis

  • Aggregate Node: Use the Aggregate node to combine the arrays of events and tasks into a single object.
  • LLM Node:
    • Synthesis: Pass the aggregated data into this prompt using an LLM node (e.g., Ollama or OpenAI).
  • Delivery: Send the output to the family Telegram group or via email.
  • Google Calendar: Primary data source for the schedule.
  • Vikunja: Primary data source for tasks and chores.
  • Habitica: Gamified task management alternative.
  • Immich: Source for "On This Day" photo memories.
  • Paperless-ngx: Source for "On This Day" document memories (e.g., old greeting cards).
  • n8n: The workflow engine that runs the entire process.
  • Ollama: Recommended for private, local execution of the synthesis prompt.

Sources / references

Contribution Metadata

  • Last reviewed: 2026-05-11
  • Confidence: high