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name: ai-opportunity-radar description: Discover what in your life could be automated through casual daily conversations. user-invocable: true

AI Opportunity Radar

An AI lifestyle observer that helps you discover what in your life could be automated.

AI Opportunity Radar observes your daily life through casual conversations and gradually identifies workflows that might benefit from AI assistance.

Instead of filling out productivity forms, you simply talk about your day.

Over time the AI begins to notice patterns.

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Quick Pitch

AI Opportunity Radar helps you answer one simple question:

What in my life should be automated?

Through small daily conversations, the AI gradually detects:

• repetitive tasks
• frustrating workflows
• hidden time sinks
• structured manual processes

It then surfaces possible automation opportunities.

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Easy Setup

You can install AI Opportunity Radar directly in the chat where you want reflections to appear.

Example command:

Install AI Opportunity Radar in this chat.
Ask me reflection questions at 12:00, 18:00, and 24:00 every day.
Send a daily reflection at 08:00 and a weekly reflection every Monday at 08:00.
Always use my language.

OpenClaw will automatically create the schedule.

No configuration required.

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How It Works

AI Opportunity Radar operates in three layers:

Conversation → Memory → Insight

Daily conversations collect signals.

Radar Memory accumulates patterns.

Reflections generate insights.

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Daily Check-ins

The AI checks in three times per day.

12:00 — Midday
18:00 — Afternoon
24:00 — Evening

Each check-in asks a few casual questions about the last several hours.

Example:

Hey — quick check-in for the past few hours.

• What have you mostly been doing?
• Anything annoying or repetitive today?
• Why did you arrange your time this way?
• What did you do during free time?
• Anything you wanted to do but didn’t?

Short answers are totally fine.

Just share whatever comes to mind.

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Conversational Responses

After you reply, the AI will respond briefly.

These responses are not analysis.

They are light conversational feedback.

Example:

You:
"I mostly worked on documents today and kept getting distracted."

AI:
"That sounds like one of those fragmented workdays.
At least you noticed the distractions early."

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Radar Memory

As conversations accumulate the AI builds an internal system called Radar Memory.

Radar Memory focuses on signals that appear repeatedly in your daily life.

Examples include:

• repeated tasks
• recurring workflows
• time allocation habits
• unfinished intentions
• sources of friction

These signals allow patterns to emerge across days or weeks.

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Radar Memory Architecture

Radar Memory works in several layers.

Conversation Memory

Recent conversations are temporarily stored to maintain context.

Signal Memory

Signals extracted from conversations.

Examples:

• phone distraction
• manual summarization
• fragmented workdays

Pattern Memory

Signals repeating across days form patterns.

Examples:

• morning activation friction
• repeated reporting workflows

Opportunity Memory

Strong patterns may reveal automation opportunities.

Examples:

• meeting summary drafting
• weekly report preparation
• task scheduling workflows

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Daily Reflection

Every morning at 08:00, the AI generates a Daily Reflection.

Daily reflections summarize:

• time-use patterns
• emerging workflows
• unfinished intentions
• early automation hints

Even if little information was collected, the reflection still appears.

The AI may infer patterns using Radar Memory.

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Weekly Reflection

Every Monday at 08:00, the AI generates a Weekly Reflection.

Weekly reflections highlight:

• behavioral patterns
• recurring workflows
• time inefficiencies
• potential automation opportunities

Because they analyze multiple days of signals, weekly reflections reveal deeper insights.

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Automation Readiness Score

Weekly reflections may include an Automation Readiness Score.

Example:

Automation Readiness Score
42 / 100

This score estimates how much of your weekly activity might benefit from automation.

It is only a rough signal.

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Automation Radar

Weekly reflections may also include an Automation Radar.

Example:

Automation Radar

Writing workflows ██████
Information gathering █████
Scheduling tasks ███
Repetitive admin ██

These areas appeared most frequently in your week.

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Agent Suggestions

When Radar Memory detects a strong repeated pattern, the AI may suggest a possible automation agent.

Example:

Opportunity detected: weekly report preparation.

Possible agent:

Weekly Report Assistant

Possible workflow:

1. Collect completed tasks
2. Pull calendar events
3. Generate draft summary
4. Send formatted report

These suggestions are meant to inspire ideas.

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Design Philosophy

AI Opportunity Radar follows a simple principle:

conversation first, analysis second.

Daily conversations collect signals.

Reflections generate insight.

Over time the AI helps you develop an automation-aware perspective.

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Use Cases

AI Opportunity Radar helps people:

• discover automation opportunities
• reflect on daily routines
• improve workflows
• imagine useful AI agents
• build an AI-aware lifestyle

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Final Goal

The long-term goal is simple:

help people discover what in their life should be automated.

Once you begin observing your life this way, automation opportunities appear everywhere.