pattern-scan

name	pattern-scan
description	Deep analysis of journal entries to surface patterns - recurring topics, energy trends, neglected areas, avoidance patterns. Use when wanting insight into what's actually getting attention over time.
allowed-tools	Read Bash(date:*) Bash(wc:*) Bash(jq:*)

Pattern Scan

Analyse journal.jsonl to surface patterns across time - what's recurring, what's neglected, energy trends, and avoidance patterns.

When to Use

• Wanting perspective on where attention has been going
• Feeling scattered - what's actually getting focus?
• Noticing something keeps coming up
• Weekly/monthly reflection
• Sensing avoidance but not sure of what

Data Source

Primary: state/journal.jsonl

Each entry:

{
  "t": "2025-12-28T09:10",
  "topics": ["planning", "strategy", "project-x"],
  "energy": "high|medium|low",
  "areas": ["projects", "learning"],
  "summary": "One-line session summary"
}

Secondary: sessions/ folder for deeper context (files named YYYY-MM-DD-HHMM-topic.md).

Execution Steps

Step 1: Load Data

cat state/journal.jsonl

Parse all entries. Note the date range covered.

Step 2: Topic Frequency

Count occurrences of each topic across all entries.

Present as:

## Topic Frequency (last N sessions)

| Topic | Count | % of Sessions |
|-------|-------|---------------|
| project-x | 5 | 100% |
| content | 3 | 60% |
| planning | 2 | 40% |
| ...

Flag:

• Dominant topics: Appearing in >50% of sessions
• One-offs: Appeared once, might indicate unfinished thread
• Emerging: New in recent sessions

Step 3: Area Coverage

Which life areas are getting attention?

## Area Coverage

| Area | Sessions | Last Touched |
|------|----------|--------------|
| projects | 5 | today |
| learning | 2 | 2025-12-27 |
| career | 0 | never |
| family | 0 | never |
| health | 0 | never |

Flag:

• Neglected: Areas with 0 sessions or not touched in 2+ weeks
• Dominant: Areas consuming >40% of sessions
• Balanced: Areas with steady, moderate attention

Step 4: Energy Patterns

Track energy levels over time:

## Energy Trend

| Date | Energy | Topics |
|------|--------|--------|
| 2025-12-28 | high | planning, strategy |
| 2025-12-27 | high | content, writing |
| 2025-12-26 | medium | admin, cleanup |
| ...

**Pattern**: Mostly high energy sessions - sustainable, or avoiding low-energy work?

Look for:

• Consistent high: Sustainable, or not capturing draining sessions?
• Consistent low: Burnout risk, or just honest tracking?
• Topic-energy correlation: Do certain topics correlate with energy?

Step 5: Avoidance Detection

Cross-reference what's present vs. what should be present:

Areas defined in user-context.md. Questions to surface:

• Which areas have zero sessions?
• Which topics appeared once then disappeared?
• What's mentioned in open_threads but never in sessions?
• Any patterns in what gets "pushed to next time"?

## Potential Avoidance Patterns

**Areas never touched:**
- career - professional development, skill building
- family - quality time, commitments
- health - exercise, fitness

**Open loops not becoming sessions:**
- "Follow up on X" - sitting since Dec 24

**Observation:**
High energy creative work (projects, content) is happening.
Admin, career planning, health tracking are not.

This isn't necessarily bad - but worth naming.

Step 6: Time Patterns

If enough data:

• Which days of week have sessions?
• Morning vs evening patterns?
• Session frequency trend (increasing, decreasing, steady?)

Step 7: Present Summary

## Pattern Scan: [Date Range]

**Sessions analysed:** N
**Date range:** [first] to [last]

### Where Attention Goes
[Top 3-5 topics and areas]

### What's Neglected
[Areas/topics with low or zero coverage]

### Energy Picture
[Overall trend and any correlations]

### Patterns Worth Naming
[Avoidance, recurring themes, observations]

### Questions to Sit With
- [Reflective question based on patterns]
- [Another if relevant]

Interpretation Notes

Patterns aren't judgments. A "neglected" area might be:

• Appropriately deprioritised right now
• Something being avoided
• Simply stable and not needing attention

The value is making the implicit explicit. The user decides what it means.

Integration

• Weekly review: Include pattern scan in the review
• Monthly: Deeper pattern analysis with more data
• On request: When something feels off and user wants perspective