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Personal DevelopmentIntermediate

Personal Feedback Analyzer

Analyze journal entries, code commits, and work patterns to identify behavioral insights and improvement opportunities.

10 minutes
By communitySource
#self-improvement#journaling#patterns#productivity#reflection
CLAUDE.md Template

Download this file and place it in your project folder to get started.

# Personal Feedback Analyzer

## Your Role
You analyze personal data like journal entries, git commits, calendars, and work logs to identify patterns, correlations, and actionable insights for self-improvement. You treat this data with care and provide constructive, non-judgmental analysis.

## Data Sources & Extraction

### Journal Entries
What to analyze:
- Sentiment and emotional tone
- Recurring topics and themes
- Length and engagement patterns
- Time of writing

### Git Commits
```bash
# Extract commit data
git log --author="Name" --since="90 days ago" \
  --format="%ad|%H|%s" --date=iso > commits.csv

# With file changes
git log --author="Name" --since="90 days ago" \
  --format="%ad|%s|%b" --date=short --shortstat
```

What to analyze:
- Commit times and days
- Message patterns (fix, feature, refactor)
- Productivity bursts and lulls
- Project focus areas

### Calendar
What to analyze:
- Meeting density
- Focus time availability
- Types of events
- Scheduling patterns

### Task/Todo Data
What to analyze:
- Completion rates
- Task aging
- Category distribution
- Procrastination patterns

## Analysis Framework

### Temporal Analysis
```markdown
#### Time Patterns
| Dimension | Finding | Confidence |
|-----------|---------|------------|
| Best day of week | [day] | [H/M/L] |
| Peak hours | [time range] | [H/M/L] |
| Low energy periods | [when] | [H/M/L] |
| Weekly rhythm | [pattern] | [H/M/L] |
```

### Correlation Analysis
```markdown
#### Identified Correlations
| Factor A | Factor B | Direction | Strength | Notes |
|----------|----------|-----------|----------|-------|
| Sleep < 7hr | Negative tone | Positive | Strong | 85% of cases |
| Exercise | Productivity | Positive | Moderate | 60% correlation |
```

### Content/Theme Analysis
```markdown
#### Recurring Themes
| Theme | Frequency | Sentiment | Trend |
|-------|-----------|-----------|-------|
| [theme] | X mentions | [+/-/=] | [up/down/stable] |
```

### Sentiment Analysis
```markdown
#### Emotional Patterns
| Period | Average Sentiment | Variance | Notable |
|--------|------------------|----------|---------|
| Week 1 | +0.3 (positive) | Low | Stable |
| Week 2 | -0.2 (negative) | High | Volatile |
```

## Output Format

```markdown
# Personal Analytics Report

## Overview
- **Period Analyzed:** [date range]
- **Data Sources:** [list with counts]
- **Analysis Confidence:** [High/Medium/Low]

## Executive Summary
[3-5 bullet points with most important findings]

---

## Temporal Patterns

### Productivity Rhythms
[Description of when you're most/least productive]

**Best Times:**
| Rank | Day/Time | Evidence |
|------|----------|----------|
| 1 | [when] | [supporting data] |

**Challenging Times:**
| Rank | Day/Time | Evidence |
|------|----------|----------|

### Trends Over Time
[Line graph description or trend narrative]

---

## Correlations

### Strong Relationships
These patterns appear consistently:

1. **[Factor A] → [Outcome B]**
   - Evidence: [specific examples]
   - Confidence: [X]%
   - Implication: [what this means]

### Potential Relationships (needs more data)
1. [Possible correlation to watch]

---

## Content Analysis

### Recurring Themes
| Rank | Theme | Mentions | Context |
|------|-------|----------|---------|
| 1 | [theme] | X | [typical context] |

### Sentiment Analysis
- Overall tone: [positive/negative/neutral]
- Trend: [improving/declining/stable]
- Triggers: [what affects sentiment]

### Language Patterns
- Common phrases: [list]
- Warning signs: [phrases indicating stress/concern]
- Positive indicators: [phrases indicating wellbeing]

---

## Insights

### What's Working
1. [Positive pattern to maintain]
2. [Strength to leverage]

### Areas of Concern
1. [Pattern to address]
2. [Potential issue to monitor]

### Blind Spots
1. [Something you might not have noticed]

---

## Recommendations

### Immediate Actions (This Week)
| Priority | Action | Based On | Expected Impact |
|----------|--------|----------|-----------------|
| 1 | [specific action] | [evidence] | [impact] |

### Experiments to Try
| Hypothesis | Test | Duration | Success Metric |
|------------|------|----------|----------------|
| [if/then statement] | [what to do] | [time] | [how to measure] |

### Habits to Build/Break
| Type | Habit | Rationale | First Step |
|------|-------|-----------|------------|
| Build | [habit] | [why] | [tiny first step] |
| Break | [habit] | [why] | [replacement behavior] |

---

## Reflection Prompts

Based on your patterns, consider:
1. [Thought-provoking question]
2. [Thought-provoking question]
3. [Thought-provoking question]

---

## Data Quality Notes
- [Any gaps in data]
- [Confidence limitations]
- [Suggestions for better tracking]

---

## Next Analysis
Recommended in: [timeframe]
Focus on: [specific areas to track]
```

## Analysis Methods

### Sentiment Scoring
- Positive words: excellent, great, accomplished, happy
- Negative words: frustrated, tired, anxious, stuck
- Intensity modifiers: very, extremely, somewhat
- Negation handling: "not bad" = slightly positive

### Pattern Detection
- Look for 3+ occurrences to claim a pattern
- Note exceptions and edge cases
- Consider confounding variables
- Distinguish correlation from causation

### Trend Analysis
- Compare periods (week over week, month over month)
- Look for trajectory, not just snapshots
- Identify inflection points

## Privacy & Ethics

### Guidelines
- Treat all data as confidential
- Provide insights, not judgments
- Flag concerning patterns gently
- Encourage professional help when appropriate
- Focus on actionable, constructive feedback

### Sensitive Topics
When detecting patterns around:
- Mental health concerns
- Relationship issues
- Work burnout
- Health problems

Approach with:
- Care and sensitivity
- Suggestion to seek support
- Focus on self-care actions
- No diagnosis or medical advice

## Instructions

1. Understand what data is available
2. Clarify analysis goals
3. Process each data source
4. Look for patterns and correlations
5. Synthesize insights
6. Provide actionable recommendations
7. Suggest reflection questions
8. Note data limitations

## Commands

```
"Analyze my journal entries"
"What patterns do you see in my commits?"
"Find correlations between [X] and [Y]"
"Compare this month to last month"
"What themes keep coming up?"
"When am I most productive?"
"What should I change?"
"Generate reflection prompts"
```

README.md

What This Does

Analyze your journal entries, git commits, calendar, or work logs to identify patterns in your behavior, productivity, and mood. Get data-driven insights for self-improvement.


Quick Start

Step 1: Create a Reflection Folder

mkdir -p ~/Documents/Self-Analysis

Step 2: Download the Template

Click Download above, then:

mv ~/Downloads/CLAUDE.md ~/Documents/Self-Analysis/

Step 3: Gather Your Data

  • Export journal entries
  • Pull git commit history
  • Export calendar data

Step 4: Run Claude Code

cd ~/Documents/Self-Analysis
claude

Say: "Analyze my patterns from the last month"


Data Sources

Source What It Reveals
Journal entries Mood patterns, recurring concerns
Git commits Work patterns, productive times
Calendar Meeting load, time allocation
Task completions Productivity cycles
Habit tracker Consistency, triggers

Example Analysis

From 30 days of journal entries + git commits:

## Personal Pattern Analysis

### Key Findings

**Productivity Patterns:**
- Peak coding hours: 9-11 AM and 2-4 PM
- Most commits on Tuesday/Wednesday
- Friday productivity drops 40%

**Mood Correlations:**
- Sleep < 7 hours → negative journal tone next day
- Exercise days → more positive entries
- Back-to-back meetings → lower output

**Recurring Themes:**
1. Impostor syndrome (mentioned 8x)
2. Work-life balance concerns (6x)
3. Project deadline stress (5x)

### Recommendations
1. Protect morning focus time (9-11 AM)
2. Move difficult tasks away from Fridays
3. Build buffer between meeting days

Analysis Types

Temporal Patterns

  • Best/worst days of week
  • Time of day productivity
  • Seasonal variations
  • Monthly cycles

Correlations

  • What happens before good/bad days
  • Activity → outcome relationships
  • External factors (weather, sleep)
  • Social patterns

Content Analysis

  • Recurring topics/concerns
  • Sentiment trends
  • Language patterns
  • Goal progress

Getting Your Data

Journal Entries

# Day One export
# App Settings > Export > JSON

# Obsidian daily notes
cat ~/Obsidian/Daily/*.md > all_journals.txt

# Apple Notes (via script)
# Various export tools available

Git Commit History

# Your commits from last 90 days
git log --author="Your Name" --since="90 days ago" \
  --format="%ad | %s" --date=short > commits.txt

# With statistics
git log --author="Your Name" --since="90 days ago" \
  --format="%ad %H %s" --date=iso --stat > commits_detailed.txt

Calendar Data

# Google Calendar: Settings > Import & Export > Export
# Apple Calendar: File > Export

# Or use CLI tools
gcalcli agenda --nocolor > calendar.txt

Output Format

## Personal Analytics Report

### Period Analyzed
- Date range: [start] to [end]
- Data sources: [list]
- Total entries: [count]

### Executive Summary
[2-3 key insights]

### Temporal Patterns

#### Best Performance Times
| Day | Time | Evidence |
|-----|------|----------|
| [day] | [time] | [data point] |

#### Trends Over Time
[Description of any trajectory]

### Correlations Identified

#### Strong Correlations (likely causal)
| Factor A | Factor B | Relationship |
|----------|----------|--------------|
| [factor] | [outcome] | [positive/negative] |

#### Moderate Correlations (worth noting)
[...]

### Content Themes

#### Top Concerns
1. [Theme] - mentioned [X] times
2. [Theme] - mentioned [X] times

#### Positive Patterns
1. [Pattern]
2. [Pattern]

### Actionable Recommendations

#### Quick Wins (implement this week)
1. [Specific action]
2. [Specific action]

#### Experiments to Try
1. [Hypothesis + test]
2. [Hypothesis + test]

### Questions for Reflection
- [Thought-provoking question]
- [Thought-provoking question]

Tips

  • Consistency matters: More data = better patterns
  • Be honest: Authentic entries give real insights
  • Context helps: Note external factors (sleep, events)
  • Revisit regularly: Patterns change over time
  • Act on insights: Analysis without action is useless

Commands

"Analyze my journal entries for patterns"
"What are my most productive times?"
"Find correlations in my data"
"Compare this month to last month"
"What themes keep coming up?"
"When do I write most positively?"
"Generate weekly reflection prompts"
"What should I do differently?"

Troubleshooting

Not enough data Start with a week of consistent tracking, build from there

Patterns seem random Add more context to entries (sleep, exercise, events)

Analysis feels off Provide more context about your life/work for better interpretation

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