User Guide: Smart Metrics System

Version: 2.1.0 Feature: Automatic Behavioral Effectiveness Tracking Token Cost: 0 (background collection, never injected)

📋 Table of Contents

What Are Smart Metrics?
What We Track
Using the /metrics Command
Understanding Metrics Data
Privacy & Data Storage
Optimization Based on Metrics
Troubleshooting
FAQ

What Are Smart Metrics?

Smart metrics automatically track how effectively Mini-CoderBrain works for you.

Think of metrics like:

Fitness tracker for your development workflow
Performance dashboard for AI behavior
Analytics for productivity
A/B testing for profile effectiveness

Key Features

✅ Zero Overhead: Collected in background, no user action required ✅ Privacy-First: No sensitive content stored (only metadata) ✅ Actionable: Use data to optimize your workflow ✅ Profile Comparison: See which profiles work best ✅ Tool Insights: Understand your tool usage patterns

What We Track

1. Tool Usage Metrics

What: Which tools used, how often

Examples:

Read: 15 uses
Edit: 10 uses
Bash: 8 uses
Grep: 6 uses
Glob: 4 uses

Why Useful:

Identify most-used tools
Spot inefficiencies (too many Bash commands?)
Validate tool selection patterns

2. Session Metrics

What: Session characteristics and outcomes

Tracked:

Duration (minutes)
Operation count
Active profile
Tasks completed
Errors encountered

Example:

{
  "duration_minutes": 45,
  "tool_uses": 47,
  "profile": "default",
  "tasks_completed": 3,
  "errors": 1
}

Why Useful:

Measure productivity
Compare session effectiveness
Track progress over time

3. Profile Performance

What: How profiles perform for you

Tracked:

Token usage (actual vs estimated)
Response characteristics
Suggestion frequency
User satisfaction indicators

Example:

focus profile:
- Avg duration: 32 mins
- Avg operations: 38/session
- Token usage: 148 (vs 150 estimated)
- User corrections: 0.2/session

Why Useful:

Choose optimal profile for tasks
Validate profile effectiveness
Customize profiles based on data

4. Behavioral Quality (Future)

Planned for v2.2:

Context check compliance
Banned questions counter
Proactive suggestion quality

What We DON’T Track

❌ Code content (no file contents stored) ❌ File names (only tool usage counts) ❌ Commit messages (no git data) ❌ Personal information (no user data) ❌ Conversation content (only metadata)

Privacy-First Design: Only behavioral metadata collected

Using the /metrics Command

Basic Usage

View Current Session

/metrics

Output:

📊 METRICS - Current Session (45 mins, default profile)

Tool Usage:
  Read: 12 | Edit: 8 | Bash: 4
  Grep: 5 | Glob: 3 | Write: 2

Behavioral Quality:
  ✅ Metrics collection active
  📊 Full metrics available at session end

---
Metrics file: sessionstart-1697123456.json

When to Use: Check progress during long session

View Weekly Summary

/metrics --weekly

Output:

📊 METRICS - Last 7 Days (8 sessions)

Profile Usage:
  default: 5 sessions (62.5%)
  focus: 2 sessions (25%)
  research: 1 session (12.5%)

Top Tools:
  1. Read: 98 uses
  2. Edit: 67 uses
  3. Bash: 45 uses
  4. Grep: 34 uses
  5. Glob: 23 uses

Session Outcomes (Avg):
  Duration: 38 mins
  Tasks: 2.4/session
  Errors: 0.6/session

---
Data from 8 sessions

When to Use: Weekly workflow review

Compare Profiles

/metrics --profile

Output:

📊 METRICS - Profile Comparison (Last 30 days)

Profile: default (15 sessions)
  Avg Operations: 47/session
  Avg Duration: 45 mins

Profile: focus (8 sessions)
  Avg Operations: 38/session
  Avg Duration: 32 mins

Profile: research (4 sessions)
  Avg Operations: 52/session
  Avg Duration: 62 mins

---
Compare profiles to optimize workflow

When to Use: Deciding which profile to use

Full Report

/metrics --all

Output: Combined view of session + weekly + profile data

When to Use: Comprehensive analysis

Understanding Metrics Data

Tool Usage Insights

High Read Count

Read: 50 | Edit: 10

Interpretation: Good balance, reading before editing Action: None needed, healthy pattern

High Write Count

Write: 20 | Edit: 5

Interpretation: Creating many new files Potential Issue: Should some be edits instead? Action: Review if refactoring existing code vs writing new

High Bash Count

Bash: 30 | Read: 10

Interpretation: Many terminal commands Potential Issue: Using Bash instead of specialized tools? Action: Review tool-selection-rules pattern

Session Duration Patterns

Short Sessions (< 20 mins)

Possible Reasons:

Quick bug fixes
Focused tasks (good!)
Context issues (investigate)

Long Sessions (> 90 mins)

Possible Reasons:

Complex features (normal)
Flow state (great!)
Potential: Consider breaks

Profile Effectiveness

Metric: Operations Per Session

focus: 38 ops/session
default: 47 ops/session
research: 52 ops/session

Interpretation:

Focus: Terse output = fewer operations needed
Default: Balanced
Research: Verbose = more operations (but deeper work)

Not a competition: Different profiles for different goals!

Metric: Session Duration

focus: 32 mins avg
default: 45 mins avg
research: 62 mins avg

Interpretation:

Focus: Faster execution (goal achieved!)
Research: Longer exploration (by design)
Default: Balanced middle ground

Match to task: Choose profile based on time available

Privacy & Data Storage

What’s Stored

Location: .claude/metrics/sessions/*.json

Format: JSON files, one per session

Size: ~1-2 KB per session

Retention: 30 days (auto-archived)

Example Structure:

{
  "session_id": "sessionstart-1697123456",
  "timestamp": "2025-10-15T14:30:00Z",
  "profile": "default",
  "metrics": {
    "tool_usage": {
      "Read": 12,
      "Edit": 8
    },
    "session_outcome": {
      "duration_minutes": 45,
      "tool_uses": 47
    }
  }
}

No Sensitive Data: Only tool names and counts, no file paths or content

Data Management

View Stored Metrics

ls .claude/metrics/sessions/

Delete Metrics Manually

rm .claude/metrics/sessions/*.json

Auto-Cleanup

Runs at session end
Archives files > 30 days old
Moved to .claude/metrics/archive/YYYY-MM/
Never deletes (archives for history)

Privacy Guarantees

✅ Local Only: Never sent to external services ✅ No Code: File contents never stored ✅ No Paths: File names not tracked ✅ Metadata Only: Tool usage counts only ✅ User Control: Delete anytime

Optimization Based on Metrics

Scenario 1: Too Many Bash Commands

Metrics Show:

Bash: 40 | Read: 10 | Edit: 8

Analysis: Using Bash excessively

Optimization:

Review last session: What Bash commands?
Check tool-selection-rules pattern
Use specialized tools:
- cat file.txt → Use Read tool
- grep "pattern" → Use Grep tool
- find . -name → Use Glob tool

Expected Result: Bash count drops, Read/Grep/Glob increase

Scenario 2: Profile Mismatch

Metrics Show:

default profile:
- Duration: 65 mins (long!)
- Operations: 85 (high!)
- Task completed: 1 (low!)

Analysis: Default might be too verbose for this work

Optimization:

Try focus profile for this task type
Compare metrics after switch
Stick with faster profile if better

Expected Result: Shorter duration, fewer ops, more tasks

Scenario 3: Low Productivity

Metrics Show:

Weekly:
- 10 sessions
- Avg tasks: 0.8/session (low!)
- Avg errors: 2.3/session (high!)

Analysis: Something’s not working well

Optimization:

Check error patterns (Git issues? Build failures?)
Review context quality: /validate-context
Consider profile change
Check if project structure detection worked

Expected Result: Task completion improves, errors decrease

Troubleshooting

Problem: No Metrics Data

Symptom: /metrics shows “No session data available”

Causes:

First session (no data yet)
Metrics collection not started
jq not installed

Solutions:

# Check metrics folder exists
ls .claude/metrics/sessions/

# Check if jq installed
which jq

# Install jq if missing
# Ubuntu/Debian:
sudo apt-get install jq

# macOS:
brew install jq

# Restart Claude Code

Problem: Metrics File Not Created

Symptom: Session completed but no metrics file

Causes:

Session too short (< 1 min)
Metrics collector script not executable
Session ended abnormally

Solutions:

# Make metrics collector executable
chmod +x .claude/hooks/metrics-collector.sh
chmod +x .claude/hooks/metrics-report.sh

# Test manually
.claude/hooks/metrics-collector.sh init

# Check if file created
ls .claude/metrics/sessions/

Problem: Inaccurate Metrics

Symptom: Numbers don’t match expectations

Causes:

Metrics collected at session end (incomplete mid-session)
Multiple sessions overlapping
Manual file operations not tracked

Solutions:

Wait for session end for accurate totals
Avoid running multiple Claude instances
Metrics track AI operations, not manual edits

FAQ

Q: Do metrics slow down Claude?

A: No! Collection happens in background, zero performance impact.

Q: Can I disable metrics?

A: Yes! Remove or comment out metrics calls in hooks. But why? Zero overhead!

Q: Are metrics sent to external servers?

A: No! Everything stored locally in .claude/metrics/.

Q: Can I export metrics?

A: Yes! Files are JSON, easy to parse and analyze externally.

Q: Do metrics affect token usage?

A: No! Collection is background only, zero token cost.

Q: How long are metrics kept?

A: 30 days active, then archived. Never deleted, always accessible.

Q: Can I see metrics for other team members?

A: No, metrics are per-machine. Each developer has their own.

Q: What if I delete metrics folder?

A: Metrics restart fresh. No impact on Mini-CoderBrain functionality.

🎯 Key Takeaways

Automatic Collection: Zero user action required
Privacy-First: No sensitive data, only metadata
Tool Insights: Understand your workflow patterns
Profile Comparison: Data-driven profile selection
Optimization: Use metrics to improve productivity
Local Storage: Everything stays on your machine
Zero Cost: No token impact, no performance impact

Behavior Profiles Guide - Compare profile performance with metrics
Patterns Guide - Patterns define what metrics track
Migration Guide - Metrics are new in v2.1
Metrics System - Technical details

💡 Pro Tips

Tip 1: Weekly Review Habit

# Every Monday morning:
/metrics --weekly

# Review patterns, adjust workflow

Tip 2: Profile Experimentation

# Try new profile for a week
behavior_profile: "focus"

# After week, compare:
/metrics --profile

# Data-driven decision!

Tip 3: Export for Analysis

# Export metrics to CSV
jq -r '.metrics.tool_usage | to_entries | .[] | [.key, .value] | @csv' \
  .claude/metrics/sessions/*.json > tool_usage.csv

# Analyze in spreadsheet

Tip 4: Team Insights

Share aggregated (anonymized) metrics with team to identify best practices!

Data-driven development with zero overhead! 📊

Need help? Open an issue: GitHub Issues

User Guide: Smart Metrics System

📋 Table of Contents

What Are Smart Metrics?

Think of metrics like:

Key Features

What We Track

1. Tool Usage Metrics

2. Session Metrics

3. Profile Performance

4. Behavioral Quality (Future)

What We DON’T Track

Using the /metrics Command

Basic Usage

View Current Session

View Weekly Summary

Compare Profiles

Full Report

Understanding Metrics Data

Tool Usage Insights

High Read Count

High Write Count

High Bash Count

Session Duration Patterns

Short Sessions (< 20 mins)

Long Sessions (> 90 mins)

Profile Effectiveness

Metric: Operations Per Session

Metric: Session Duration

Privacy & Data Storage

What’s Stored

Data Management

View Stored Metrics

Delete Metrics Manually

Auto-Cleanup

Privacy Guarantees

Optimization Based on Metrics

Scenario 1: Too Many Bash Commands

Scenario 2: Profile Mismatch

Scenario 3: Low Productivity

Troubleshooting

Problem: No Metrics Data

Problem: Metrics File Not Created

Problem: Inaccurate Metrics

FAQ

Q: Do metrics slow down Claude?

Q: Can I disable metrics?

Q: Are metrics sent to external servers?

Q: Can I export metrics?

Q: Do metrics affect token usage?

Q: How long are metrics kept?

Q: Can I see metrics for other team members?

Q: What if I delete metrics folder?

🎯 Key Takeaways

📚 Related Documentation

💡 Pro Tips

Tip 1: Weekly Review Habit

Tip 2: Profile Experimentation

Tip 3: Export for Analysis

Tip 4: Team Insights