name: log-analyze description: Parse and analyze system and application logs. Use when the user says "find errors in logs", "analyze logs", "check journalctl", "what's in the logs", "debug from logs", or asks to investigate log files. allowed-tools: Bash, Read, Grep

Log Analysis

Parse and analyze logs to identify errors, patterns, and issues.

Instructions

1. Identify log source (journalctl, file, application)
2. Establish time range of interest
3. Filter for relevant entries (errors, specific service)
4. Identify patterns and root causes
5. Summarize findings with evidence

Common log sources

# Systemd journal
journalctl -u <service> --since "1 hour ago"
journalctl -p err --since today
journalctl -b  # current boot

# System logs
/var/log/syslog
/var/log/messages
/var/log/auth.log

# Application logs
/var/log/nginx/error.log
/var/log/apache2/error.log
/var/log/postgresql/

Journalctl patterns

# Errors only
journalctl -p err -b

# Specific service with context
journalctl -u nginx --since "2024-01-01" --until "2024-01-02"

# Follow live
journalctl -f -u myapp

# Kernel messages
journalctl -k

# JSON output for parsing
journalctl -o json -u myapp | jq .

# Disk usage
journalctl --disk-usage

Analysis patterns

# Count errors by type
grep -oP 'ERROR: \K[^:]+' app.log | sort | uniq -c | sort -rn

# Find IPs with most errors
grep "error" access.log | grep -oP '\d+\.\d+\.\d+\.\d+' | sort | uniq -c | sort -rn

# Time distribution of errors
grep "ERROR" app.log | grep -oP '^\d{4}-\d{2}-\d{2} \d{2}' | uniq -c

# Errors around a specific time
grep -A5 -B5 "15:30:" error.log

Common error patterns

Output format

## Summary
[Brief description of what was found]

## Errors Found
- [timestamp] [error message] (occurred N times)

## Root Cause Analysis
[Explanation of likely cause]

## Recommendations
1. [Action to fix]
2. [Preventive measure]

Rules

• MUST establish time range before analyzing
• MUST quantify error frequency (not just "found errors")
• MUST provide specific log excerpts as evidence
• Never expose sensitive data from logs (passwords, tokens)
• Always check for time correlation between errors