log-analysis
Analyze application logs to identify errors, performance issues, and security anomalies. Use when debugging issues, monitoring system health, or investigating incidents. Handles various log formats including Apache, Nginx, application logs, and JSON logs.
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install supercent-io-skills-template-log-analysis
Repository
Skill path: .agent-skills/log-analysis
Analyze application logs to identify errors, performance issues, and security anomalies. Use when debugging issues, monitoring system health, or investigating incidents. Handles various log formats including Apache, Nginx, application logs, and JSON logs.
Open repositoryBest for
Primary workflow: Run DevOps.
Technical facets: Full Stack, Security.
Target audience: everyone.
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: supercent-io.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install log-analysis into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/supercent-io/skills-template before adding log-analysis to shared team environments
- Use log-analysis for development workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.
Original source / Raw SKILL.md
---
name: log-analysis
description: Analyze application logs to identify errors, performance issues, and security anomalies. Use when debugging issues, monitoring system health, or investigating incidents. Handles various log formats including Apache, Nginx, application logs, and JSON logs.
allowed-tools: Read Grep Glob
metadata:
tags: logs, analysis, debugging, monitoring, grep, patterns
platforms: Claude, ChatGPT, Gemini
---
# Log Analysis
## When to use this skill
- **Error debugging**: analyze the root cause of application errors
- **Performance analysis**: analyze response times and throughput
- **Security audit**: detect anomalous access patterns
- **Incident response**: investigate the root cause during an outage
## Instructions
### Step 1: Locate Log Files
```bash
# Common log locations
/var/log/ # System logs
/var/log/nginx/ # Nginx logs
/var/log/apache2/ # Apache logs
./logs/ # Application logs
```
### Step 2: Search for Error Patterns
**Common error search**:
```bash
# Search ERROR-level logs
grep -i "error\|exception\|fail" application.log
# Recent errors (last 100 lines)
tail -100 application.log | grep -i error
# Errors with timestamps
grep -E "^\[.*ERROR" application.log
```
**HTTP error codes**:
```bash
# 5xx server errors
grep -E "HTTP/[0-9.]+ 5[0-9]{2}" access.log
# 4xx client errors
grep -E "HTTP/[0-9.]+ 4[0-9]{2}" access.log
# Specific error code
grep "HTTP/1.1\" 500" access.log
```
### Step 3: Pattern Analysis
**Time-based analysis**:
```bash
# Error count by time window
grep -i error application.log | cut -d' ' -f1,2 | sort | uniq -c | sort -rn
# Logs for a specific time window
grep "2025-01-05 14:" application.log
```
**IP-based analysis**:
```bash
# Request count by IP
awk '{print $1}' access.log | sort | uniq -c | sort -rn | head -20
# Activity for a specific IP
grep "192.168.1.100" access.log
```
### Step 4: Performance Analysis
**Response time analysis**:
```bash
# Extract response times from Nginx logs
awk '{print $NF}' access.log | sort -n | tail -20
# Slow requests (>= 1 second)
awk '$NF > 1.0 {print $0}' access.log
```
**Traffic volume analysis**:
```bash
# Requests per minute
awk '{print $4}' access.log | cut -d: -f1,2,3 | uniq -c
# Requests per endpoint
awk '{print $7}' access.log | sort | uniq -c | sort -rn | head -20
```
### Step 5: Security Analysis
**Suspicious patterns**:
```bash
# SQL injection attempts
grep -iE "(union|select|insert|update|delete|drop).*--" access.log
# XSS attempts
grep -iE "<script|javascript:|onerror=" access.log
# Directory traversal
grep -E "\.\./" access.log
# Brute force attack
grep -E "POST.*/login" access.log | awk '{print $1}' | sort | uniq -c | sort -rn
```
## Output format
### Analysis report structure
```markdown
# Log analysis report
## Summary
- Analysis window: YYYY-MM-DD HH:MM ~ YYYY-MM-DD HH:MM
- Total log lines: X,XXX
- Error count: XXX
- Warning count: XXX
## Error analysis
| Error type | Occurrences | Last seen |
|----------|-----------|----------|
| Error A | 150 | 2025-01-05 14:30 |
| Error B | 45 | 2025-01-05 14:25 |
## Recommended actions
1. [Action 1]
2. [Action 2]
```
## Best practices
1. **Set time range**: clearly define the time window to analyze
2. **Save patterns**: script common grep patterns
3. **Check context**: review logs around the error too (`-A`, `-B` options)
4. **Log rotation**: search compressed logs with zgrep as well
## Constraints
### Required Rules (MUST)
1. Perform read-only operations only
2. Mask sensitive information (passwords, tokens)
### Prohibited (MUST NOT)
1. Do not modify log files
2. Do not expose sensitive information externally
## References
- [grep manual](https://www.gnu.org/software/grep/manual/)
- [awk guide](https://www.gnu.org/software/gawk/manual/)
- [Log analysis best practices](https://www.loggly.com/ultimate-guide/)
## Examples
### Example 1: Basic usage
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### Example 2: Advanced usage
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