A self-contained Linux shell utility designed to parse syslogs and custom log files for error detection, anomaly spikes, and IP frequency analysis.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install laolaoqi-log-analyzer
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install laolaoqi-log-analyzer using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Log Analyzer?
Log Analyzer is a robust diagnostic tool integrated into the Openclaw Skills ecosystem, designed to provide developers and sysadmins with immediate insights into system health. By leveraging standard Linux utilities like awk, grep, and sed, it processes raw log data to identify critical patterns without the need for heavy external dependencies.
This skill excels at turning massive, unstructured log files into actionable intelligence. Whether you are troubleshooting a sudden service outage or monitoring for brute-force attempts, it provides the necessary granularity to isolate issues by time, frequency, or source IP. It is an essential addition for those looking to expand their Openclaw Skills library for automated system maintenance.
Log Analyzer Use Cases
- Troubleshooting application crashes by identifying the most frequent error messages.
- Detecting potential DDoS or brute-force attacks through IP frequency analysis.
- Correlating system errors with specific deployment windows or cron job schedules.
- Proactive monitoring of system warnings to prevent critical infrastructure failure.
- Analyzing real-time log streams by piping journalctl or tail output directly into the script.
How Log Analyzer Works
- The script ingestion layer receives log data via a specified file path or a piped stdin stream.
- The Pattern Matching engine scans the text for keywords like error, fail, or critical using customizable regex.
- The Frequency Aggregator groups these findings to determine 'Top N' errors and high-traffic IP addresses.
- Time-based Bucketing organizes entries into hourly or daily segments to visualize error distribution over time.
- The Spike Detection module calculates the average error rate and flags any time bucket exceeding 2x that average as an anomaly.
- A consolidated report is generated, providing a structured overview of errors, sources, and temporal spikes.
Log Analyzer Setup
To integrate this into your environment, ensure you have the script locally and provide execution permissions:
# Navigate to your scripts directory
chmod +x scripts/log-analyzer.sh
# Run a full analysis on a local syslog file
bash scripts/log-analyzer.sh -f /var/log/syslog --all
For real-time analysis with Openclaw Skills, you can pipe live service logs:
journalctl -u nginx --since "1 hour ago" | bash scripts/log-analyzer.sh --errors --ips
Log Analyzer Data Schema & Taxonomy
The Log Analyzer processes data based on standard Linux log formats (RFC 3164/5424). It organizes output into the following logical sections:
| Data Component | Description | Extraction Method |
|---|---|---|
| Error Frequency | Count of unique error strings | Regex pattern matching & sort/uniq |
| Temporal Data | Errors grouped by Hour/Day | Date string parsing |
| Source IPs | List of IPv4 addresses | IPv4 Regex extraction |
| Anomaly Flags | Deviations > 2x average | Statistical mean comparison |
Log Analyzer Advanced Features
- Custom Pattern Support: Use the
-pflag to define project-specific error strings or exceptions. - Stdin Interoperability: Seamlessly integrates with Linux pipes using
-f -for automated CI/CD log checking. - Scalability Tuning: Use the
-tflag to restrict analysis to specific time windows, optimizing performance for files larger than 100MB. - Multi-Agent Compatibility: Can be triggered by other AI agents to provide diagnostic context during incident response.
SKILL.md
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