An automated log parsing utility that identifies error patterns, calculates frequency distributions, and provides actionable summaries from system and application logs.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install app-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 app-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?
The Log Analyzer is a specialized tool within the Openclaw Skills ecosystem designed to help developers and system administrators make sense of voluminous log data. By automatically identifying error levels, grouping similar exceptions, and generating chronological timelines, it transforms raw text into a structured diagnostic report. This skill is essential for root cause analysis and proactive system monitoring, providing a high-level overview of system health without requiring manual grepping.
Built to be lightweight and fast, it leverages powerful Unix utilities to process everything from local syslog files to containerized Docker logs. By utilizing Openclaw Skills like this one, teams can significantly reduce their Mean Time to Recovery (MTTR) by pinpointing the exact moment and nature of a system failure.
Log Analyzer Use Cases
- Debugging application crashes by identifying the most frequent error messages.
- Monitoring system stability after a new deployment or configuration change.
- Auditing web server logs to identify spikes in 4xx or 5xx status codes.
- Parsing structured JSON logs to extract specific metadata and error context.
- Generating automated daily summaries of system warnings and anomalies.
How Log Analyzer Works
- Locate and access the log source, whether it is a physical file path, a piped input, or a system journal.
- Execute categorical filtering to determine the density of Errors, Warnings, and Info messages.
- Apply pattern normalization using sed and awk to deduplicate error messages, stripping out unique timestamps or IDs.
- Analyze the temporal distribution of issues to generate a timeline highlighting specific spikes in activity.
- Output a structured Markdown report that includes error counts, timelines, and prioritized recommendations.
Log Analyzer Setup
To get started with this component of Openclaw Skills, ensure your environment has the necessary CLI utilities installed. Most Linux and macOS systems include these by default, but jq is required for structured log parsing.
# Install jq for JSON log support
sudo apt-get install jq # Debian/Ubuntu
brew install jq # macOS
# Basic usage pattern
cat /var/log/syslog | log-analyzer
Log Analyzer Data Schema & Taxonomy
The skill produces a structured output that categorizes log data into the following taxonomy:
| Component | Description |
|---|---|
| Summary Stats | Counts for total lines, errors, and warnings within the specified time range. |
| Pattern Table | A deduplicated list of unique error messages paired with their occurrence count. |
| Error Timeline | A time-series breakdown (usually by hour) to visualize when issues occurred. |
| Action Items | A list of suggested next steps based on the highest frequency error patterns. |
Log Analyzer Advanced Features
- Large file handling using tail and time-based filtering to prevent memory overflow on files exceeding 100MB.
- Deep JSON log parsing using jq to isolate specific fields like trace IDs or service names.
- Real-time monitoring support by piping streaming inputs directly into the analysis engine.
- Integration with journalctl for native systemd service log inspection.
- Pattern-based deduplication that groups related stack traces into single, manageable entries.
SKILL.md
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