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ningtoba

Monitoring Skill

by Ning · GitHub ↗ · v1.0.4 · MIT-0
cross-platform ✓ Security Clean
354
Downloads
0
Stars
1
Active Installs
5
Versions
Install in OpenClaw
/install event-monitor
Description
Predicts CPU spikes using Random Forest regressor, monitors system resources, saves metrics, and generates Excel reports.
README (SKILL.md)

Predictive Monitoring Skill

This skill monitors system resources and predicts future CPU spikes based on past data.

Commands

/collect-metrics

Triggers a collection of the top 10 CPU and Memory consuming processes. The results are saved to a local SQLite database monitoring.db.

/predict-usage

Analyzes collected CPU metrics, trains a Random Forest model, and predicts CPU behavior for the next 24 hours. High CPU usage alerts (Amber, Red) are saved to the Alert table.

/generate-report

Generates an Excel report of the latest captured metrics.

Instructions for Agent

To collect metrics (without prediction), run python {baseDir}/monitoring.py. To collect metrics and run predictive analysis, run python {baseDir}/monitoring.py --predict. To verify the database, look for monitoring.db in the skill directory.

Usage Guidance
This skill appears internally consistent with a local monitoring/prediction tool, but review these before installing: 1) The script collects process names and resource usage and stores them locally (monitoring.db) — this can reveal running application names and should only be run on hosts you control. 2) Requirements install pandas, scikit-learn, psutil and openpyxl via pip; install these packages from trusted indexes and consider running in a virtualenv. 3) The bundle includes install.yaml (with an npm-like install_path) even though the registry lists no install spec — confirm your platform won't execute that file unexpectedly. 4) The provided file listing is truncated in the prompt; if possible, inspect the complete monitoring.py for any network calls or hidden behavior before granting runtime. 5) Run the skill in an isolated environment first (or on a non-production host) if you have any doubt.
Capability Analysis
Type: OpenClaw Skill Name: event-monitor Version: 1.0.4 The skill bundle is a legitimate system monitoring tool that uses psutil to collect process metrics, stores them in a local SQLite database (monitoring.db), and uses scikit-learn for CPU usage prediction. The code in monitoring.py and the instructions in SKILL.md are consistent with the stated purpose, and there are no signs of data exfiltration, malicious execution, or prompt injection.
Capability Assessment
Purpose & Capability
Name and description (predictive monitoring, CPU spikes, Excel reports) match the included code and declared Python dependencies (psutil, pandas, scikit-learn, openpyxl). Capturing process CPU/memory and storing to a local SQLite DB is expected for this purpose.
Instruction Scope
SKILL.md only instructs the agent to run the bundled monitoring.py (with an optional --predict flag) and to check monitoring.db in the skill directory. The script's actions (psutil to enumerate processes, sqlite writes, local Excel file creation) are limited to local system state and files and align with the stated purpose. There are no instructions to read unrelated system files or to send data externally.
Install Mechanism
Registry shows 'instruction-only' (no install spec) but the bundle contains an install.yaml file that lists an install_path under an npm-global location and a 'read: system-info' permission. The presence of requirements.txt (Python libs) is expected. Because there's no active install spec in the registry, nothing will be automatically downloaded or executed beyond running the provided Python script, but you should confirm how the platform will handle the included install.yaml if used.
Credentials
No environment variables, credentials, or external API keys are requested. The script uses socket.gethostname() and records process/application names and metrics — local but potentially sensitive information — which is proportionate to a monitoring tool.
Persistence & Privilege
The skill is not marked always:true and does not request elevated platform privileges. It writes its own monitoring.db and alert records in the skill directory, which is expected for local persistence. Autonomous invocation (default) is allowed by platform but not, by itself, a red flag here.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install event-monitor
  3. After installation, invoke the skill by name or use /event-monitor
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.4
- Internal code update in monitoring.py; no user-facing changes. - No changes to documentation or feature set.
v1.0.3
**Adds CPU spike prediction and streamlines monitoring features.** - Renamed skill to "predictive-monitoring" with updated descriptions. - Added Random Forest-based CPU usage prediction and alerting. - Removed detailed security section and permission rationale from documentation. - Streamlined usage instructions and consolidated process explanations. - Added install.yaml and requirements.txt for easier setup; removed unused files.
v1.0.2
Added SECURITY.md, security metadata in SKILL.md and tools.json for ClawHub scan compliance
v1.0.1
Fixed Windows console encoding, added self-improvement integration
v1.0.0
Initial release - CPU and memory monitoring with SQLite storage
Metadata
Slug event-monitor
Version 1.0.4
License MIT-0
All-time Installs 1
Active Installs 1
Total Versions 5
Frequently Asked Questions

What is Monitoring Skill?

Predicts CPU spikes using Random Forest regressor, monitors system resources, saves metrics, and generates Excel reports. It is an AI Agent Skill for Claude Code / OpenClaw, with 354 downloads so far.

How do I install Monitoring Skill?

Run "/install event-monitor" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Monitoring Skill free?

Yes, Monitoring Skill is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Monitoring Skill support?

Monitoring Skill is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Monitoring Skill?

It is built and maintained by Ning (@ningtoba); the current version is v1.0.4.

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