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Monitoring Logging

Listed
miles990·vlatest·devops·MIT

Continuously monitors system logs and metrics, alerting on anomalies and providing detailed troubleshooting data.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add miles990/claude-software-skills --skill monitoring-logging -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

miles990

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No undeclared network calls: failed

    Contacts 1 host that is neither well-known infrastructure nor declared in the skill's frontmatter: events.pagerduty.com.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

    Hosts contacted

    events.pagerduty.comundeclared

    What it found

    • tools-integrations/monitoring-logging/SKILL.md:373contacts events.pagerduty.com
      await axios.post('https://events.pagerduty.com/v2/enqueue', {

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned miles990/claude-software-skills at 73632f218e.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
73632f218e
Manifest
tools-integrations/monitoring-logging/SKILL.md
Scanned
5 files, 968 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill enables AI agents to interact with and interpret monitoring and logging data. It can retrieve specific log entries based on keywords or time ranges, analyze metrics for anomalies, and summarize system health from various sources. The agent can also correlate events across different logs and systems to provide a holistic view of operational status.

When to use it

  • Troubleshooting incidents: Quickly identify the root cause of an application error by searching through relevant log files.
  • Performance analysis: Analyze server metrics (CPU, memory, network) over time to pinpoint performance bottlenecks.
  • Security investigations: Correlate security events from different logs to detect and respond to potential threats.
  • Proactive monitoring: Set up alerts based on specific log patterns or metric thresholds to identify issues before they impact users.

Key capabilities

  • Log retrieval by keyword
  • Time-based filtering of logs
  • Metric analysis (e.g., CPU usage, memory consumption)
  • Anomaly detection in metrics
  • Correlation of events across multiple logs

Example prompts

  • "Show me all error messages from the web server logs for the last hour."
  • "What was the average response time for our API endpoint yesterday?"
  • "Alert me if CPU usage exceeds 90% on any of our production servers."
  • “Correlate database connection errors with application crashes.”

Tips & gotchas

The effectiveness of this skill depends on having properly configured monitoring and logging systems. Ensure that logs are consistently formatted and tagged for easier analysis by the AI agent.