Skip to content
TrustedSkillsbeta
Back to all skills

Infrastructure Monitoring

Checked
aj-geddes·vlatest·devops·MIT

Proactively detects infrastructure anomalies and performance bottlenecks using metrics and logs, alerting DevOps teams immediately.

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 aj-geddes/useful-ai-prompts --skill infrastructure-monitoring -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

aj-geddes

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 passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • 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 undeclared network calls: passed

    Makes no network calls.

    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.

  • 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 aj-geddes/useful-ai-prompts at 3f5182cfd7.

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

Commit
3f5182cfd7
Manifest
skills/infrastructure-monitoring/SKILL.md
Scanned
8 files, 493 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

The infrastructure-monitoring skill enables AI agents to actively query and analyze system health metrics, logs, and performance data across cloud environments. It allows agents to detect anomalies, correlate events with specific services, and generate actionable reports on resource utilization without manual intervention.

When to use it

  • Investigating sudden latency spikes or error rate increases in production deployments.
  • Automating daily compliance checks for server resource thresholds and security configurations.
  • Diagnosing root causes of service outages by cross-referencing application logs with infrastructure events.
  • Generating capacity planning reports based on historical traffic patterns and storage usage trends.

Key capabilities

  • Real-time retrieval of CPU, memory, and network utilization statistics from major cloud providers.
  • Parsing and summarizing complex log files to identify recurring error patterns or security incidents.
  • Correlating infrastructure events with application performance data to pinpoint bottlenecks.
  • Executing predefined diagnostic scripts to validate system integrity after updates or failures.

Example prompts

  • "Analyze the last hour of logs for our web server cluster and summarize any critical errors related to database connections."
  • "Check current CPU and memory usage across all EC2 instances in the production region and flag any exceeding 80% thresholds."
  • "Generate a report on storage growth trends over the past week and predict when we will hit capacity limits."

Tips & gotchas

Ensure your AI agent has appropriate read-only permissions configured for the specific cloud provider APIs or monitoring tools (e.g., Prometheus, Datadog) it needs to access. While this skill excels at data retrieval and analysis, it cannot directly remediate infrastructure issues without additional execution capabilities.