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Monitoring Observability

Checked
yonatangross·vlatest·devops·MIT

Proactively identifies and alerts on system anomalies using advanced monitoring and observability techniques.

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 yonatangross/orchestkit --skill monitoring-observability -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

yonatangross

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 yonatangross/orchestkit at 7784b90c05.

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

Commit
7784b90c05
Manifest
src/skills/monitoring-observability/SKILL.md
Scanned
54 files, 7,756 lines
Copies in repo
2 — all of them scanned
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.
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About this skill

What it does

This skill enables AI agents to automate the setup and management of monitoring and observability stacks for infrastructure and applications. It streamlines the deployment of tools like Prometheus, Grafana, and ELK to ensure system health is continuously tracked without manual configuration overhead.

When to use it

  • Deploying a new microservices architecture that requires immediate visibility into latency and error rates.
  • Automating the transition from ad-hoc logging to a centralized observability platform during scaling events.
  • Setting up alerting rules for critical infrastructure metrics such as CPU saturation or disk I/O bottlenecks.
  • Integrating existing cloud-native applications with standardized dashboards for team-wide monitoring.

Key capabilities

  • Automated installation and configuration of popular observability tools including Prometheus, Grafana, and ELK.
  • Customizable dashboard generation based on specific infrastructure metrics and application logs.
  • Pre-configured alerting mechanisms to notify teams of anomalies in real-time.
  • Support for both containerized environments and traditional server setups.

Example prompts

  • "Set up a full Prometheus and Grafana stack for my Kubernetes cluster with default dashboards."
  • "Configure an ELK stack to aggregate logs from my Node.js applications and create a search interface."
  • "Deploy monitoring tools that track memory usage and network latency across my distributed system."

Tips & gotchas

Ensure your target environment has sufficient resources, as observability stacks can be resource-intensive. Verify network connectivity between agents and the monitoring endpoints to prevent data collection failures.