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Observability Monitoring Slo Implement

Checked
rmyndharis·vlatest·devops·MIT

Automates SLO implementation, observability setup, and monitoring dashboards for improved DevOps performance and reliability.

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 rmyndharis/antigravity-skills --skill observability-monitoring-slo-implement -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

rmyndharis

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 rmyndharis/antigravity-skills at 3eff4af253.

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

Commit
3eff4af253
Manifest
skills/observability-monitoring-slo-implement/SKILL.md
Scanned
2 files, 1,100 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.
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About this skill

What it does

This skill enables AI agents to implement observability, monitoring, and Service Level Objectives (SLOs). It facilitates defining SLOs based on key performance indicators (KPIs), configuring automated dashboards for visualization, and setting up alerts triggered by SLO breaches. The agent can also assist in identifying root causes of issues impacting SLO adherence through analysis of collected metrics.

When to use it

  • Defining SLOs: You need help establishing clear SLO targets for your services based on business requirements.
  • Dashboard Creation: You want an automated way to create dashboards visualizing key service performance indicators.
  • Alerting Setup: You require assistance in configuring alerts that notify you when SLOs are at risk of being violated.
  • Troubleshooting Performance Issues: When services exhibit degraded performance, the agent can help pinpoint underlying causes by analyzing monitoring data.

Key capabilities

  • Define Service Level Objectives (SLOs)
  • Configure automated dashboards for visualization
  • Set up alerts triggered by SLO breaches
  • Analyze metrics to identify root causes of issues

Example prompts

  • "Create an SLO for our API endpoint, targeting 99.9% uptime."
  • "Generate a Grafana dashboard showing latency and error rates for the payment service."
  • "Set up alerts if the average response time exceeds 500ms for the user authentication microservice."

Tips & gotchas

The agent's effectiveness depends on access to existing monitoring data sources (e.g., Prometheus, Datadog). Ensure appropriate permissions and connectivity are configured beforehand to allow the agent to retrieve and analyze relevant metrics.