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Phoenix Observability

Checked
davila7·vlatest·devops·MIT

Phoenix Observability swiftly identifies root causes of application issues by correlating logs, metrics, and traces – boosting DevOps efficiency & reducing downtime.

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 davila7/claude-code-templates --skill phoenix-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

davila7

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 davila7/claude-code-templates at 79182c51fb.

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

Commit
79182c51fb
Manifest
cli-tool/components/skills/ai-research/observability-phoenix/SKILL.md
Scanned
3 files, 1,495 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 allows you to generate Prometheus queries and Grafana dashboards for monitoring Phoenix applications. It can translate natural language requests into PromQL, helping visualize application performance metrics like request latency, error rates, and resource utilization. The generated dashboards provide a clear overview of the system's health and identify potential bottlenecks.

When to use it

  • You need to quickly generate Prometheus queries for specific Phoenix application metrics.
  • You want to create Grafana dashboards without manually writing PromQL or configuring panels.
  • Troubleshooting performance issues in a Phoenix application by visualizing key metrics.
  • Setting up monitoring for new Phoenix applications and services.

Key capabilities

  • Generates Prometheus queries (PromQL) from natural language descriptions.
  • Creates Grafana dashboard configurations based on user requests.
  • Supports common Phoenix application metrics (latency, error rates).
  • Provides visualizations of system health and performance.

Example prompts

  • "Generate a PromQL query to show the average request latency for all endpoints."
  • "Create a Grafana dashboard visualizing 5-minute error rate trends in my Phoenix app."
  • “Give me a Prometheus query to monitor database connection pool usage.”

Tips & gotchas

The skill's effectiveness depends on accurate descriptions of desired metrics and visualizations. Ensure you have Prometheus already configured to collect the necessary data from your Phoenix application.