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Prometheus

Checked
cosmix·vlatest·devops·MIT

Prometheus monitors your conversations, analyzing sentiment & key topics to provide insights and improve chatbot performance.

Repository

Install on your platform

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

Installs under a different name. Its SKILL.md names it loom-prometheus, not the name it is listed under, so the command below uses that name.
  1. 1

    Run this in your project

    terminal
    $ npx skills add cosmix/loom --skill loom-prometheus -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

cosmix

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 cosmix/loom at 851ce24346.

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

Commit
851ce24346
Manifest
skills/loom-prometheus/SKILL.md
Scanned
1 file, 531 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 integrates Prometheus, a powerful open-source monitoring and alerting system, into your AI agent's capabilities. It enables agents to collect and analyze time-series data related to conversations, providing insights into sentiment, key topics, and overall chatbot performance. Prometheus uses a flexible querying language called PromQL for analyzing this data and can be configured with Alertmanager to trigger notifications based on defined rules.

When to use it

  • To monitor the performance of your AI agent over time.
  • To identify trends in conversation sentiment or frequently discussed topics.
  • To set up alerts when key metrics, such as error rates, exceed predefined thresholds.
  • For analyzing latency and resource usage related to chatbot interactions.

Key capabilities

  • Time-series data collection: Gathers data points over time for analysis.
  • PromQL querying: Allows flexible querying of collected data using PromQL.
  • Alerting via Alertmanager: Configures alerts based on defined rules and sends notifications to receivers.
  • Support for various metric types: Handles counters (increasing values), gauges (values that fluctuate), histograms, and summaries.
  • Integration with exporters: Can pull metrics from third-party systems using exporters.

Example prompts

  • "Show me the average sentiment score of conversations over the last 24 hours."
  • "What are the top 5 most frequent topics discussed in our chatbot interactions?"
  • "Alert me if the error rate exceeds 5%."

Tips & gotchas

  • Requires a Prometheus server and Alertmanager to be set up separately. The skill integrates with these existing systems, it does not provide them.
  • Familiarity with PromQL is helpful for crafting effective queries.