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Pipeline Monitor

Checked
manastalukdar·vlatest·devops·MIT

Helps with pipeline automation, monitoring as part of automating DevOps pipelines and CI/CD workflows workflows.

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 manastalukdar/ai-devstudio --skill pipeline-monitor -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

manastalukdar

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 manastalukdar/claude-devstudio at e457c1d3b5.

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

Commit
e457c1d3b5
Manifest
skills/pipeline-monitor/SKILL.md
Scanned
1 file, 32 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

The pipeline-monitor skill provides real-time monitoring of CI/CD pipelines. It can track the status of jobs, identify failures, and provide insights into pipeline performance. This allows for proactive issue detection and faster resolution times in your development workflow.

When to use it

  • Troubleshooting build failures: Quickly pinpoint the stage or job causing a pipeline failure.
  • Monitoring deployment frequency: Track how often deployments are happening and identify potential bottlenecks.
  • Performance optimization: Analyze pipeline execution times to identify areas for improvement.
  • Proactive alerting: Set up notifications for specific events, like failed jobs or long-running stages.

Key capabilities

  • Real-time pipeline status tracking
  • Job failure identification
  • Pipeline performance metrics
  • Alerting and notification support

Example prompts

  • "Show me the current status of the 'production' pipeline."
  • "What was the last error in the 'staging' pipeline?"
  • "How long did it take to run the 'integration-tests' job in the 'main' branch?"

Tips & gotchas

The skill requires access to your CI/CD platform (e.g., Jenkins, GitLab CI). Ensure appropriate credentials and permissions are configured for the AI agent to connect and retrieve pipeline data.