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Jenkins Pipeline

Checked
aj-geddes·vlatest·devops·MIT

Automates Jenkins pipeline execution, monitoring, and troubleshooting based on provided configuration and error analysis.

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 aj-geddes/useful-ai-prompts --skill jenkins-pipeline -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

aj-geddes

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 aj-geddes/useful-ai-prompts at 3f5182cfd7.

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

Commit
3f5182cfd7
Manifest
skills/jenkins-pipeline/SKILL.md
Scanned
5 files, 258 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 enables AI agents to generate, manage, and optimize Jenkins pipeline configurations for continuous integration and deployment workflows. It automates the creation of build scripts tailored to specific project requirements and infrastructure constraints.

When to use it

  • Automating the setup of CI/CD pipelines for new microservices or monolithic applications.
  • Refactoring existing Jenkinsfile syntax to adopt newer declarative pipeline standards.
  • Generating complex multi-stage builds that include testing, security scanning, and containerization steps.
  • Adapting pipeline logic to integrate with specific cloud providers like AWS or Azure.

Key capabilities

  • Generates valid Jenkins Declarative Pipeline syntax.
  • Configures build stages for compilation, unit testing, and integration testing.
  • Integrates artifact management tools such as Docker and Maven/Gradle.
  • Implements conditional logic for environment-specific deployments (dev, staging, prod).
  • Structures parallel execution steps to reduce overall build time.

Example prompts

  • "Create a Jenkins pipeline that builds a Node.js application, runs linting tests, and pushes the image to Docker Hub."
  • "Generate a multi-stage Jenkins pipeline including security scanning with SonarQube before deployment to Kubernetes."
  • "Write a Jenkinsfile that triggers a build only when specific branches are pushed and deploys to staging using SSH credentials."

Tips & gotchas

Ensure your AI agent has access to the project's dependency files (e.g., package.json, pom.xml) to generate accurate build commands. Avoid relying solely on generated pipelines for production environments without manual review of security configurations and credential handling.