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Deployment Automation

Listed
aj-geddes·vlatest·devops·MIT

Helps with deployment, automation 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 aj-geddes/useful-ai-prompts --skill deployment-automation -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 failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No credential access: failed

    Touches credential material in 2 places.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

    What it found

    • skills/deployment-automation/references/github-actions-deployment-workflow.md:56Kubernetes credentials
      echo "${{ secrets.KUBE_CONFIG }}" | base64 -d > $HOME/.kube/config
    • skills/deployment-automation/references/github-actions-deployment-workflow.md:57Kubernetes credentials
      chmod 600 $HOME/.kube/config

  • 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 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/deployment-automation/SKILL.md
Scanned
7 files, 305 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

deployment-automation

What it does

This skill enables AI agents to execute automated deployment workflows for software applications. It streamlines the release process by managing build, test, and deploy sequences without manual intervention.

When to use it

  • Triggering continuous integration/continuous deployment (CI/CD) pipelines upon code commits.
  • Rolling out infrastructure changes or configuration updates across multiple environments.
  • Automating rollback procedures when a deployment fails validation checks.
  • Scheduling routine maintenance windows for automated system restarts or patching.

Key capabilities

  • Orchestrates end-to-end deployment lifecycles from source control to production.
  • Integrates with standard version control systems and container registries.
  • Validates build artifacts before initiating the release process.
  • Provides status reporting on deployment success or failure states.

Example prompts

  • "Deploy the latest stable version of the payment service to the staging environment."
  • "Initiate a full pipeline run for the new feature branch and notify me upon completion."
  • "Rollback the user authentication module to the previous commit due to critical errors."

Tips & gotchas

Ensure your AI agent has appropriate read/write permissions for your repository and cloud provider APIs before attempting deployments. Always verify that automated rollback rules are configured correctly to prevent extended downtime during failures.