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Github Workflow Automation

Checked
proffesor-for-testing·vlatest·backend·MIT

Helps with testing, GitHub, automation as part of testing, debugging, and quality assurance 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 proffesor-for-testing/agentic-qe --skill github-workflow-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

proffesor-for-testing

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 proffesor-for-testing/agentic-qe at 124d8c735e.

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

Commit
124d8c735e
Manifest
.claude/skills/github-workflow-automation/SKILL.md
Scanned
1 file, 930 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 autonomously discover, configure, and execute GitHub Actions workflows for continuous integration and deployment. It streamlines the testing lifecycle by allowing agents to trigger builds, run test suites, and analyze results directly within the repository ecosystem without manual intervention.

When to use it

  • Automating regression testing after every code commit to ensure immediate feedback on build health.
  • Orchestrating complex multi-stage pipelines that require conditional logic based on previous job outputs.
  • Validating infrastructure-as-code changes by triggering specific deployment workflows in staging environments.
  • Generating detailed test reports and failure logs automatically when CI jobs encounter errors.

Key capabilities

  • Triggers GitHub Actions workflows via API or webhooks based on agent-defined criteria.
  • Monitors workflow execution status in real-time to detect successes, failures, or pending states.
  • Parses raw workflow logs to extract specific error messages, stack traces, and test coverage metrics.
  • Integrates with existing repository secrets and environment variables for secure credential management.

Example prompts

  • "Run the 'main-ci' workflow on the latest commit and summarize any failing tests."
  • "Trigger the staging deployment pipeline if the unit test suite passes with 100% coverage."
  • "Analyze the logs from the last failed build and suggest potential configuration fixes."

Tips & gotchas

Ensure your GitHub repository has active Actions enabled and that necessary secrets are configured before deploying agents. Agents may require explicit permission scopes to trigger workflows or read logs, so verify role assignments in your organization settings.