circleci

Enforce script organization, generated configs, and version pinning in CircleCI.

490|98|Updated Jan 15, 2018
One-click install
npx skills add https://github.com/astronomer/astronomer --skill circleci-astronomer
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: circleci
Source: https://github.com/astronomer/astronomer/tree/main/.agents/skills/circleci
Command: npx skills add https://github.com/astronomer/astronomer --skill circleci-astronomer

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill eliminates the frustration of managing inconsistent, unsecure, and hard-to-maintain CircleCI configurations for the Astronomer Private Cloud Helm chart repository, removing the risk of supply chain vulnerabilities, merge conflicts from edited generated files, and untestable inline CI scripts.

Core Features & Use Cases

  • Script Organization Enforcement: Requires all CI script logic to be stored in the bin/ directory instead of inline in .circleci/config.yml, making scripts lintable, testable locally, and reusable across jobs.
  • Generated Config Management: Mandates that .circleci/config.yml is produced by rendering the .circleci/config.yml.j2 Jinja2 template via bin/generate_circleci_config.py, preventing direct edits that cause configuration drift.
  • Version Pinning Standards: Requires all Docker image and tool versions to be pinned to exact values, declared in a single location at the top of the Jinja2 template for easy auditing and supply chain safety.
  • Use Case: When adding a new CI job to test Helm chart builds for Astronomer APC, this Skill ensures you add the test script to bin/, update the Jinja2 template, and pin all required tool versions correctly.

Quick Start

Use the circleci skill to update the Astronomer APC CircleCI configuration to add a new job for running Helm chart linting with all tool versions pinned to their latest stable releases.

Frequently Asked Questions about circleci

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I organize CircleCI scripts to make them lintable and testable for Helm chart builds?

To make CircleCI scripts lintable and testable, store all CI script logic in the bin/ directory instead of inline in .circleci/config.yml. This approach ensures scripts are reusable across jobs and can be tested locally before deployment.

How does generating CircleCI config from a Jinja2 template prevent configuration drift?

Generating CircleCI config from a Jinja2 template prevents configuration drift by mandating that .circleci/config.yml is produced by rendering .circleci/config.yml.j2 via bin/generate_circleci_config.py, blocking direct edits that cause merge conflicts and untestable inline scripts.

Why should I pin Docker image and tool versions in CircleCI configurations?

You should pin Docker image and tool versions in CircleCI configurations to ensure reproducible CI builds and mitigate supply chain vulnerabilities. Declaring exact versions in a single location enables easy auditing and consistent workflow conventions.

What is the best way to add a new CI job for Helm chart linting without causing merge conflicts?

The best way to add a new CI job for Helm chart linting is to add the test script to the bin/ directory, update the Jinja2 template, and pin all required tool versions correctly. This ensures reproducible builds and prevents configuration drift.

Does this CircleCI configuration approach work for Astronomer Private Cloud Helm chart repositories?

Yes, this CircleCI configuration approach is specifically designed for the Astronomer Private Cloud Helm chart repository. It enforces script organization, config generation pipeline management, and version pinning standards tailored to that environment.

What are the limitations of using inline CI scripts in CircleCI config files?

Inline CI scripts in CircleCI config files are untestable, hard to maintain, and cannot be linted locally. Storing script logic in the bin/ directory resolves these limitations by making scripts reusable and testable across multiple jobs.