$ show veggiemonk/awesome-docker
This repository is a curated list of Docker/container resources (awesome-docker) paired with a production-grade Go CLI tool for maintaining the list. The CLI provides commands for parsing the README, linting entries (alphabetical order, description capitalization, period, duplicates), checking external and GitHub links concurrently, scoring repository health via the GitHub API, generating markdown/JSON health reports, building a static website from the README, an interactive TUI browser, and pruning stale/archived entries from both the README and the health cache. The architecture is modular with clear separation of concerns: parser, linter, checker, scorer, cache, builder, pruner, and TUI packages. The code is well-tested, uses modern Go idioms (Cobra CLI, Bubbletea TUI, GitHub GraphQL API), and is backed by comprehensive CI/CD workflows. The project is actively maintained with frequent commits, dependabot updates, and automated health reports. While the primary value is the curated list, the tooling itself is a high-quality, reusable framework for managing any curated awesome list.
The LLM identified 5 files worth highlighting for reuse:
Implements a concurrent HTTP link checker that uses HEAD requests with automatic fallback to GET on 4xx responses. Handles redirects, timeouts, and supports an exclusion list. The pattern is self-contained and can be extracted as a standalone library for any project needing to verify URL reachability across a list of links.
Provides a GitHub GraphQL client to query repository metadata (stars, forks, last push, archived status, license). Includes URL parsing to extract owner/name from GitHub URLs and handles authentication errors gracefully. The pattern is reusable for any tool that needs to batch-fetch GitHub repository information.
Encapsulates lint rules for markdown list entries: description capitalization, period, alphabetical sorting, and duplicate URL detection. The rule-based approach with severity levels is a clean, reusable pattern for implementing custom linters on structured markdown or any text-based format.
Computes health status (healthy, inactive, stale, archived, dead) for repositories based on last push date and archived/disabled flags. Generates both markdown and JSON reports with grouped entries and summary statistics. The scoring logic and report templates are isolated and can be adapted for any time-based health assessment system.
Implements automated removal of README entries that match certain health statuses, with dry-run support. Also prunes corresponding entries from the health cache to maintain consistency. The pattern of translating a list of targets (from scoring) into file edits is a clean, testable approach for maintaining any curated list with automated cleanup.