$ show zouyee/zig-learning
This repository is a curated learning-resource aggregator (an 'awesome list') for the Zig programming language, not a software application. Classified as 'application' only because of its CI/CD tooling; it is not a data_research repo either — there are no datasets, notebooks, pipelines, or application source code. The core asset is README.md, a ~200-entry categorized collection of links to Zig books, videos, podcasts, blog posts, GitHub projects, and AI/ML frameworks, organized into ~25 categories with older entries progressively moved to a yearly archive/ directory. The only code-adjacent artifacts are package.json (markdownlint-cli, markdown-link-check), two GitHub Actions workflows, and three OpenCode agent-skill definitions.
The LLM identified 3 files worth highlighting for reuse:
Defines an OpenCode agent role for automated maintenance of a curated-link repository: discovery of markdown files, live URL validation, content-freshness checks (version-specific resources, stale repos), and quality assessment (duplicates, missing descriptions, ordering violations). Includes a structured maintenance-report template, tool-selection guidance, CI-integration notes, and an anti-pattern table forbidding content deletion without evidence. Reusable: the workflow is domain-agnostic — replace the 'Zig ecosystem context' section and it applies to any awesome-list repo. Demonstrates the emerging pattern of codifying repository operations as machine-readable agent skill definitions.
An agent playbook for triaging resource submissions to a curated list. Encodes the contribution rules (alphabetical order, one link per item, author attribution, 3-item minimum for new categories), a 4-phase evaluation workflow (accessibility verification, fluff detection, duplicate checks, category fit), an APPROVE/REQUEST_CHANGES/REJECT decision matrix, and PR-review output templates. The quality checklist and categorization decision rules transfer directly to any resource-aggregation project; only the :star:/:end:/:soon: tag semantics are repo-specific.
The most action-oriented of the three agent skills — it searches the web for new ecosystem content, inserts entries into README categories while maintaining alphabetical order, applies tag semantics, runs markdownlint and markdown-link-check as a verification gate, then commits and pushes to origin. Encodes a pragmatic mitigation for platform link-check failures (add YouTube/Medium/Reddit to ignorePatterns rather than deleting links), which is useful for anyone running automated link checks at scale. Minor reliability flaw: the suggested commit author email '[email protected]' contains a typo, indicating the skill was not end-to-end validated.