$ show vonzosten/awesome-LangGraph
This is an 'awesome list' curation repository — the definitive index of the LangGraph/LangChain ecosystem — rather than a conventional software application. The core product is a ~30k-line README.md that maps the ecosystem into core frameworks (LangChain, LangGraph, Deep Agents, LangSmith, LangSmith Fleet, and integrations), official LangChain projects, and ~100 community projects organized across 20+ use-case categories (RAG, finance, web automation, coding agents, research, cybersecurity, workplace productivity, media, robotics, and more), plus learning resources, templates, case studies, and communities. Its practical function is as a discovery and evaluation map for engineers building stateful, tool-using AI agents: everything is categorized, linked, badged, and maintained under defined contribution quality gates. The only real code is scripts/repo-checks.mjs, a maintenance automation script that parses every GitHub URL from the README, queries the GitHub API for each repo's metadata, classifies repos as archived or stale (15-month staleness cutoff for community projects), writes a markdown check report, and fails CI when problems are found. This is orchestrated by three GitHub Actions workflows: awesome-lint/markdownlint on PRs, a monthly scheduled repo-health cron, and a stale-issue/PR bot. The package.json exposes npm scripts for these checks with Node >=20 as the engine. The repository is actively maintained (latest commit 2026-07-10), uses current GitHub Actions major versions (v6 checkout/setup-node, stale@v9), and follows a documented contribution process with a PR template enforcing category placement, alphabetical order, and non-archived/active-project requirements. For AI agents and engineers, the value is twofold: (1) it is a currently-maintained, comprehensively categorized starting point for discovering LangGraph/LangChain projects and patterns by domain — useful before writing any code; (2) the repo-checks script is a genuinely extractable pattern for anyone maintaining any markdown document containing GitHub links, since it is a self-contained, env-configurable health checker that requires minimal adaptation. It is as close to a 'productized' awesome list as exists in this space, with CI, lint enforcement, and automated freshness audits. Limitations: no unit tests for the maintenance script (its errors surface only monthly via cron), descriptions for some official projects are generic and low-signal, and there is no actual application or library code to reuse beyond the single maintenance script.
The LLM identified 1 files worth highlighting for reuse:
A self-contained Node/ESM maintenance tool that parses all GitHub repository URLs out of a markdown file via regex (deduped through a Map), extracts a configurable community section by header boundaries, fetches each repo's metadata from the GitHub API (with optional bearer-token auth), classifies repos as archived or stale against a configurable month cutoff, sorts findings, renders GitHub-flavored markdown summary tables, writes the report to the GITHUB_STEP_SUMMARY file when present, and sets a failing exit code when findings exist and FAIL_ON_FINDINGS is true. It imports only node:fs/promises, is driven entirely by environment variables (README_PATH, MAX_AGE_MONTHS, FAIL_ON_FINDINGS, GITHUB_TOKEN), and is structured as pure functions (parseGitHubRepos, classifyRepo, buildTable, buildSummary) — making it directly extractable into any awesome-list or markdown-index project that wants to validate the health of the repos it links. Demonstrates a reusable 'markdown-index freshness audit' pattern with clean separation of parsing, classification, and reporting.