Summary
This workflow automates refreshing a ranked markdown file of popular LLM applications by scraping GitHub topics and sorting by stars. It wraps get_app_list_by_github_star.py with clear guardrails: the generated list lives in section/x_llm_apps.md and gets linked from applications.md, never pasted inline. You can tune the star threshold, export to JSON or CSV for inspection, or narrow the topic set when the default pull is too broad. The main gotcha is forgetting to use a GitHub token, which will get you rate limited halfway through a full topic sweep. It deliberately outputs plain text star counts instead of live badges, so don't run badge scripts on the generated file or your next refresh will clobber them.
Install to Claude Code
npx -y skills add kimtth/awesome-azure-openai-llm --skill update-app-count --agent claude-codeInstalls into .claude/skills of the current project.
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Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
one prompt install →Give your AI agent a complete email layer—sending, inbound inboxes, and sandbox testing.
Get 4K emails/month free →Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →Notes, actions and memory. Without a meeting bot. First month 100% off.
Download for free →Your agent targets a perfect 10 Code Health score. Deterministic. Every commit.
Try For Free →First SeenJun 11, 2026
