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DeveloperJul 25, 2025

GitHub Stargazers Data Extraction

Wendong FanWendong Fan
GitHub Stargazers Data Extraction
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Turn Your GitHub Stars Into a Contact List

Every GitHub star is a signal. Someone found your repository interesting enough to bookmark it — and in most cases, they've also linked their LinkedIn or Twitter/X profile right on their GitHub page. Eigent can walk through every single stargazer's profile and extract that data into a structured table, giving you a ready-made list of potential users, contributors, or outreach targets.

1Identify the Repository

Start by telling Eigent which GitHub repository to pull stargazers from. For this workflow, the target is the Eigent open-source repository:

Get all the stargazers' information from https://github.com/eigent-ai/eigent. Save into a table including their LinkedIn and X links, which are usually present in their GitHub profiles.

You can substitute any public GitHub repository URL. The workflow scales to repositories with thousands of stars.

2Eigent Fetches the Stargazer List

Eigent navigates to the repository's stargazers page and collects every username. Depending on the total count, it may paginate through multiple pages of results. The browser agent handles this automatically — you don't need to worry about pagination limits or rate limiting.

3Profile Enrichment

For each stargazer, Eigent visits their GitHub profile page to collect:

  • Username and display name (if set)
  • GitHub profile URL
  • LinkedIn URL (if listed in their profile)
  • X (Twitter) URL (if listed in their profile)
  • Bio or location (optional, if requested)

This enrichment step runs in parallel across multiple profiles to keep the total time manageable even for large repositories.

4Table Output

The final output is a structured data table — saved as a CSV or displayed inline — with one row per stargazer and columns for each data point. The table is ready to import into a CRM, export to Google Sheets, or use as the basis for an outreach campaign.

5Filter and Segment

After the initial extraction, you can ask Eigent to filter or segment the data:

Filter this list to only stargazers who have a LinkedIn profile listed.

Show me only the stargazers who have more than 100 followers on GitHub.

Sort by most recently starred.

6Why This Matters

For open-source projects, your stargazer list is one of the most valuable and underused assets you have. These are people who have already self-selected as interested in what you're building. Eigent turns a passive vanity metric into an actionable contact database — without any manual profile-clicking or copy-pasting.

7What to Try Next

Do the same extraction for three competitor repositories and merge the results.

Find which of our stargazers are also contributors to similar open-source projects.

Cross-reference this list with our existing user database to identify who hasn't signed up yet.

Send a personalized outreach message to the top 50 stargazers who have a LinkedIn profile.

8Tips for Better Results

  • Run it on smaller repos first. For repositories with 10,000+ stars, the enrichment step takes longer. Test your prompt on a smaller repo before running it at full scale.

  • Request specific fields. If you only need LinkedIn links and don't need X/Twitter, say so — Eigent will skip the extra profile parsing and run faster.

  • Ask for a summary too. Adding "also tell me the most common employer domains and locations listed in the profiles" gives you instant audience insights on top of the raw list.

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