GitHub Project & Contributor Finder API Skill

Before running, check the BROWSERACT_API_KEY environment variable. If not set, do not take other measures; ask and wait for the user to provide it. Agent must inform the user:

"Since you haven't configured the BrowserAct API Key yet, please visit the BrowserAct Console to get your Key."

🛠️ Input Parameters

The agent should flexibly configure the following parameters based on user requirements:

1. KeyWords

   • Type: string
   • Description: Keywords for searching repositories.
   • Example: browser automation, react framework, machine learning
   • Default: browser automation

2. stars

   • Type: number
   • Description: Minimum number of stars the repository should have.
   • Example: 100, 1000
   • Default: 100

3. updated

   • Type: string
   • Description: Filter repositories by the date they were last updated (format: YYYY-MM-DD).
   • Example: 2026-01-01, 2025-06-01
   • Default: 2026-01-01

4. Page_Turns

   • Type: number
   • Description: Number of search result pages to paginate through. For example, if there are 39 pages and you want the first 2, input 2.
   • Example: 1, 2
   • Default: 1

5. date_limit_per_page

   • Type: number
   • Description: Number of data items to extract per page in the search results list.
   • Example: 5, 10
   • Default: 5

🚀 Invocation Method

Agent should execute the following command to invoke the skill:

# Example invocation (all parameters)
python -u ./scripts/github_project_contributor_finder_api.py "browser automation" 100 "2026-01-01" 1 5

# Minimal invocation (only keywords, others use defaults)
python -u ./scripts/github_project_contributor_finder_api.py "react framework"

⏳ Execution Monitoring

Since this task involves automated browser operations, it may take several minutes. The script outputs timestamped status logs continuously (e.g., [14:30:05] Task Status: running). Agent guidelines:

• Monitor the terminal output while waiting.
• As long as new status logs appear, the task is running normally; do not misjudge it as frozen.
• Only consider triggering retry if the status remains unchanged for a long time or output stops without a final result.

📊 Data Output

Upon successful execution, the script parses and prints the structured results from the API response.

Project Fields:

• repository_name: The name of the GitHub repository.
• repository_url: The URL link to the repository.
• repository_owner_name: The owner/creator of the repository.
• repository_description: A brief description of the repository.
• star_count: The number of stars the repository has received.

Contributor Fields:

• user_name: The GitHub username of the contributor.
• profile_url: The URL link to the contributor's profile.
• bio: The bio or short description of the contributor.
• repositories_summary: A summary of other repositories owned by the contributor.
• personal_website: The contributor's personal website link.
• twitter: The contributor's Twitter handle.

⚠️ Error Handling & Retry

If an error occurs during script execution (e.g., network fluctuations or task failure), the Agent should follow this logic:

1. Check Output Content:

   • If the output contains "Invalid authorization", it means the API Key is invalid or expired. Do not retry; guide the user to re-check and provide the correct API Key.
   • If the output contains "concurrent" or "too many running tasks", it means the concurrent task limit has been reached. Do not retry; guide the user to upgrade their plan. Agent must inform the user:

     "The current task cannot be executed because your BrowserAct account has reached the concurrent task limit. Please visit the BrowserAct Plan Upgrade Page to upgrade your plan."

   • If the output does not contain the above error keywords but the task failed (e.g., output starts with Error: or returns empty results), the Agent should automatically re-execute the script once.

2. Retry Limit:

   • Automatic retry is limited to one time. If the second attempt fails, stop retrying and report the specific error to the user.

🌟 Typical Use Cases

1. Tech Recruiting: Gather contributor profiles and social links from popular repositories to build candidate pipelines.
2. Open-Source Discovery: Search for trending repositories by keywords and star count to find valuable projects.
3. Developer Outreach: Collect personal websites and Twitter handles of active contributors for developer tool marketing.
4. Community Building: Identify and connect with active open-source contributors in specific domains.
5. Competitor Analysis: Monitor which developers contribute to competing projects.
6. Partnership Scouting: Find repository owners for potential collaboration or sponsorship.
7. Market Research: Analyze repository metrics and descriptions to understand technology trends.
8. Lead Generation: Generate targeted leads for developer tools by finding projects with relevant tech stacks.
9. Academic Research: Discover recently updated repositories in specific research areas.
10. Talent Mapping: Build a database of skilled developers based on their GitHub contributions and profiles.