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github-project-contributor-finder-api-skill

Esta skill ajuda usuários a extrair detalhes de projetos de repositórios GitHub e informações de contato de contribuidores usando palavras-chave, estrelas e datas de atualização. O agente deve aplicá-la proativamente quando usuários buscarem projetos GitHub por palavras-chave, encontrarem contribuidores de código aberto em domínios específicos, extraírem contatos de desenvolvedores de repositórios GitHub ou descobrirem repositórios em alta.

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Atualizado há 4 meses

Ver no GitHub ↗ Licença: MIT

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GitHub Project & Contributor Finder API Skill

📖 Brief

This skill utilizes BrowserAct's GitHub Project & Contributor Finder API to extract project details and contributor contact information from GitHub. Simply provide keywords, minimum stars, and an update date filter — BrowserAct traverses the search results, extracts repository metrics, and fetches detailed contributor profiles, returning it all directly via API without building crawler scripts or dealing with rate limits.

✨ Features

  1. No Hallucinations: Pre-set workflows avoid AI generative hallucinations, ensuring stable and precise data extraction.
  2. No Captcha Issues: No need to handle reCAPTCHA or other verification challenges.
  3. No IP Restrictions: No need to handle regional IP restrictions or geofencing.
  4. Faster Execution: Tasks execute faster compared to pure AI-driven browser automation solutions.
  5. Cost-Effective: Significantly lowers data acquisition costs compared to high-token-consuming AI solutions.

🔑 API Key Setup

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
  2. Type: string
  3. Description: Keywords for searching repositories.
  4. Example: browser automation, react framework, machine learning
  5. Default: browser automation
  1. stars
  2. Type: number
  3. Description: Minimum number of stars the repository should have.
  4. Example: 100, 1000
  5. Default: 100
  1. updated
  2. Type: string
  3. Description: Filter repositories by the date they were last updated (format: YYYY-MM-DD).
  4. Example: 2026-01-01, 2025-06-01
  5. Default: 2026-01-01
  1. Page_Turns
  2. Type: number
  3. Description: Number of search result pages to paginate through. For example, if there are 39 pages and you want the first 2, input 2.
  4. Example: 1, 2
  5. Default: 1
  1. date_limit_per_page
  2. Type: number
  3. Description: Number of data items to extract per page in the search results list.
  4. Example: 5, 10
  5. 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:
  2. 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.
  3. 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.
  1. Retry Limit:
  2. 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.
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