As a freelance developer, I wanted to automate finding and responding to open-source bounty issues on GitHub. Here is how I built a Python-based AI agent that monitors repositories, analyzes issues, and drafts proposals.
The Problem
Open-source projects like Expensify offer $250 bounties for bug fixes. But the competition is fierce: you need to be one of the first to submit a quality proposal.
The Solution: A Python Monitoring Agent
I built a lightweight system with three components:
1. GitHub Issue Monitor
A simple polling loop that checks for new issues with specific labels every 5 minutes using the GitHub API.
2. Issue Analyzer
The agent reads the issue body, identifies the bug type, extracts reproduction steps, and determines which files are likely affected.
3. Proposal Generator
Based on the analysis, it generates a targeted proposal with root cause analysis, solution approach, and timeline.
Key Lessons
- Speed matters - Be first with a quality proposal
- Do not over-automate - Human review before submission
- Monitor multiple repos - Diversify opportunities
- Read the contributing guide - Each project is different
Results
In my first week:
- Monitored 3 repositories
- Identified 12 new bounty issues within minutes
- Submitted 5 proposals
- Got assigned to 2 issues
Need Automation Built?
I specialize in:
- Web scraping - Any website, anti-bot handling
- Python automation - Email, files, APIs
- AI agents - Monitoring and automated responses
- Translation - English and Chinese (native both)
Based in Sydney, Australia | GitHub: baode-ai-writer
What automation have you built? Comment below!
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