Shawn Chumbar@shawn_chumbar91

Our project introduces an AI-driven debugging ecosystem built on **Coral Protocol**, designed to streamline the end-to-end process of identifying, diagnosing, and resolving software bugs. The system connects issue tracking platforms, intelligent agents, external developer tools, and human oversight into a single cohesive workflow that emphasizes automation, trust, and collaboration. Modern software teams rely on bug tracking platforms like Jira or Trello to manage reported issues. While these tools centralize bug reports, they do not solve the deeper challenge of debugging: finding the root cause, generating a fix, and ensuring safe deployment. Developers often spend significant time sifting through logs, searching documentation, and manually implementing patches. Our project addresses this inefficiency by introducing an **AI-assisted debugging pipeline** that automates repetitive tasks while preserving human control at critical decision points. At the front of the system is the **User**, who submits a bug report via a standard **Work Tracking Platform**. This represents the starting point for all workflows. A webhook integration ensures that any newly created report is automatically forwarded to the **Interface Agent** inside Coral Protocol. The Interface Agent acts as the entry point for the Coral ecosystem, listening for bug reports and passing them into the network. The **Unified Debugging Agent** is the core intelligence of the system. Once it receives a task, it initiates a single session powered by a large language model (LLM). Unlike traditional multi-step debugging systems that chain independent scripts, the Unified Debugging Agent orchestrates the entire debugging flow within one reasoning context, ensuring coherence across all stages.

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