TaskMiner_AI

Managing multiple tasks without clear priorities is one of the most common yet underestimated challenges in software development and project management. When deadlines overlap, dependencies are unclear, and sprint planning is done manually, teams lose valuable time to decision paralysis and avoidable blockers. The Task Input & Storage System was built to eliminate exactly that friction. Built with Python, Streamlit, and JSON, this tool provides a clean and intuitive interface for capturing, organizing, and prioritizing tasks from a single place. Each task stores rich metadata — including title, description, priority level, status, estimated effort, labels, dependency IDs, and notes — ensuring nothing important is ever lost or ambiguous. The system supports full CRUD operations and lets users search and filter tasks by priority, status, or keyword. Every change is auto-saved to a local JSON file, keeping the setup lightweight with zero database overhead. Where the system truly stands out is its Bob AI Integration. Users can export their entire task list as structured, LLM-ready text that captures all metadata and relationships. This export is then analyzed by Bob, a custom Task Prioritizer AI mode, which returns four types of actionable intelligence: dependency mapping to understand what blocks what, step-by-step execution order recommendations, proactive risk and blocker identification, and automated sprint planning that groups tasks into logical delivery phases. Bob also generates color-coded visual flow diagrams as PNG files, giving teams an instant overview of their workload. Getting started requires just three commands — install, launch, and export. The codebase is modular and well-structured, making it easy to extend or integrate into existing workflows. Future plans include native integrations with Jira, GitHub Issues, and Linear, along with team collaboration features and a mobile app. Stack: Python 3.9+ · Streamlit 1.32.0 · JSON · Bob AI