dotbot: dotbot wraps AI-assisted coding in a managed, transparent workflow where every step is tracked. It features multi-workflow pipelines, per-task isolation, and a web dashboard for observability. It supports multiple AI providers and enables team collaboration with human-in-the-loop Q&A.; context-mode: Every tool call in an MCP (Model-Controller-Program) environment dumps raw data into the context window, quickly consuming space and causing the agent to lose track of ongoing tasks. Context Mode is an MCP server that tackles this by sandboxing tool outputs to significantly reduce context usage, tracking session events in SQLite for continuity, and promoting 'think in code' to minimize data processing within the LLM.
Managing and tracking AI-assisted development decisions across a team.
Deep repository research and analysis (e.g., architecture, contributors, issues)