I got tired of being the router between incoming work and coding agents, so I built a local control layer

Most of my work does not arrive as a clean prompt for an agent. It shows up in email, Teams, Slack, GitHub, Jira, or a scheduled report. I was spending too much time doing the orchestration myself: reading the surrounding thread, deciding whether something was actually a task, rewriting it with enough context, choosing a coding agent and repo, then carrying the result back to where the request started. I built Taskuary to handle that coordination layer. It pulls incoming work into one timeline and triages each item into a task, a draft reply, or something to ignore. Coding tasks can open real Claude Code, Codex, Gemini, Cursor, or other supported CLI sessions in your own checkout. The result comes back into the same workflow, while outbound replies and reports wait in a review queue. Nothing sends without approval. The part I care about is not making one agent more autonomous. It is giving several agents a shared work queue, enough source context to act, and a clear boundary around what still needs a human decision. It runs locally with FastAPI, React, and SQLite. There is no hosted account or telemetry, and it is MIT licensed. It is still early, currently v0.3, so I expect rough edges and breaking changes before 1.0. I would like feedback from people building agent systems: where should orchestration stop and agent autonomy begin? What context should be passed automatically, and what should always require an explicit human choice?