AI-assisted ticket drafting with project context

AppHandoff's AI ticket drafting lets coding agents create detailed implementation tickets based on scan results and project context. Instead of generating vague TODO items, agents produce tickets with specific endpoint paths, request and response schemas, implementation steps, and acceptance criteria.

The drafting process uses MCP tools to access the full project state: current mismatches, existing tickets, API specifications, and scan history. This context allows agents to write tickets that account for dependencies, avoid duplicate work, and reference specific lines of code that need changes.

The drafting flow is grounded in real project data instead of generic prompt expansion.

Human developers review agent-drafted tickets before work begins. The review step ensures that implementation plans make architectural sense and align with team conventions. Approved tickets enter the Kanban pipeline where either agents or humans can pick them up for execution.

Every agent-drafted ticket goes through a human review step. This is not a formality — it is the checkpoint that prevents agents from planning work that conflicts with architectural decisions, ongoing tickets, or team conventions the agent does not know about.

After approval, tickets move into the standard Kanban pipeline. The same ticket can be picked up by an agent for implementation or by a human developer — both see the same context, acceptance criteria, and implementation notes.