skill-system-cockpit

You can consolidate note workflow and runtime signals into a single cockpit state by using a Python-based runtime to derive a JSON-serializable, renderer-agnostic state object from your workflow and ticket data for UI rendering.

A renderer-independent cockpit state is a unified, JSON-serializable view of notes, tickets, and runtime signals. You need it when multiple downstream UIs or automation pipelines must consume a consistent workflow state without renderer lock-in.

The cockpit TUI maintains synchronization through a dedicated feedback render pathway that updates the shared cockpit state. This ensures note feedback and the operator-facing dashboard views consistently reflect the same runtime data.

Yes, you can use a YAML-backed cockpit-state schema to define the structure. The runtime then derives state from task authority and evolution nodes, exposing a consistent object to your downstream tools and automation.

Yes, a frontmatter-defined manifest is required to configure the runtime. This setup allows the Python-based runtime to properly derive, render, and expose the consolidated cockpit state to your automation pipelines and tools.

The best way to coalesce agent tasks and runtime signals is to derive a shared state object via a Python runtime. This approach supports a read-only TUI and outputs a single source of truth for operator-facing dashboards.