The Library is Origin’s analytics building-block store. It contains all the reusable components that power your dashboards and automations: Kernels, Canvases, Workflows, and Signals. Access it by clicking the grid icon (⊞) in the far-left navigation strip.
Library sections
Kernels
Kernels are the fundamental unit of Origin analytics. Each Kernel is a named, versioned query that:
- Specifies a data source (e.g.,
/activity-summary, /model-mix, /agent-surfaces)
- Defines the computation (aggregation, filtering, grouping)
- Specifies how to render the result (bars, lines, table, metric card)
Built-in kernels
Origin ships with 14 built-in kernels covering the most common analytics needs:
Viewing a kernel
Click any kernel in the left panel to open it. The center panel shows the kernel’s output visualization, and the right panel shows the kernel’s metadata:
- Command — the kernel’s identifier (e.g.,
/model-mix)
- Title — human-readable name
- Steps — number of computation steps
- Render — visualization type (bars, lines, table, etc.)
- Params — configurable parameters (if any)
- Updated — last modification date
- Description — what the kernel measures and how to interpret it
- Used in canvases — which canvases include this kernel
Forking a kernel
Built-in kernels are read-only. To customize one, click Fork to Customize. This creates a copy in your Library that you can edit. Forked kernels are prefixed with your organization name and can be modified without affecting the original.
Canvases
The Library lists all saved Canvases. Clicking a canvas opens it in the center panel. The Library shows:
- Canvas name and description
- How many Kernels it contains
- Last modified date
Currently there are 5 built-in canvases, including /ai-usage-overview, /adoption-and-concentration, and /shadow-ai.
Workflows
Workflows are triggered automations. A Workflow runs one or more Kernels on a schedule or in response to a Signal, then takes an action (send a Slack message, create a ticket, update a record). The Workflow builder is available via the + button in the Workflows section.
Signals
Signals are real-time stream triggers. A Signal watches your AI activity stream for a specific pattern — a new agent appearing, a token spend threshold being crossed, a new MCP tool spreading to more than N endpoints — and fires an event when the condition is met. Signals can trigger Workflows.
The fastest way to build a custom analytics view is to find the closest built-in kernel, fork it, adjust the query parameters, and add it to a new Canvas. The Fork to Customize button appears in the right panel when you select any built-in kernel.
