The Canvas
The Builder Canvas is the visual overview of the agent configuration inside the UPTIQ Qore Platform Agent Builder. It presents the agent at the center, with its connected knowledge, skills, triggers, and integrations arranged around it in a structured layout.

The canvas acts as a high-level representation of how the agent has been configured. At a glance, you can quickly understand:
What knowledge sources are attached
Which skills and connectors are available
How many triggers are configured
What runtime capabilities the agent has access to
Most configuration changes happen through Agent Config, but the canvas serves as the primary navigation surface for understanding the agent setup and accessing related workflows.
The core layout
The canvas follows a simple mental model: one agent with connected capabilities around it.
Agent
The agent appears at the center of the layout with its avatar, name, and agent type.
Knowledge
Knowledge sources appear to the left of the agent, below Triggers. These represent the files, documents, and connected data sources the agent can reference during execution.
Skills and Integrations
Skills and connected integrations appear to the right of the agent. These include platform-provided skills, MCP-based integrations, external connectors, and additional capabilities attached to the agent.
Triggers
Triggers appear to the left of the agent, above Knowledge. Triggers define the events or actions that can initiate agent execution.
Each section in this guide maps back to one of these areas of the canvas.
The headers
The Agent Builder has two headers: one above the chat on the left, and one above the canvas on the right.
Chat header
Agent name: opens the agent's options menu, with Back and Rename Agent.
Chat history: your past conversations with the builder.
New chat: starts a fresh conversation with the builder.
Need Help? Report the Issue (the ? icon): opens a form to raise a request. See Report an issue.
Toggle Panel: hides or shows the chat.
The builder chat
Attach Files: select + beside Type here…, then Attach Files (Upload files from your device).
Context usage: the ring beside the send arrow shows how much of the chat's context is used. Hover for how full it is, such as 11% Full, the tokens used out of the total, such as ~21.1K / ~200.0K Tokens, and the tokens taken by User messages, Assistant messages, Tool calls, and Tool results.
Credits per reply: each builder reply shows the credits it used, such as 70.3 credits · $0.0351.
Chats from an older version: these show This chat was made in an older version. Select Migrate chat to keep building in it with its history (migrating can take a while), or Start new conversation.


Canvas header

From left to right:
Overview and Flow: the two views of the agent. See Overview and Flow tabs.
Credits and cost: what the agent has used, such as
1,530 creditsand$0.77. Hover for the breakdown.Version selector: the version you're viewing, such as Draft Version or v1.0. See Runtime & Versioning.
Download Agent Version (download icon): downloads the selected version's file to your browser. It appears only when you're on a saved version with no unsaved changes.
Integrate Agent (
</>): the options for running the agent inside your own app. See Integrate Agent.Export Agent (export icon): exports the agent as a package, delivered by email. You need the Export Agent capability; without it the button is disabled. See Export Agent.
Agent Config: opens the agent's settings.
Try Agent: opens the Agent Playground in a new tab, where you can chat with the agent. You need the Trigger Agent capability, and the agent needs a widget key.
Overview and Flow tabs
The canvas has two tabs, in the canvas header.
Overview
The default view. It shows the agent at the center with its Triggers, Knowledge, Skills, and Integrations cards around it.

Flow
The Flow tab (formerly Plan) displays the agent’s decomposed execution flow as a sequence of steps the agent may follow during runtime, under What the Agent will do.
Instead of showing the visual layout of connected components, the Flow tab focuses on how the agent approaches task execution. It breaks the workflow into structured milestones, helping you understand:
How the agent plans to solve a task
The sequence of execution stages
Which skills or integrations may be used during execution
How larger workflows are decomposed into smaller operational steps
This view is useful for understanding orchestration logic, validating execution behavior, and reviewing how the agent is expected to progress through a task.

Report an issue
To raise a request, select Need Help? Report the Issue (the ? icon) in the chat header. The Need Help? Raise a Request form opens with the agent already filled in.

Title: required, up to 200 characters.
What do you need help with?: required, up to 2,000 characters. Explain the issue or the outcome you're trying to achieve.
Attachment: optional. Upload up to five PNG or JPEG screenshots, each up to 10 MB.
Select Submit Request. Qore confirms with Issue reported successfully. Thank you for your feedback! The same form is available in App Builder.
Interactive Areas on the Canvas
The canvas primarily acts as a visual overview rather than a direct editing surface.
Most nodes are informational summaries of the current agent state. Configuration changes are managed through Agent Config and related setup flows.
Some sections act as shortcuts into deeper workflows, such as:
Adding knowledge
Managing skills
Configuring integrations
Setting triggers
The visual layout helps you quickly understand what is connected to the agent and identify what may still need configuration.
Why this matters
The Builder Canvas serves as the central navigation and visualization layer for the agent.
Understanding this layout makes it easier to:
Review the current agent setup
Navigate to the correct configuration area
Validate attached knowledge and integrations
Identify missing runtime capabilities
Troubleshoot agent behavior during testing
Most pages in this guide either explain a section visible on the canvas or describe the configuration flows launched from it.
Maintained by Abhishek Paul
AI-assisted, human-approved

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