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Custom Agents
Build your own AI agent in Agent Architect — pick the model, write the system prompt, attach tools that call your own systems and deploy it as a reusable Workflow Editor node. No code required.
What Are Custom Agents?
Custom Agents are AI agents you design yourself. Agent Architect is a visual, no-code designer: you pick the model, write the system prompt, attach tools that call your own APIs and databases, and deploy the result as a reusable node in the Workflow Editor. You can start from scratch or from a template.
In one sentence
Design the agent visually, connect it to the systems you already run, and drop it into any workflow — there is no separate agent infrastructure to maintain.
Screen Previews
A quick look at the screens. Use the toggle in the corner of each preview to switch between the dark and light themes.
Custom agent configuration: model, prompt, tools and knowledge
New tool registered and attached to an agent
Custom agent in the workflow node palette
How You Build One
Agent Architect lets you design a custom agent from scratch or from a template. You define every aspect — which model backs it, what its system prompt says, and what it is allowed to read and call — and it is ready to use immediately.
- Model — pick any active cloud model (Claude, GPT-4o) or local model (TinyLlama, Mistral)
- System prompt — define the agent's role, output format, and constraints in plain language
- Knowledge base — link collections so the agent retrieves and cites the right context automatically
- Test in Prompt Lab first — iterate on the prompt before saving an agent version
Integrate Your Systems
The Tool / Function Registry is how a custom agent reaches outside TotalApp — an HTTP call to your own API, a SQL query against a connected database, or a call to another TotalApp workflow. Define a tool once, attach it to any agent.
- Name, description, and a JSON Schema parameter spec — the model reads these to decide when to call the tool
- Implementation options: your own HTTP endpoint, a SQL query, a sandboxed JS function, or another workflow
- No manual prompt engineering — TotalApp injects the tool schema into the agent automatically
- Every call is logged in Observability, with the exact arguments and the value returned
Deploy & Reuse
Click Save Agent and your custom agent becomes an immediately draggable node in the Workflow Editor's palette — no restart, no re-deployment. It behaves exactly like a pre-built agent type, because it is built on the same architecture.
- Appears in the Workflow Editor node palette under "Custom Agents" the moment it is saved
- Every save creates a new version — running workflows keep using their pinned version
- Upgrade a workflow to a newer agent version explicitly, whenever you choose
- Reuse the same agent across as many workflows and screens as you need
Everything You Configure
Any Model, Cloud or Local
Back your agent with Claude, GPT-4o, or a local model like TinyLlama or Mistral — swap models without rebuilding the agent.
Prompt Lab for Iteration
Test and refine the system prompt in a live sandbox before it becomes a saved agent version.
Tool / Function Registry
Give your agent access to your own APIs, databases, or other TotalApp workflows via defined, reusable tools.
Knowledge Base Linking
Attach document collections so the agent retrieves and cites relevant context automatically for every query.
Workflow Editor Node
Every saved agent shows up as a draggable node — wire it into triggers, branches, and other agents like any other block.
Full Observability
Every run, tool call, and token is logged — audit exactly what your agent did and why.