Agents · Neo Docs v6.1.0

Agent components use an LLM to reason and act. They range from general-purpose autonomous agents to specialised routing and delivery agents.

Agent

A general-purpose autonomous agent that uses an LLM with tools and knowledge bases to reason and act over multiple steps.

Use in a flow

Add an Agent node to the canvas.
Select Model Provider and Model ID.
Write Agent Instructions (system prompt).
Optionally connect Tools, select a Knowledge Base, and wire Input from Input or upstream components.
Connect Selected Output to Output or the next step.

Input ──► Agent ◄── Tools / MCP Client
Knowledge Base (dropdown) ──► Agent
Agent (Selected Output) ──► Output

The agent can call connected tools, retrieve knowledge base context, use memory, and run guardrails before returning a response.

Parameters — Model and instructions

Parameter	Default	Hidden	Description
Model Provider	—	No	LLM provider for the agent.
Model ID	—	No	Model to use. Refresh to load available models.
Region Name	—	No	Region where the selected model is available.
Agent Instructions	—	No	System prompt that guides agent behavior.
Input	—	No	User message or task for the agent to process.

Parameters — Tools and knowledge

Parameter	Default	Hidden	Description
Tools	—	No	Connected tool components the agent can call.
Knowledge Base	—	No	Optional knowledge base for retrieval-augmented responses. Refresh to load options.
Fallback Knowledge Base	—	Yes	KB used when the user lacks access to the primary KB.
Assume Policy	—	No	Access policy limiting which resources this agent can use.

Parameters — Memory and behavior

Parameter	Default	Hidden	Description
STM Retrieval Limit	10	Yes	Recent conversation turns from short-term memory.
LTM Retrieval Limit	10	Yes	Records from long-term memory via semantic search.
User Level LTM	false	Yes	Scope long-term memory per user instead of shared agent namespace.
Current Date	false	Yes	Add a tool that returns the current date.
Max Iterations	15	Yes	Maximum reasoning steps before the agent stops.
Handle Parse Errors	true	Yes	Recover from input parsing errors.
Verbose	true	Yes	Detailed agent logging during execution.

Parameters — Delivery and personalization

Parameter	Default	Hidden	Description
Enable File Deliverables	false	No	Let the agent register files for delivery to channels.
Enable Channel Delivery	false	No	Inform the agent that a downstream Channel Agent handles outbound delivery.
Post-HITL Instructions	—	Yes	Custom instructions after Human In The Loop approval.
Enable Personalization	false	No	Inject user personalization preferences into the prompt.

Parameters — Structured output

Parameter	Default	Hidden	Description
Enable Structured Output	false	No	Return JSON matching a defined schema.
Output Schema	—	No	Table of field names, types, and descriptions. Appears when structured output is enabled.
Output Field	response	No	Which field to expose on Selected Output when structured output is enabled.
Schema Name	OutputModel	Yes	Name for the output schema model.
Format Instructions	—	Yes	Instructions for formatting structured output.

Parameters — Guardrails

Parameter	Default	Hidden	Description
Enable Input Guardrail	false	No	Validate input before agent execution.
Input Guardrails	—	Yes	Guardrails to apply on input. Appears when enabled.
Enable Output Guardrail	false	No	Validate agent output after execution.
Output Guardrails	—	Yes	Guardrails to apply on output. Appears when enabled.

Outputs

Output	Description
Selected Output	Agent response message, or a specific structured output field.
Language Model	The built language model instance (for wiring to other components).

Limitations

Model required — A model must be selected before the agent can run.
Tool mode — When used as a tool by another agent, the deprecated Agent Description applies.
Knowledge base — Retrieval uses the selected KB’s embedding model and search settings internally.

Intent Classification Agent (Beta)

Classifies the user’s intent and returns a structured output with the classified category.

Use in a flow

Add an Intent Classification Agent (Beta) node to the canvas.
Select Model Provider and Model ID.
Define Agent Instructions and an Output Schema (for example, an intent string field).
Connect Input from Input or an upstream message.
Connect Structured Output downstream (for example, a conditional router or Agent).

Input ──► Intent Classification Agent ──► Router / Agent

Parameters

Parameter	Default	Hidden	Description
Model Provider	—	No	LLM provider for classification.
Model ID	—	No	Model to use.
Region Name	—	No	Region where the model is available.
Agent Instructions	helpful classifier prompt	No	System prompt guiding intent classification.
Input	—	No	User query to classify.
Output Schema	intent field	No	Fields to return (name, description, type).
Output Field	structured_output	No	`structured_output` for full JSON, or a specific schema field name.
Enable Streaming	false	No	Run classification in streaming mode.
Schema Name	—	Yes	Name for the output schema model.
Model Kwargs	—	Yes	Extra keyword arguments for the model.

Outputs

Output	Description
Structured Output	Classified intent as a message. Returns full JSON or a single field value based on Output Field.

Limitations

Beta — Behavior may change.
Schema required — Output Schema must define at least one field.
Structured output — Uses native structured output when the model supports it; otherwise falls back to prompt-based parsing.

Human In The Loop (Beta)

Pauses the flow and sends an approval request to configured delivery targets. The flow resumes once approved or rejected.

Use in a flow

Add a Human In The Loop (Beta) node after an upstream Agent (or any component that produces a bot response).
Wire User Query and Bot Response from upstream steps.
Configure Approval Delivery Targets (channel, recipient, event type).
Connect Response downstream.

Input ──► Agent ──► Human In The Loop ──► Channel Agent / Output

On first run, the component sends an approval card to the configured channels and pauses execution. When a human approves or rejects, the flow resumes with the action result.

Parameters

Parameter	Default	Hidden	Description
User Query	—	No	Original user message for approval context.
Bot Response	—	No	Generated answer included in the approval request. Required.
Approval Title	Action Required	No	Title on the approval card.
Approval Description	default text	No	Description explaining what needs approval.
Approval Delivery Targets	—	No	Where to send approval requests (channel, event type, recipient). One row. Refresh to load routes.
Send Reply to Original Channel	true	No	Send confirmation back to the incoming channel after dispatching the approval.
Attach Incoming Files	false	No	Attach session-uploaded files to the approval card.
Post-Approval Instructions	—	No	Custom instructions injected into the main agent after approval.
Timeout (seconds)	86400	No	Timeout value in seconds. Under advanced settings.
Auto-reject on Timeout	false	No	Under advanced settings.
Context Data (JSON)	{}	No	Extra context shown on the approval card. Under advanced settings.
Assume Policy	—	No	Access policy for channel and resource access.

Outputs

Output	Description
Response	On pause: JSON with `awaiting_approval` status. On resume: approval or rejection message.

Limitations

Beta — Behavior may change.
Delivery target required — One complete row in Approval Delivery Targets (channel, event type, recipient). Approval requests are delivered to Microsoft Teams.
Playground and NeoGPT — Approval requests are not raised in these channels; the flow continues without review.
Flow pause — Execution stops until a human responds.
Event type — Approval targets use the hitl_approval event type automatically.

Channel Agent (Beta)

An agent wired to a communication channel. Handles inbound messages and routes outbound replies to configured delivery targets.

Use in a flow

Add a Channel Agent (Beta) node after an upstream Agent that generates the message content.
Wire User Query and Bot Response.
Configure Outbound Routes or Delivery Targets.
Connect Response downstream.

Input ──► Agent ──► Channel Agent ──► Output

The Channel Agent resolves the correct channel and recipient from the user query and delivers the bot response. Fully configured delivery targets are sent automatically; partial rows are resolved by the LLM at runtime.

Parameters

Parameter	Default	Hidden	Description
User Query	—	No	Original user query — used to determine channel, recipient, and event type.
Bot Response	—	No	Content from an upstream agent to deliver. Required.
Model Provider	—	No	LLM provider for routing decisions.
Model ID	—	No	Model used to resolve delivery targets.
Agent Instructions	auto	No	Base system prompt. `auto` generates routing instructions from configured routes.
Additional Instructions	—	No	Extra routing or delivery overrides appended to the prompt.
Outbound Routes	—	No	Channels this agent can deliver to. Refresh to load routes.
Delivery Targets	—	No	Table of outbound targets (channel, event type, recipient, invocation). Empty fields are resolved by the LLM.
Send Reply to Original Channel	true	No	Send confirmation back to the incoming channel after delivery.
Max Iterations	10	Yes	Maximum agent reasoning steps.
Handle Parsing Errors	true	Yes	Recover from tool parsing errors.
Verbose	false	Yes	Detailed agent logging.
Model Kwargs	—	Yes	Extra keyword arguments for the model.

Outputs

Output	Description
Response	Delivery result message from the channel agent.

Limitations

Beta — Behavior may change.
Routes required — At least one Outbound Route or Delivery Target must be configured.
Bot response required — Upstream content must be wired to Bot Response.
Automatic targets — Targets marked automatic must have channel, event type, and recipient fully configured.

Flow Agent

Calls another Agentic Flow as a sub-flow and returns its output into the current flow.

Use in a flow

Add a Flow Agent node to the canvas.
Select Workspace and Flow Agent (refresh to load options).
Wire Input from an upstream message or component.
Optionally set Tweaks to override sub-flow parameters.
Connect Response or Full Response downstream.

Input ──► Flow Agent ──► Output / Agent
Agent ──► Flow Agent (as a tool)

Parameters

Parameter	Default	Hidden	Description
Input	—	No	Input message or data for the sub-flow.
Workspace	—	No	Workspace containing the target flow. Refresh to load.
Flow Agent	—	No	Agentic flow to execute. Refresh after selecting a workspace.
Conversation history	—	No	Optional conversation history passed to the sub-flow.
Session ID	—	No	Session ID for conversation continuity.
Output Component	—	No	Specific output component to retrieve from the sub-flow.
Tweaks	—	No	Key-value parameter overrides for the sub-flow. Auto-populated from the selected flow.
Enable Retry	—	Yes	Retry failed API requests.
Max Retries	—	Yes	Maximum retry attempts.
Save Output as Variable	—	Yes	Store output as a named flow variable.
Variable Name	—	No	Name for the flow state variable.

Outputs

Output	Description
Response	Main text output from the sub-flow execution.
Full Response	Complete API response including metadata and all output data.

Limitations

Workspace and flow required — Both must be selected before execution.
Authorization — Runs using the flow’s authorization context; sub-flow must be accessible to the caller.
Session continuity — Pass Session ID to maintain conversation context across parent and child flows.
Tweaks — Values support {{variable}} placeholders resolved from flow context.

Voice Agent Call

Triggers a Voice Agent call and returns the call response.

Use in a flow

Add a Voice Agent Call node to the canvas.
Select Workspace and Voice Agent (refresh to load options).
Fill in Call Parameters (auto-populated when a voice agent is selected).
Connect Call Response or Status downstream.

Flow trigger ──► Voice Agent Call ──► Output / Agent

Parameters

Parameter	Default	Hidden	Description
Workspace	—	No	Workspace containing the voice agent. Refresh to load.
Voice Agent	—	No	Voice agent to trigger. Refresh after selecting a workspace.
Call Parameters	—	No	Parameter table auto-populated from the selected voice agent. Fill in values for each parameter.
Enable Retry	—	Yes	Retry failed API requests.
Max Retries	—	Yes	Maximum retry attempts.
Save Output as Variable	—	Yes	Store output as a named flow variable.
Variable Name	—	No	Name for the flow state variable.

Outputs

Output	Description
Call Response	API response from the voice call (result, status code, raw data).
Status	HTTP status code from the last call attempt.

Limitations

Workspace and voice agent required — Both must be selected before triggering a call.
Call parameters — Required parameters depend on the selected voice agent configuration.
Authorization — Requires valid authorization to call the voice backend service.

Skills

Resolves workspace skills and outputs them for an Agent to use. See Skills for creating and managing skills.

Use in a flow

Add a Skills node and select one or more active skills.
Set each skill to Allow or Ask in Skill Approvals.
Connect Skills to the Skills input of an Agent.

Skills ──► Agent ──► Output

The agent receives a short list of the selected skills and reads a skill’s SKILL.md only when a request matches it.

Parameters

Parameter	Default	Hidden	Description
Workspace ID	—	Yes	Workspace used to fetch available skills. Filled automatically.
Skill Provider	AGENTCORE	No	Runtime provider for downloading and hosting skills.
Skills	—	No	Skills to load into the agent sandbox. Refresh to load the workspace’s active skills.
Sandbox Status	Not checked	No	Refresh to test connectivity to the sandbox runtime.
Skill Approvals	Allow	No	One row per selected skill. Set a row to Ask to pause for approval before the agent uses that skill. Rows follow the Skills selection and cannot be added or deleted.

Outputs

Output	Description
Skills	The selected skills, for the Agent’s Skills input.

Limitations

Approval destination — A skill set to Ask sends its approval request to the delivery target of a Human In The Loop node in the flow.
Multiple nodes — Several Skills nodes can be connected to one Agent.

Break Agent

Immediately terminates the current flow execution with an optional break reason and instruction.

Use in a flow

Add a Break Agent node where you want to pause execution after processing.
Configure it like a standard Agent (model, instructions, tools, input).
Optionally set Break Instruction and Break Reason.
Connect Selected Output to Output so the response is delivered before the pause.

Input ──► Agent steps ──► Break Agent ──► Output

The agent processes the input, streams the response downstream, then pauses the flow. On resume, it runs as a normal agent without breaking again.

Parameters

Break Agent includes all Agent parameters plus the following:

Parameter	Default	Hidden	Description
Break Instruction	execution state summary prompt	No	Instruction injected when breaking. The agent summarizes execution state.
Should Break	true	Yes	When `false`, behaves like a normal Agent without pausing.
Break Reason	agent_break	Yes	Reason logged for the break (for debugging).

Outputs

Output	Description
Selected Output	Agent response message before the break is set.

Limitations

Pause after response — The response is sent to downstream components before execution pauses.
Resume behavior — On resume (is_resume in flow context), the agent does not break again.
Execution ID — Flow can be resumed later using the execution ID stored in flow context.
Should Break off — Set Should Break to false to use as a standard Agent without pausing.