Create an agent profile to define a reusable AI agent in MicroTx Workflows. An agent profile provides a centralized place
to configure an agent's role, instructions, prompt variables, tools, MCP servers, LLM
profile, model parameters, memory behavior, execution limits, capabilities, and
guardrails.
Use agent profiles to run agents within workflows through Agentic Tasks or as
conversational agents through the chat API. You can port templates defined for external
agents and execute it within MicroTx Workflows.
Before creating an agent profile, ensure that the required LLM profile, tool
configurations, and MCP server definitions are already available.
- Open the navigation menu and click Agentic AI.
- Click the Agent Profile tab.
The Agent Profile Definitions list page opens. All the agent
profiles that you have defined are displayed in a table.
- Click
.The New Agent Profile Definition dialog
box appears.
- Enter the following information.
- Name: Enter a unique and descriptive name. This name
is used to reference the agent profile definition in an Agentic Task in
a workflow or through the chat conversation API using the
agentName parameter. The name can be up to 128-characters long. Use only
letters, numbers, underscores (_), and hyphens (-). Spaces and other
special characters are not supported.
- Description: Optional. Provide a
brief description of this agent profile.
- Role: Specify the role of the agent
to be included in the execution prompt. This field helps establish the
agent’s high-level behavior, responsibilities, boundaries, and tone as
shown in the following example. Keep the content concise and stable so
it consistently guides the agent during execution. The maximum supported
length is 200000
characters.
You are an expert Oracle Database Assistant. Your primary function is to help users interact with the database by translating their natural language requests into valid SQL queries. You are precise, knowledgeable,and cautious, especially with data modification commands.
- Instruction: Enter detailed instructions to define
the agent's behavior during execution. Describe what the agent should do
when invoked, how it should respond, how it should use available tools,
and any behavioral rules or constraints it must follow while interacting
with workflow inputs, tools, or users. Keep the instructions clear,
specific, and action-oriented so the agent behaves consistently as shown
in the following example. The maximum supported length is 400000
characters.
Your primary task is to parse the user's request and convert it into a valid Oracle SQL query.
1. Analyze the user's request to understand their goal (e.g., retrieve data, describe a table, count rows).
2. Construct the appropriate SQL query using Oracle syntax.
3. Present the results from the database to the user in a clear and easy-to-understand format. For example, a markdown table for data.
- Capabilities: Select one or more of the following
options to define the agent's operation modes.
- Workflow: Allows agent to
run within MicroTx Workflows, such as
through an Agentic Task, while a workflow manages the
execution.
- Conversational: Allows agent
to run as a conversational agent in free-form chat interactions
through the conversation API.
- LLM Profile: Select an LLM profile that powers the
agent's reasoning and language tasks.
Note:
Agentic task does not support Cohere models.
-
Use Memory: Optional. This setting applies only to
conversational capability and it does not change behavior for
workflow or agentic task execution. It controls whether a
conversational agent uses prior chat context, including recent
messages and summary, to answer new prompts in the same chat
session. When enabled, the agent keeps contextual continuity across
turns, so responses can reference earlier parts of the conversation.
When disabled, the agent responds using only the current input and
profile instructions; prior session context is not used to generate
response. It is enabled by default.
Caution:
Disabling memory may reduce response relevance in
multi-turn conversations since earlier context is not
considered.
- Max Messages: Optional. Sets the
maximum number of chat messages kept in the agent's in-memory context
window during execution. When the limit is exceeded, older messages are
evicted and only the most recent messages are sent to the model. This
helps control token usage and cost. The default value is 20.
- Prompt Variables: If the prompt
contains any variables, add the variables and specify the values that
replace these variables at runtime.
- Guardrails - Stop Words: Define
runtime stop-word rules that filter both requests and responses. For
each stop-word rule, specify:
words: a case-insensitive list of terms or
phrases to detect or match.
scope: specify where the system applies the
rule
INPUT: scan text before sending it to
the model.
OUTPUT: scan the model's response
before returning it.
BOTH: scan both input and output.
action: specify what the system does when it
finds a match:
MASK: replace the matched text with
***.
FAIL: stop execution and raise a
guardrail violation error.
At runtime, the system evaluates all rules. It runs input
guardrails before the LLM call and output guardrails after the LLM
generates a response. It matches content using case-insensitive
string matching. If you omit or provide an invalid
scope or action, the system
does not enforce that rule. If you omit words or
set it to an empty list, the rule has nothing to match.
- Temperature: Optional. Controls randomness of the generated response. Lower
values generate more deterministic responses. Higher values generate more varied
responses. The default value is 0.2.
- Max Tokens: Optional. Sets the maximum number of tokens that the model
can generate. The default value is 1024. Optional. Sets the maximum number of tokens the model can generate in
a response. The default value is 1024.
- Top K: Optional. Number of highest-probability tokens considered during
generation. The default value is 40.
- Top P: Optional. Controls nucleus sampling value. The default value is
0.9.
- Max Tool Calls: Optional. Limits the number of
tool invocations per session. This prevents runaway invocation loops and
constrains execution cost and side effects. The default value is
10.
- MCP Servers: Optional. Select one or more Model
Context Protocol (MCP) servers that the agent can access and use for
executing tasks or accessing resources.
- Tools: Optional. Select one or more tool
configurations that you have created previously in MicroTx Workflows. The agent accesses and
invokes the specified tools during workflow execution.
- Click Submit.
Your new definition appears in the list of available agent profile
definitions. You can invoke the agent profile by name in workflows or tasks.
Example
The following JSON code provides sample values for parameters of an
agent profile.
{
"name": "orderProcessorAgent",
"description": "Handles order-related workflow and chat queries",
"role": "Process and respond to all order fulfillment workflow tasks",
"instruction": "Always validate input, check inventory before approving order, escalate exceptions",
"llmProfile": {
"model": "gpt-4",
"vendor": "OpenAI"
},
"tools": [
"OrderDBLookupTool",
"EmailSender"
],
"mcpServers": [
"inventoryMCP",
"shippingMCP"
],
"memory": true,
"maxMessages": 30,
"maxToolCalls": 5,
"capabilities": [
"WORKFLOW",
"CONVERSATIONAL"
],
"promptVariables": {
"companyBrand": "MicroTx",
"region": "APAC"
},
"temperature": 0.5,
"maxTokens": 2048,
"topK": 50,
"topP": 0.9,
"maxCompletionTokens": 512,
"guardrails": {
"stopWords": [
{
"words": [
"password"
],
"scope": "INPUT",
"action": "MASK"
}
]
}
}