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Documentation Index

Fetch the complete documentation index at: https://koreai-v2-agent-platform-dev.mintlify.app/llms.txt

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Test and debug Agentic projects before deploying them to production. The platform provides interactive test sessions, execution traces, session inspection, and automated evaluation workflows to help validate agent behavior, tool execution, routing, and response quality. The platform supports the following testing capabilities:
CapabilityPurpose
Studio Test ChatInteractively test agents and workflows
Execution TracesInspect decisions, tool calls, handoffs, and state changes
Session InspectionAnalyze runtime behavior for a session
Trace AnalysisDetect slow spans, failures, and anomalies
Test Personas & ScenariosCreate repeatable conversation flows
Evaluations (Evals)Measure quality and performance using automated evaluators

Test in Studio Chat

Use the Studio test chat to validate agent behavior interactively before deploying to production. The agent responds using the same execution pipeline as production, including:
  • Tool calls and their results.
  • Flow step transitions.
  • Handoffs between agents.
  • Guardrail checks on inputs and outputs.

Start a Test Session

  1. Open your project in Studio.
  2. To test the full project, go to the Overview page and click Test your agents. For multi-agent projects, Studio defaults to the project’s entry agent (usually the supervisor).
  3. To test an individual agent in isolation, go to the Agent page and click Chat with Agent. Test Agent
  4. Or use the Chat option next to any agent on the Overview page. Test Agent
  5. Studio creates a test session. Type a message in the chat input and press Enter.
  6. Each agent response message includes metadata such as:
    • Executed flow step
    • Tool invocations
    • Response time

Debug View

The Session Debug view provides real-time visibility into agent execution during a conversation. Use it to inspect responses, trace execution flow, monitor token usage, and diagnose runtime issues. The left panel displays active and historical chat sessions. The center panel shows the live conversation between the user and the agent, including routed responses and workflow progression. The right-side diagnostics panel provides detailed runtime insights such as trace events, model usage, token consumption, session identifiers, and timeout diagnostics in real-time.
SignalWhat it meansWhat to do
High response latency on a turnA tool call is slow or the LLM loop ran multiple iterationsCheck the trace for slow tool_call spans; consider adding ON_ERROR retry limits
Unexpected handoffSupervisor routed to wrong agentReview the handoff_match trace event and refine WHEN conditions
Tool called with wrong parametersGATHER field mismatch or type errorCheck gather_extraction trace events and validate field types in ABL
Guardrail triggered unexpectedlyOutput hit a content or format boundaryReview guardrail_eval trace events and adjust guardrail thresholds
Agent asks for data already providedSession state not passed during handoffCheck PASS declarations in HANDOFF blocks

Using Traces to Debug

Use traces to inspect every decision, tool call, state update, and handoff during execution.
  1. Open your project in Studio.
  2. Navigate to Sessions and select a session.
  3. Click the Traces tab to view the full execution trace.
  4. Use filters to narrow results by event type, agent, or time range.

Trace Structure

Each session produces a hierarchical execution trace organized into spans.
Session
+-- Turn 1
|   +-- LLM Call
|   +-- Tool Call
|   |   +-- Tool Result
|   +-- Response
+-- Turn 2
|   +-- Decision
|   +-- Handoff
|   +-- Response