AgentTalk Tester

AI Agent Multi-turn Conversation Testing Tool

Test Scripts

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Create a new test script or select an existing one

Scripted Testing

Define multi-turn conversation flows

Multi-dimensional Validation

Keywords, semantics, context checks

Regression Testing

Ensure consistency across updates

Export Reports

JSON format for CI/CD integration

Why AgentTalk Tester Is Worth Using

Test AI agents in multi-turn conversations with scripted scenarios. Validate keywords, semantics, and context consistency. Free. This page is built for people who want a fast path to a working result, not a vague prompt-and-pray workflow. If you need a more reliable first draft, cleaner output, or a repeatable workflow you can hand to a teammate, AgentTalk Tester is designed to shorten that path.

Most visitors use AgentTalk Tester because they need something specific done now: a deliverable, a decision, or a workflow checkpoint. The sections below show the fastest way to get value from the tool and the adjacent pages that help you keep going.

How to Use AgentTalk Tester

Create test scripts to validate your AI agent's multi-turn conversation behavior.

  1. 1Configure your API key (OpenAI or Anthropic)
  2. 2Create a test script with conversation turns
  3. 3Add validation rules (keywords, semantics)
  4. 4Run the test and view results
  5. 5Export reports for CI/CD integration

Who Is AgentTalk Tester For?

For AI developers who need to test multi-turn conversation flows.

AI Agent Developers

Test conversation consistency and goal achievement

QA Engineers

Automate regression testing for AI systems

AI Product Teams

Ensure quality before deployment

What a Good Result Looks Like

A strong outcome from AgentTalk Tester is not just “some output.” It should be usable with minimal cleanup, aligned to the task you opened the page for, and specific enough that you can paste it into the next step of your workflow without rewriting everything from scratch.

If the first pass feels too generic, use the use cases, FAQs, and related pages here to tighten the scope. That usually produces better results faster than starting over in a blank chat.

Frequently Asked Questions

What validation types are supported?
Keyword checking (response contains specific words), semantic matching (response aligns with expected intent), and context consistency (agent remembers previous turns).
Which AI models are supported?
OpenAI GPT-4o, Anthropic Claude, and custom HTTP endpoints for your own AI agents.
Can I use this in CI/CD?
Yes, export test reports as JSON for integration with GitHub Actions, Jenkins, or other CI tools.

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