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fluxloop-scenario

Create and refine test scenarios, agent contracts, and wrapper configurations.

9|Updated Sep 26, 2025
Search Tags:#testing#scenario#contract#wrapper#agent setup#fluxloop
One-click install
npx skills add https://github.com/Fluxloop-AI/fluxloop --skill fluxloop-scenario
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: fluxloop-scenario
Source: https://github.com/Fluxloop-AI/fluxloop/tree/main/fluxloop-plugin/skills/scenario
Command: npx skills add https://github.com/Fluxloop-AI/fluxloop --skill fluxloop-scenario

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill streamlines the creation of test scenarios, agent contracts, and wrapper setups, ensuring your AI agents are thoroughly tested against defined objectives.

Core Features & Use Cases

  • Scenario Initialization: Define and name new test scenarios for your agents.
  • Contract Generation: Automatically create and refine behavioral contracts for agent testing.
  • Wrapper Setup: Configure necessary Python wrappers for stateful or dependency-heavy agents.
  • Use Case: When developing a new customer support chatbot, use this Skill to set up a scenario for handling refund requests, define the expected agent behavior (contract), and configure any necessary code wrappers.

Quick Start

Use the fluxloop scenario skill to create a new test scenario named 'order-cancellation'.

Frequently Asked Questions about fluxloop-scenario

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create test scenarios for AI agents?▼

To create test scenarios for AI agents, initialize and name a new scenario, load agent context, and generate behavioral contracts to define and refine expected testing outcomes.

What is an agent contract in AI testing?▼

An agent contract in AI testing is a defined behavioral agreement generated to ensure your AI agent acts according to specific objectives and expected responses during scenario execution.

How do I set up Python wrappers for stateful AI agents?▼

You set up Python wrappers for stateful AI agents by configuring wrapper setups during scenario initialization, ensuring dependency-heavy agents maintain state correctly throughout test execution.

Does fluxloop-scenario support local persistence for test strategies?▼

Yes, fluxloop-scenario supports local persistence, allowing you to save generated test scenarios, agent contracts, and wrapper configurations locally for future refinement and continuous testing.

When do I need to generate behavioral contracts for agent testing?▼

You need to generate behavioral contracts when developing AI agents like chatbots, ensuring the agent is thoroughly tested against defined objectives such as handling refund requests or order cancellations.

Can I analyze agent profiles when designing test scenarios?▼

Yes, you can analyze agent profiles and load context during scenario design, enabling informed test scenario creation and precise contract generation tailored to the specific agent setup.

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