Create mock LLM responses and tool call sequences for @copilotkit/aimock testing.
npx skills add https://github.com/CopilotKit/aimock --skill write-fixtures
Please help me install this Agent Skill. Skill: write-fixtures Source: https://github.com/CopilotKit/aimock/tree/main/skills/write-fixtures Command: npx skills add https://github.com/CopilotKit/aimock --skill write-fixtures
This Skill helps users write test fixtures for @copilotkit/aimock, enabling the creation of mock LLM responses, tool call sequences, and more for testing AI applications.
Use the write-fixtures skill to generate a mock response for the user message 'hello' with a placeholder content 'Hello there!'.
High-intent search queries and answers about installing and using this skill.
Mock data for language model testing is created by defining test fixtures that simulate LLM responses, tool call sequences, and embeddings. This enables testing AI applications with @copilotkit/aimock without live API calls.
Simulating multi-turn agent loops in AI testing requires building test fixtures that handle sequential conversations between agents. You define these multi-turn structures to validate complex conversational workflows.
Yes, you can inject intentional errors into mock LLM responses for chaos testing. The skill supports error injection into test data, allowing you to evaluate how your AI application handles unexpected failures.
@copilotkit/aimock supports mocking embeddings and structured outputs for AI tools. You can create test fixtures that generate mock embeddings and structured data to verify compatibility with various AI tools.
To test complex tool call sequences without a live language model, you create mock data fixtures that define the exact tool call sequences. This allows you to test complex workflows locally and deterministically.
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