Perf FAQs

Question 1

How does Perf detect and correct AI hallucinations?

Accepted Answer

Perf uses its `perf_verify` tool, which employs multi-channel verification techniques like web search, NLI models, and cross-referencing. This method goes beyond simple LLM checks to accurately detect factual inaccuracies and suggest corrections.

Question 2

Which development clients does Perf integrate with?

Accepted Answer

Perf is designed for seamless integration with popular AI-powered coding clients. It supports Claude Code, Cursor, Windsurf, Cline, and any other MCP-compatible client, allowing for easy setup within your existing development workflow.

Question 3

Can Perf validate and fix malformed JSON from LLMs?

Accepted Answer

Yes, `perf_validate` specifically handles LLM-generated JSON. It validates the output against a provided schema and automatically repairs violations such as incorrect data types, malformed enums, missing fields, or hallucinated properties.

Question 4

How does Perf optimize the use of different LLM models?

Accepted Answer

Perf's `perf_chat` feature intelligently routes your LLM requests to the most optimal model (e.g., GPT-4o, Claude, Gemini, or 20+ others) based on the task's complexity, helping you achieve better results efficiently.

Question 5

What is Perf and how does it improve AI outputs?

Accepted Answer

Perf is a developer tool that fact-checks and fixes AI outputs before they reach users. It detects hallucinations, repairs broken JSON, corrects various error types, and optimizes LLM routing, ensuring higher quality and more reliable generative AI responses.

Perf

Perf

Key Features

Use Cases

Key Features

Use Cases