llm-debugger

What problem does it solve?

Diagnoses LLM output failures including hallucinations, formatting issues, and reasoning gaps, enabling root cause analysis and guided fixes.

Core Features & Use Cases

• Root-cause classification of LLM failures (hallucination, format_violation, constraint_break, reasoning_error, tool_misuse, refusals, incomplete_output)
• Prompt fixes and iterative testing to stabilize AI outputs
• Tooling improvements and test-case generation for robust AI-assisted coding tasks
• Real-world scenario: debugging a misbehaving code assistant and validating structured outputs

Quick Start

Start an interactive debugging session to identify and fix LLM output issues.