Structured Test Result Serialization For Llm Consumption

A Vitest reporter optimized for LLM parsing with structured, concise output

Unique: Purpose-built reporter that strips formatting noise and normalizes test output specifically for LLM token efficiency and parsing reliability, rather than human readability — uses compact field names, removes color codes, and orders fields predictably for consistent LLM tokenization

vs others: Unlike default Vitest reporters (verbose, ANSI-formatted) or generic JSON reporters, this reporter optimizes output structure and verbosity specifically for LLM consumption, reducing context window usage and improving parse accuracy in AI agents