Iris v0.4.0 ships today. It's the release where protocol-native eval crosses from "deterministic rules" into "semantic scoring" — without giving up any of what made the deterministic layer work.

Three headline features plus a lot of infrastructure work that quietly compounds. I'll go through each, why it matters, and how it fits the thesis.

1 — LLM-as-Judge, as a real MCP tool

Heuristic rules catch a lot: length, keyword overlap, PII patterns, prompt-injection signatures, hallucination markers. They don't catch semantic quality. "Did the output actually answer the user's question?" is not a regex.

v0.4.0 adds a dedicated tool for that: evaluate_with_llm_judge .

Five templates — accuracy (hallucination detection), helpfulness (does it address the ask), safety (harm potential beyond regex PII), correctness (vs a reference answer), faithfulness (RAG grounding vs provided sources).…