iris-eval

Evaluate AI agent output quality, safety, and cost using the Iris MCP server. Use when building, testing, or shipping agents and the user wants to score output quality, detect PII or prompt injection, verify citations, track cost per query, enforce cost budgets, add tracing/observability to an agent, or set up eval-driven development. Also use when the user asks "is my agent good enough to ship" or wants quality gates on agent responses.

Evaluate AI agent outputs for quality, safety, and cost using the Iris MCP server. Use when reviewing agent responses, checking for PII leaks, scoring output quality, or tracking execution costs.