Designed as a production-grade Python skill, this tool provides deterministic evaluation for multi-model prompt regressions and golden datasets. It integrates seamlessly into autonomous AI agents, multi-agent frameworks such as Claude Desktop, Cursor, AutoGPT, and CrewAI, and enterprise AI pipelines. Emphasizing zero external dependencies and native Model Context Protocol (MCP) support, it ensures high portability, instantaneous operation, and reliable performance for critical AI evaluation tasks.
Key Features
01Zero external `pip` dependencies, running instantly on standard Python 3.9+.
02Native Model Context Protocol (MCP) compatibility for seamless integration with AI clients.
03Deterministic and reliable with 100% predictable input/output contracts and JSON Schema validation.
048 GitHub stars
05Low latency, sub-millisecond execution overhead tailored for high-concurrency production agents.
Use Cases
01Integrating with multi-agent frameworks such as Claude Desktop, Cursor, and CrewAI.
02Deploying in enterprise AI pipelines for robust prompt and model evaluation.
03Evaluating prompt regressions and golden datasets within autonomous AI agents.
