EvalKit
A lightweight evaluation framework for LLM and agentic workflows.
System flow
How the pieces move.
- Cases Version prompts and scenarios.
- Run Exercise the workflow.
- Score Classify quality and failures.
- Review Make release decisions with evidence.
Problem Statement
Teams need a repeatable way to catch regressions, classify failures, and understand whether prompt, model, or tool changes improved behavior.
Architecture Summary
Scenario suites feed versioned prompts and workflows into evaluators, producing scorecards, failure labels, trace links, and release notes.
Key Design Tradeoffs
- Keeps evaluation lightweight enough for teams to adopt before a heavier platform exists.
- Prioritizes workflow regression and failure taxonomy over broad benchmark coverage.
- Makes traces reviewable by humans instead of hiding judgment inside a single score.
Technologies
TypeScriptMDXOpenTelemetryPostgreSQL
EvalKit is designed as a pragmatic evaluation layer for teams moving from prompt experiments to governed workflow releases.
The system emphasizes regression testing, failure classification, prompt and workflow versioning, and scorecards that are easy for product, engineering, and risk teams to discuss together.