Evaluate and monitor LLM workflows with Agenta
Run prompt experiments, testset evaluations, and observability reviews for production LLM workflows before regressions reach users.
npx skills add agentskillexchange/skills --skill evaluate-and-monitor-llm-workflows-with-agenta
Use Agenta when an LLM workflow needs a repeatable evaluation and observability loop. The operator versions prompts and configurations, builds or imports test cases, runs human or automated evaluators, and reviews traces, cost, latency, and usage patterns before promoting changes. Invoke this instead of normal product use when a team needs to compare prompt or model changes against production-like cases and monitor the resulting workflow. The boundary is LLM evaluation, prompt review, and observability for a defined application; do not present Agenta as a generic LLMOps platform listing.
What this skill actually does
Inputs and prerequisites: Agenta, LLM application traces or test cases, model/provider credentials.
Setup notes: Use Agenta Cloud or follow the Agenta documentation for self-hosting. Create or import test cases, connect the target LLM application or prompts, run evaluations, and review observability traces before promoting a prompt or model configuration.
Source and verification boundary: use https://agenta.ai/docs/ as the canonical reference before running the workflow; keep commands, API calls, CLI usage, and generated outputs reviewable against that upstream source.
Framework fit: publish this as a Multi-Framework workflow only when the operator can invoke the documented toolchain directly, rather than treating the upstream project as a generic product listing.