Build offline checks and model-backed evidence for an LLM agent — trajectory scoring, groundedness/citation coverage, a run-over-run token drift warning, and side-by-side prompt A/B. Use when a prompt or model change might silently regress behavior, cost, or grounding, or when "it looked fine" is your only test.
Add layered safety to an LLM agent — PII redaction, prompt-injection spotlighting, human approval on state-changing tools, and a configuration-controlled write kill-switch. Use when an agent can take consequential actions, when tool output could carry injected instructions, or when user data must be redacted before it…
Index of the AgentOps patterns for operating LLM agents in production — telemetry, guardrails, resilience, evaluation, token budgets, least privilege, and incident response — with a pointer to the full open-source course. Use when you want an overview of how the AgentOps skills fit together, or where to start…