Testing and Evals for Claude Code Threat Agents
Build an eval loop for a Claude Code threat-detection agent: labeled cases, deterministic plus LLM-judge scoring, and CI gates that block regressions.
Browse older CallSphere articles on AI voice agents, contact center automation, and conversational AI.
From the blog
Build an eval loop for a Claude Code threat-detection agent: labeled cases, deterministic plus LLM-judge scoring, and CI gates that block regressions.
Sandboxing, least privilege, secrets handling, and prompt-injection defense for a Claude Code threat-detection agent that reads adversary-controlled data.
Caching, batching, model cascades, and per-run budgets that keep a Claude Code threat-detection agent fast and cheap without losing investigation quality.
Fix the common Claude Code agent failures — loops, wrong tool calls, hallucinated args — in a threat-detection build, with hooks, validation, and replay.
What to put in context and what to leave out for a Claude Code threat-detection agent, and why it decides accuracy.
Wire tools and MCP servers into a Claude Code threat-detection agent: auth, schemas, error handling, idempotency.
Code-level patterns for prompts, tools, and context in a Claude Code threat-detection agent that stays reliable.
Step-by-step walkthrough to build a threat-detection triage agent on Claude Code, from ingestion to a working loop.
End-to-end architecture of a Claude Code threat-detection platform: ingestion, triage agents, MCP tools, and human review.
Get notified when we publish new articles on AI voice agents, automation, and industry insights. No spam, unsubscribe anytime.
Try our live demo -- no signup required. Talk to an AI voice agent right now.