Quality Assurance & Testing
AI Agent Reliability
Make an AI agent or automation reliable enough to trust — the tests, checks, and guardrails that catch its failures before they reach anything real. Use when asked how do I test my AI agent, make my automation reliable, my agent works sometimes, or how do I trust an AI workflow in production. Produces a map of where the agent can fail (bad input, hallucination, wrong tool call, edge cases, silent errors), the checks that catch each (validation, evals on real cases, human-in-the-loop gates, monitoring), a right-sized reliability plan scaled to the stakes, and a rollout that earns trust incrementally.
- Publisher / source
- mohitagw15856/pm-claude-skills (found on the CSV list)
- Upstream record
- mohitagw15856/pm-claude-skills
- Version
- Version 2
- Published
- Publication review
- Approved for publication · recorded passed scan 2026-11-02
- Content fingerprint
95f1ee6004ea3d384a875f183dd167fe0ccc708bccfb69dcc1cd44a30c219f90