Analyzing expensive users

Use this skill when the user wants to understand the most expensive users in AI observability. The job is not just to rank users by cost. The useful answer explains what makes the top users expensive: volume, model choice, prompt size, output size, cache behavior, retries/errors, trace type, feature or tenant dimensions, and representative trace examples.

For general cost rollups, also use exploring-llm-costs. For reading individual traces, also use exploring-llm-traces.

Tools