What problem does it solve? Manually constructing Arize UI URLs is error-prone: IDs must be base64-encoded, time ranges must be set correctly, and each resource type has a different URL pattern. This Skill produces correct, clickable deep links to any Arize resource so you can share traces, datasets, and evaluators with teammates without 404s or empty views. ## Core Features & Use Cases - Deep Link Generation: Builds URLs for traces, spans, sessions, datasets, labeling queues, evaluators, and annotation configs using the correct template for each resource type. - ID and Time-Range Validation: Verifies that path IDs are base64-encoded and computes appropriate startA/endA time windows so links actually show data instead of "no recent data". - Use Case: After debugging a failing LLM trace, you have the trace_id and span_id from exported data. Use this Skill to generate a clickable Arize link with the correct time window and share it in your incident report so teammates land directly on the highlighted span. ## Quick Start Generate an Arize link to trace abc123 in my project so I can share it with my team.
