Arize Link

If you're working with Arize's observability platform and need to share specific traces, spans, or datasets with your team, this skill generates the proper deep links. The tricky part with Arize URLs is that all the IDs need to be base64 encoded and the time ranges have to be set correctly or you'll get 404s and empty views. This handles that for you. It covers traces, spans, sessions, datasets, labeling queues, evaluators, and annotation configs. The instructions are thorough about ID encoding and time window logic, which matters because a missing startA parameter defaults to the last 7 days and will show nothing if your trace is older. Useful if you're frequently moving between exported data and the UI.

skills.sh installs: 3.2K
GitHub stars: 72
last updated: Aug 21, 2026

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Install

$ npx -y skills add arize-ai/arize-skills --skill arize-link --agent claude-code

Installs into .claude/skills of the current project.

Files

Arize Link

Generate deep links to the Arize UI for projects, traces, spans, sessions, datasets, experiments, labeling queues, evaluators, and annotation configs.

When to Use

User wants a link to a project, trace, span, session, dataset, labeling queue, evaluator, or annotation config
You have IDs from exported data or logs and need to link back to the UI
User asks to "open" or "view" any of the above in Arize

Required Inputs

Collect from the user, context (exported trace data or parsed URLs), or the ax CLI:

Always required	Resource-specific
`org_id` (base64)	`project_id` + `trace_id` [+ `span_id`] — trace/span
`space_id` (base64)	`project_id` + `session_id` — session
	`dataset_id` — dataset
	`dataset_id` + `experiment_id` (one or more) — experiment or comparison
	`experiment_id` — experiment with no dataset
	`queue_id` — specific queue (omit for list)
	`evaluator_id` [+ `version`] — evaluator