Creates direct URLs to specific Arize observability resources using encoded IDs.
Install
mkdir -p .claude/skills/arize-link && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/17926" && unzip -o skill.zip -d .claude/skills/arize-link && rm skill.zipInstalls to .claude/skills/arize-link
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Generate deep links to the Arize UI. Use when the user wants a clickable URL to open a specific trace, span, session, dataset, labeling queue, evaluator, or annotation config.Key capabilities
- →Generate deep links to the Arize UI for traces
- →Generate deep links to the Arize UI for spans
- →Generate deep links to the Arize UI for sessions
- →Generate deep links to the Arize UI for datasets
- →Generate deep links to the Arize UI for labeling queues
- →Generate deep links to the Arize UI for evaluators
How it works
The skill constructs Arize UI deep links by substituting provided base64-encoded IDs and time ranges into predefined URL templates for various resource types.
Inputs & outputs
When to use arize-link
- →Link to a specific trace in Arize
- →Open a dataset labeling queue
- →View a specific session or span
- →Jump to evaluator configurations
About this skill
Arize Link
Generate deep links to the Arize UI for traces, spans, sessions, datasets, labeling queues, evaluators, and annotation configs.
When to Use
- User wants a link to a 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 or context (exported trace data, parsed URLs):
| 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 | |
queue_id — specific queue (omit for list) | |
evaluator_id [+ version] — evaluator |
All path IDs must be base64-encoded (characters: A-Za-z0-9+/=). A raw numeric ID produces a valid-looking URL that 404s. If the user provides a number, ask them to copy the ID directly from their Arize browser URL (https://app.arize.com/organizations/{org_id}/spaces/{space_id}/…). If you have a raw internal ID (e.g. Organization:1:abC1), base64-encode it before inserting into the URL.
URL Templates
Base URL: https://app.arize.com (override for on-prem)
Trace (add &selectedSpanId={span_id} to highlight a specific span):
{base_url}/organizations/{org_id}/spaces/{space_id}/projects/{project_id}?selectedTraceId={trace_id}&queryFilterA=&selectedTab=llmTracing&timeZoneA=America%2FLos_Angeles&startA={start_ms}&endA={end_ms}&envA=tracing&modelType=generative_llm
Session:
{base_url}/organizations/{org_id}/spaces/{space_id}/projects/{project_id}?selectedSessionId={session_id}&queryFilterA=&selectedTab=llmTracing&timeZoneA=America%2FLos_Angeles&startA={start_ms}&endA={end_ms}&envA=tracing&modelType=generative_llm
Dataset (selectedTab: examples or experiments):
{base_url}/organizations/{org_id}/spaces/{space_id}/datasets/{dataset_id}?selectedTab=examples
Queue list / specific queue:
{base_url}/organizations/{org_id}/spaces/{space_id}/queues
{base_url}/organizations/{org_id}/spaces/{space_id}/queues/{queue_id}
Evaluator (omit ?version=… for latest):
{base_url}/organizations/{org_id}/spaces/{space_id}/evaluators/{evaluator_id}
{base_url}/organizations/{org_id}/spaces/{space_id}/evaluators/{evaluator_id}?version={version_url_encoded}
The version value must be URL-encoded (e.g., trailing = → %3D).
Annotation configs:
{base_url}/organizations/{org_id}/spaces/{space_id}/annotation-configs
Time Range
CRITICAL: startA and endA (epoch milliseconds) are required for trace/span/session links — omitting them defaults to the last 7 days and will show "no recent data" if the trace falls outside that window.
Priority order:
- User-provided URL — extract and reuse
startA/endAdirectly. - Span
start_time— pad ±1 day (or ±1 hour for a tighter window). - Fallback — last 90 days (
now - 90dtonow).
Prefer tight windows; 90-day windows load slowly.
Instructions
- Gather IDs from user, exported data, or URL context.
- Verify all path IDs are base64-encoded.
- Determine
startA/endAusing the priority order above. - Substitute into the appropriate template and present as a clickable markdown link.
Troubleshooting
| Problem | Solution |
|---|---|
| "No data" / empty view | Trace outside time window — widen startA/endA (±1h → ±1d → 90d). |
| 404 | ID wrong or not base64. Re-check org_id, space_id, project_id from the browser URL. |
| Span not highlighted | span_id may belong to a different trace. Verify against exported span data. |
org_id unknown | ax CLI doesn't expose it. Ask user to copy from https://app.arize.com/organizations/{org_id}/spaces/{space_id}/…. |
Related Skills
- arize-trace: Export spans to get
trace_id,span_id, andstart_time.
Examples
See references/EXAMPLES.md for a complete set of concrete URLs for every link type.
When not to use it
- →When the user provides a raw numeric ID instead of a base64-encoded ID
- →When omitting `startA` and `endA` for trace/span/session links, leading to 'no recent data'
- →When the `span_id` may belong to a different trace
Limitations
- →All path IDs must be base64-encoded
- →`startA` and `endA` are required for trace/span/session links
- →The `version` value for evaluators must be URL-encoded
How it compares
This skill specifically generates deep links for the Arize UI, allowing direct navigation to specific traces, sessions, or datasets, unlike general URL construction.
Compared to similar skills
arize-link side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| arize-link (this skill) | 0 | 2mo | No flags | Beginner |
| observability | 1 | 5mo | No flags | Advanced |
| lmt | 0 | 4mo | No flags | Beginner |
| langsmith-observability | 4 | 6mo | Review | Intermediate |
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Example prompts that trigger this skill in your AI assistant.
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