
Arize Link
- 1k installs
- 37.1k repo stars
- Updated July 28, 2026
- github/awesome-copilot
This is a copy of arize-link by arize-ai - installs and ranking accrue to the original listing.
arize-link is an agent skill that generates deep links opening Arize Phoenix or Arize observability to a specific LLM trace, span, session, dataset, or labeling queue for developers who need shareable URLs during observa
About
arize-link is a reference skill from github/awesome-copilot that templates deep URLs into the Arize app for LLM tracing workflows. Placeholders cover base64-encoded org_id, space_id, and project_id plus epoch-millisecond startA and endA windows and identifiers such as selectedTraceId and selectedSpanId. Link types include full traces, highlighted spans within traces, sessions, datasets, and labeling queues with queryFilter and envA=tracing parameters. Developers use arize-link when Slack threads or tickets need a one-click path to the exact Phoenix view instead of manual UI navigation. The skill complements ax profile setup by focusing on URL construction rather than authentication repair.
- Generates ready-to-click Arize deep links for traces, spans, sessions and datasets
- Supports placeholder substitution for org_id, space_id, project_id, trace_id, span_id, session_id, dataset_id and time r
- Produces links that open directly to LLM tracing, examples tab or experiments tab
- Eliminates manual navigation through Arize UI when debugging agent runs
Arize Link by the numbers
- 1,011 all-time installs (skills.sh)
- +24 installs in the week ending Jul 28, 2026 (Skillselion tracking)
- Security screen: LOW risk (skills.sh audit)
- Data as of Jul 28, 2026 (Skillselion catalog sync)
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| Installs | 1k |
|---|---|
| repo stars | ★ 37.1k |
| Security audit | 3 / 3 scanners passed |
| Last updated | July 28, 2026 |
| Repository | github/awesome-copilot ↗ |
How do you link directly to an Arize Phoenix trace?
Quickly generate deep links that open Arize Phoenix or Arize observability directly to a specific LLM trace, span, session, dataset or labeling queue.
Who is it for?
AI engineers sharing Arize Phoenix trace, span, or session URLs in tickets and chat with correct org, space, project, and time-range placeholders filled in.
Skip if: Fixing Ax authentication failures (use arize-trace) or teams not on Arize Phoenix generative LLM tracing.
When should I use this skill?
User needs an Arize deep link, Phoenix trace URL, span highlight link, or shareable observability URL with org, space, project, and time parameters.
What you get
Shareable app.arize.com deep links targeting a specific trace, span, session, dataset, or labeling queue with encoded IDs and time filters.
- Shareable app.arize.com deep link
- Parameterized trace or span URL
Files
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_llmSession:
{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_llmDataset (selectedTab: examples or experiments):
{base_url}/organizations/{org_id}/spaces/{space_id}/datasets/{dataset_id}?selectedTab=examplesQueue 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-configsTime 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: 1. User-provided URL — extract and reuse startA/endA directly. 2. Span `start_time` — pad ±1 day (or ±1 hour for a tighter window). 3. Fallback — last 90 days (now - 90d to now).
Prefer tight windows; 90-day windows load slowly.
Instructions
1. Gather IDs from user, exported data, or URL context. 2. Verify all path IDs are base64-encoded. 3. Determine startA/endA using the priority order above. 4. 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.
Arize Link Examples
Placeholders used throughout:
{org_id}— base64-encoded org ID{space_id}— base64-encoded space ID{project_id}— base64-encoded project ID{start_ms}/{end_ms}— epoch milliseconds (e.g. 1741305600000 / 1741392000000)
---
Trace
https://app.arize.com/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_llmSpan (trace + span highlighted)
https://app.arize.com/organizations/{org_id}/spaces/{space_id}/projects/{project_id}?selectedTraceId={trace_id}&selectedSpanId={span_id}&queryFilterA=&selectedTab=llmTracing&timeZoneA=America%2FLos_Angeles&startA={start_ms}&endA={end_ms}&envA=tracing&modelType=generative_llmSession
https://app.arize.com/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_llmDataset (examples tab)
https://app.arize.com/organizations/{org_id}/spaces/{space_id}/datasets/{dataset_id}?selectedTab=examplesDataset (experiments tab)
https://app.arize.com/organizations/{org_id}/spaces/{space_id}/datasets/{dataset_id}?selectedTab=experimentsLabeling Queue list
https://app.arize.com/organizations/{org_id}/spaces/{space_id}/queuesLabeling Queue (specific)
https://app.arize.com/organizations/{org_id}/spaces/{space_id}/queues/{queue_id}Evaluator (latest version)
https://app.arize.com/organizations/{org_id}/spaces/{space_id}/evaluators/{evaluator_id}Evaluator (specific version)
https://app.arize.com/organizations/{org_id}/spaces/{space_id}/evaluators/{evaluator_id}?version={version_url_encoded}Annotation Configs
https://app.arize.com/organizations/{org_id}/spaces/{space_id}/annotation-configsRelated skills
How it compares
Use arize-link for shareable Phoenix URLs; pair with arize-trace when Ax authentication blocks trace export entirely.
FAQ
What placeholders does arize-link use in URLs?
arize-link templates use base64-encoded org_id, space_id, and project_id plus epoch-millisecond startA and endA values. Trace links add selectedTraceId, selectedTab=llmTracing, envA=tracing, and modelType=generative_llm query parameters for Phoenix.
Which Arize resources can arize-link target?
arize-link covers trace pages, individual spans highlighted within a trace, sessions, datasets, and labeling queues. Each URL pattern encodes the relevant selected IDs and time-window filters so recipients land on the exact observability view.
Is Arize Link safe to install?
skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.