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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)
npx skills add https://github.com/github/awesome-copilot --skill arize-link

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Listed on Skillselion
Installs1k
repo stars37.1k
Security audit3 / 3 scanners passed
Last updatedJuly 28, 2026
Repositorygithub/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

SKILL.mdMarkdownGitHub ↗

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 requiredResource-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: 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

ProblemSolution
"No data" / empty viewTrace outside time window — widen startA/endA (±1h → ±1d → 90d).
404ID wrong or not base64. Re-check org_id, space_id, project_id from the browser URL.
Span not highlightedspan_id may belong to a different trace. Verify against exported span data.
org_id unknownax 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, and start_time.

Examples

See references/EXAMPLES.md for a complete set of concrete URLs for every link type.

Related 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.

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