arize-link
🤖 AI Summary
This skill generates deep links to specific Arize UI pages (traces, spans, sessions, datasets, etc.) using provided IDs, enabling quick navigation from exported data or logs.
How to Install
Claude Code:
git clone --depth 1 https://github.com/github/awesome-copilot.git && cp awesome-copilot/skills/arize-link ~/.claude/skills/arize-link -r# 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:**
1. **User-provided URL** — extract and reuse `startA`/`endA` directly.
2. **Span `start_time`** — pad ±1 day (or ±1 hour for a tighter w
Details
| Category | AI/ML → ml |
| Source | github/awesome-copilot |
| SKILL.md | View on GitHub → |
| Repo Stars | ★ 35.6K |
| Est. per Skill | 712 (shared across 50 skills from this repo) |
| Difficulty | Intermediate |
| Risk Level | N/A |
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