arize-ai/arize-skills

arize-link

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

View source
Original skill document

Rendered from the source repository. Headings, examples, code, tables, links, and referenced images are preserved.

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 requiredResource-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

Discover organization and project IDs

Prefer the CLI over asking the user for IDs that it can provide:

bash
ax organizations list --output json

Use .organizations[].id for the organization ID. If more than one organization is returned, match the user-provided organization name or ask them to choose.

To discover a project ID, list projects in the relevant space:

bash
ax projects list --space "{space_name_or_id}" --limit 100 --output json

Use the matching project's id; its space_id supplies the space ID required in the URL. The command accepts a space name or ID; if no space is known, run ax projects list --limit 100 --output json and select the matching project.

To discover experiment IDs, list the experiments on the dataset; each has an id and a dataset_id:

bash
ax experiments list --dataset "{dataset_name_or_id}" --space "{space_name_or_id}" --output json

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)

Project:

{base_url}/organizations/{org_id}/spaces/{space_id}/projects/{project_id}

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

Experiment (repeat experimentId to compare experiments side by side):

{base_url}/organizations/{org_id}/spaces/{space_id}/datasets/{dataset_id}/experiments/compare?experimentId={experiment_id}
{base_url}/organizations/{org_id}/spaces/{space_id}/datasets/{dataset_id}/experiments/compare?experimentId={experiment_id_a}&experimentId={experiment_id_b}

Experiment with no dataset:

{base_url}/organizations/{org_id}/spaces/{space_id}/experiments/{experiment_id}

URL-encode experiment IDs (= → %3D, + → %2B, / → %2F).

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, URL context, or the CLI. Use ax organizations list --output json to obtain org_id; use ax projects list to obtain project_id when needed.
  2. Verify all path IDs are base64-encoded.
  3. Determine startA/endA using the priority order above for trace, span, and session links.
  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 with ax organizations list --output json, project_id with ax projects list, and space_id from the browser URL.
Span not highlightedspan_id may belong to a different trace. Verify against exported span data.
org_id unknownRun ax organizations list --output json and use .organizations[].id. If the CLI cannot access the organization, ask the user to copy it from their Arize browser URL.

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.

from this repository

More skills

All skills
arize-ai
Community

arize-admin

Manages Arize users, organizations, spaces, projects, roles, role bindings, resource restrictions, and API keys via the ax CLI. Use for enterprise admin workflows: inviting and offboarding users, onboarding new teams, creating custom roles for SAML/SSO mappings, assigning roles to users, restricting project-level access, and managing service keys for multi-tenant architectures. Covers ax users, ax organizations, ax spaces, ax projects, ax roles, ax role-bindings, and ax api-keys.

installs
3
GitHub stars
58
Updated
Oct 7
arize-ai
Community

arize-ai-provider-integration

Creates, reads, updates, and deletes Arize AI integrations that store LLM provider credentials used by evaluators and other Arize features. Supports any LLM provider (e.g. OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, Gemini, NVIDIA NIM, Fireworks AI, Together AI). Use when the user mentions AI integration, LLM provider credentials, create integration, list integrations, update credentials, delete integration, or connecting an LLM provider to Arize.

installs
3
GitHub stars
58
Updated
Oct 7
arize-ai
Community

arize-annotation

Creates and manages annotation configs (categorical, continuous, freeform label schemas) and annotation queues (human review workflows) on Arize. Applies human annotations to project spans via the Python SDK. Use when the user mentions annotation config, annotation queue, label schema, human feedback, bulk annotate spans, updateannotations, labeling queue, annotate record, or human review.

installs
3
GitHub stars
58
Updated
Oct 7
arize-ai
Community

arize-compliance-audit

INVOKE THIS SKILL when auditing an AI agent or LLM app for regulatory compliance. Covers EU AI Act, GPAI Code of Practice, GDPR, NIST AI RMF, Colorado AI Act, HIPAA, and ISO 42001. Scans the codebase for compliance gaps, cross-references Arize instrumentation for audit trail coverage, and produces an actionable remediation checklist tailored to the selected frameworks.

installs
3
GitHub stars
58
Updated
Oct 7