Quick Start
Make sure you have the AX CLI installed before getting started.Option 1: npx (recommended)
Option 2: git clone
- macOS / Linux
- Windows (PowerShell)
ax CLI. Use --global / -Global instead to install to ~/.<agent>/skills/.
Installer flags
- Bash (install.sh)
- PowerShell (install.ps1)
| Flag | Description |
|---|---|
--project <dir> | Target project directory for skill symlinks |
--global | Install to ~/.<agent>/skills/ instead (alternative to --project) |
--copy | Copy files instead of symlinking |
--force | Overwrite existing skills |
--skip-cli | Don’t install ax CLI even if missing |
--agent <name> | Manually specify agent (cursor, claude, codex) — repeatable |
--skill <name> | Only install/uninstall specific skills — repeatable |
--yes | Skip confirmation prompts |
--uninstall | Remove previously installed skill symlinks |
--list | List all available skills and exit |
Why Skills for Agents?
Agents (in Cursor, Claude Code, and similar environments) need to know when to use Arize and how to use it. Skills encode that knowledge:- When to invoke: Each skill has a clear description and trigger phrases (e.g., “creating or managing Arize datasets”, “downloading traces”, “running experiments”).
- How to use AX: Skills document the
axCLI commands, concepts (datasets, experiments, traces, spans), and prerequisites (API key, space ID, project).
Available Arize Skills
The arize-skills repository provides skills that agents can load and use:| Skill | Description |
|---|---|
| arize-instrumentation | Set up and configure tracing and instrumentation for applications (e.g., OpenTelemetry, Arize AX tracer registration, framework-specific instrumentors). |
| arize-link | Generate deep links to traces, spans, and sessions in the Arize UI. |
| arize-dataset | Create, list, get, update, or delete datasets; append examples; export dataset data; create datasets from files. |
| arize-experiment | Create experiments, list runs, export experiment results, compare runs, and run evaluation workflows. |
| arize-trace | Export traces and spans by trace ID, span ID, or session ID; debug LLM applications using trace data. |
| arize-prompt-optimization | Optimize or debug LLM prompts using production trace data, evaluations, and annotations; extract prompts from spans and run data-driven optimization. |
ax commands and flags to use, so the agent can interface with Arize AX without guessing.
How Agents Use Skills
- Install or load skills in the agent environment using one of the Quick Start methods above.
- User asks in natural language (e.g., “Create a dataset for my eval”, “Export traces for session X”, “Run an experiment on this dataset”).
- Agent matches the request to a skill’s description and triggers.
- Agent follows the skill’s instructions: check prerequisites (
ax --version, API key, space ID, project), then run the documentedaxcommands with the right flags and output handling.
Prerequisites for Using Skills
Agents using Arize skills need the same setup as a human using the CLI:- AX CLI installed:
- API key — set up with a profile (
ax profiles create) or via theARIZE_API_KEYenvironment variable. Get your key from Arize app → API Keys. - Space ID (from the Arize URL:
/spaces/{SPACE_ID}/...) and project name as used in the Arize UI.
ax profiles show, ax projects list) and when to ask the user for missing values. See AX CLI overview for full CLI setup.
Updating Skills
- npx path:
npx skills update - git clone path:
cd arize-skills && git pull(symlinks update automatically)
Related Resources
- Arize AX for Agents — Observability, evaluations, and testing for agent applications.
- AX CLI overview — Install, configure, and use the
axCLI. - Arize-ai/arize-skills — Official Arize skills repository for agents (includes arize-instrumentation, arize-link, and other skills).