Arize Skills
Skills that guide AI coding agents to help you add observability, run experiments, and optimize prompts for your LLM applications.
These skills encode the workflows we've refined building the Arize platform and helping teams debug LLM apps in production. They handle the ax CLI flags, data shape quirks, and multi-step recipes so you don't have to.
Works with Cursor, Claude Code, Codex, Windsurf, and 40+ other agents.
New to Arize? Start Here
Adding tracing to your app — give your coding agent this prompt:
Follow the instructions from https://arize.com/docs/PROMPT.md and ask me questions as needed.
This walks through a two-phase flow: analyze your codebase for LLM providers and frameworks, then add Arize AX tracing with the right instrumentors. No skill installation needed.
Already have traces? Give your agent this prompt to install the skills and start debugging:
Install the Arize skills plugin from https://github.com/Arize-ai/arize-skills, then use the arize-trace skill to export and analyze recent traces from my project. Summarize any errors or latency issues you find.
Installation
Option 1: npx (recommended)
# Interactive — choose skills, agent, and scope
npx skills add Arize-ai/arize-skills
# Non-interactive — install everything with auto-detected defaults
npx skills add Arize-ai/arize-skills --skill "*" --yes
Both options auto-detect your agent (Cursor, Claude Code, Codex, etc.) and symlink skills into place.
Option 2: git clone
macOS / Linux:
git clone https://github.com/Arize-ai/arize-skills.git
cd arize-skills
./install.sh --project ~/my-project
Windows (PowerShell):
git clone https://github.com/Arize-ai/arize-skills.git
cd arize-skills
.\install.ps1 -Project ~\my-project
The installer detects installed agents and optionally installs the ax CLI. Use --global / -Global instead to install to ~/.<agent>/skills/.
Option 3: Claude Code plugin
/plugin add https://github.com/Arize-ai/arize-skills
Prerequisites
Arize CLI (ax)
The skills use the ax CLI to interact with the Arize API. Install it if you don't have it:
# Preferred (isolated environment)
uv tool install arize-ax-cli
# or
pipx install arize-ax-cli
# Fallback
pip install arize-ax-cli
Authentication
Option A — ax CLI profile (recommended):
Set up your API key once and it persists across all sessions and projects:
# Interactive wizard
ax profiles create
# Or pass the key directly
ax profiles create --api-key YOUR_API_KEY
# Update an existing profile (patches only what you specify)
ax profiles update --api-key NEW_API_KEY
ax profiles update --region us-east-1b
You'll also need a space ID. Find yours in the Arize URL (/spaces/{SPACE_ID}/...) or run ax spaces list -o json, then persist it:
# macOS/Linux — add to ~/.zshrc or ~/.bashrc
export ARIZE_SPACE_ID="U3BhY2U6..."
Option B — .env file (project-scoped credentials + provider keys):
Copy the example and fill in your keys:
cp .env.example .env
# Edit .env with your credentials
The .env file supports all credentials used by the skills:
ARIZE_API_KEY=your-api-key # from https://app.arize.com/admin > API Keys
ARIZE_SPACE_ID=U3BhY2U6... # base64 space ID from your Arize URL
# ARIZE_DEFAULT_PROJECT=my-project # optional default project
# OPENAI_API_KEY=sk-... # for AI integrations and evaluators
# ANTHROPIC_API_KEY=sk-ant-... # for AI integrations and evaluators
Skills automatically load this file during their prerequisite check. The .env file is gitignored — never commit it.
Option C — Environment variables (CI/CD):
export ARIZE_API_KEY="your-api-key" # from https://app.arize.com/admin > API Keys
export ARIZE_SPACE_ID="U3BhY2U6..." # base64 space ID from your Arize URL
Verify
ax --version && ax profiles show 2>&1
On-prem / self-hosted Arize
Point the CLI at your deployment with a single-endpoint profile (hostname and HTTPS port, usually 443). Replace the host with the value your operations team provides:
ax profiles create my-onprem --api-key <key> --single-host arize.yourcompany.com --single-port 443
ax profiles use my-onprem
ax profiles validate
For interactive setup, ax profiles create also offers Advanced → Single endpoint. More options (TOML, Flight/OTLP splits) are documented in the arize-ax-cli README.
Available Skills
Arize-ai