Official agent skill

Arize AI Provider Integration

by github in github/awesome-copilot

Creates, reads, updates, and deletes Arize AI integrations that store LLM provider credentials used by evaluators and other Arize features.

OfficialMITAuto-check: notes

Install Arize AI Provider Integration

skills CLI
$ npx skills add github/awesome-copilot --skill arize-ai-provider-integration -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install github/awesome-copilot arize-ai-provider-integration --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/github/awesome-copilot.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/arize-ai-provider-integration .claude/skills/arize-ai-provider-integration && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
arize-ai-provider-integration
GitHub stars
40k
Used in
1 other repo
Token cost
~2.6k tokens
SKILL.md length
875 words
Files
3 (incl. references)
Skills in repo
417
Repo updated
First seen
Licence
MIT

At a glance

Creates, reads, updates, and deletes Arize AI integrations that store LLM provider credentials used by evaluators and other Arize features.

  • The user mentions AI integration
  • SKILL.md covers Concepts, Prerequisites, List AI Integrations and Get a Specific Integration, plus 6 more sections
  • Reaches integrate.api.nvidia.com; needs OPENAI_API_KEY and ANTHROPIC_API_KEY
  • LLM provider credentials

What it does

Arize AI Provider Integration is an agent skill from github/awesome-copilot, published by the product's own GitHub organization. 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). 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.

Its SKILL.md is about 2.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/ax-profiles.md` and `references/ax-setup.md`). Compatibility notes: Requires the ax CLI and a configured Arize profile.

It works with Arize Phoenix, OpenAI, Amazon Bedrock and Azure OpenAI. The repository describes itself as: Community-contributed instructions, agents, skills, and configurations to help you make the most of GitHub Copilot. The licence is MIT.

When your agent uses it

  • The user mentions AI integration
  • LLM provider credentials
  • Create integration
  • List integrations

Example prompts

  • “/arize-ai-provider-integration”

Requirements

  • A credential in OPENAI_API_KEY
  • A credential in ANTHROPIC_API_KEY
  • Compatibility (from SKILL.md): Requires the ax CLI and a configured Arize profile.

What it can do on your machine

Read from SKILL.md and the folder at commit 727ff2e. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are bash).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • integrate.api.nvidia.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • OPENAI_API_KEY
    • ANTHROPIC_API_KEY
    • ARIZE_API_KEY
    • CURSOR_TOKEN
    • AZURE_OPENAI_API_KEY
    • GEMINI_API_KEY
    • NVIDIA_API_KEY
    • CUSTOM_LLM_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Requires the ax CLI and a configured Arize profile.

    From compatibility in the SKILL.md frontmatter.

Context cost

Arize AI Provider Integration loads about 2.6k tokens when it runs, and up to ~4.1k if it reads all its reference files. Until then it costs about 117 tokens; SKILL.md has 875 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~117
When it runs · the whole SKILL.md, loaded when a task matches
~2.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:32
    - **Security:** Never read `.env` files or search the filesystem for credentials. Use `ax profiles` for Arize credential

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from github/awesome-copilot at commit 727ff2e, republished under its MIT licence (© github). 875 words, ~2,601 tokens.

Download SKILL.mdSave it as .claude/skills/arize-ai-provider-integration/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
arize-ai-provider-integration
description
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). 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.
compatibility
Requires the ax CLI and a configured Arize profile.
metadata.author
arize
metadata.version
1.0

Arize AI Integration Skill

SPACE — Most --space flags and the ARIZE_SPACE env var accept a space name (e.g., my-workspace) or a base64 space ID (e.g., U3BhY2U6...). Find yours with ax spaces list. Note: ai-integrations create does not accept --space — AI integrations are account-scoped. Use --space only with list, get, update, and delete.

Concepts

  • AI Integration = stored LLM provider credentials registered in Arize; used by evaluators to call a judge model and by other Arize features that need to invoke an LLM on your behalf
  • Provider = the LLM service backing the integration (e.g., openAI, anthropic, awsBedrock)
  • Integration ID = a base64-encoded global identifier for an integration (e.g., TGxtSW50ZWdyYXRpb246MTI6YUJjRA==); required for evaluator creation and other downstream operations
  • Scoping = visibility rules controlling which spaces or users can use an integration
  • Auth type = how Arize authenticates with the provider: default (provider API key), proxy_with_headers (proxy via custom headers), or bearer_token (bearer token auth)

Prerequisites

Proceed directly with the task — run the ax command you need. Do NOT check versions, env vars, or profiles upfront.

If an ax command fails, troubleshoot based on the error:

  • command not found or version error → see references/ax-setup.md
  • 401 Unauthorized / missing API key → run ax profiles show to inspect the current profile. If the profile is missing or the API key is wrong, follow references/ax-profiles.md to create/update it. If the user doesn't have their key, direct them to https://app.arize.com/admin > API Keys
  • Space unknown → run ax spaces list to pick by name, or ask the user
  • LLM provider call fails (missing OPENAI_API_KEY / ANTHROPIC_API_KEY) → run ax ai-integrations list --space SPACE to check for platform-managed credentials. If none exist, ask the user to provide the key or create an integration via the arize-ai-provider-integration skill
  • Security: Never read .env files or search the filesystem for credentials. Use ax profiles for Arize credentials and ax ai-integrations for LLM provider keys. If credentials are not available through these channels, ask the user.

List AI Integrations

List all integrations accessible in a space:

bash
ax ai-integrations list --space SPACE

Filter by name (case-insensitive substring match):

bash
ax ai-integrations list --space SPACE --name "openai"

Paginate large result sets:

bash
# Get first page
ax ai-integrations list --space SPACE --limit 20 -o json

# Get next page using cursor from previous response
ax ai-integrations list --space SPACE --limit 20 --cursor CURSOR_TOKEN -o json

Key flags:

FlagDescription
--spaceSpace name or ID to filter integrations
--nameCase-insensitive substring filter on integration name
--limitMax results (1–100, default 15)
--cursorPagination token from a previous response
-o, --outputOutput format: table (default) or json

Response fields:

FieldDescription
idBase64 integration ID — copy this for downstream commands
nameHuman-readable name
providerLLM provider enum (see Supported Providers below)
has_api_keytrue if credentials are stored
model_namesAllowed model list, or null if all models are enabled
enable_default_modelsWhether default models for this provider are allowed
function_calling_enabledWhether tool/function calling is enabled
auth_typeAuthentication method: default, proxy_with_headers, or bearer_token

Get a Specific Integration

bash
ax ai-integrations get NAME_OR_ID
ax ai-integrations get NAME_OR_ID -o json
ax ai-integrations get NAME_OR_ID --space SPACE   # required when using name instead of ID

Use this to inspect an integration's full configuration or to confirm its ID after creation.


Create an AI Integration

Before creating, always list integrations first — the user may already have a suitable one:

bash
ax ai-integrations list --space SPACE

If no suitable integration exists, create one. The required flags depend on the provider.

OpenAI
bash
ax ai-integrations create \
  --name "My OpenAI Integration" \
  --provider openAI \
  --api-key $OPENAI_API_KEY
Anthropic
bash
ax ai-integrations create \
  --name "My Anthropic Integration" \
  --provider anthropic \
  --api-key $ANTHROPIC_API_KEY
Azure OpenAI
bash
ax ai-integrations create \
  --name "My Azure OpenAI Integration" \
  --provider azureOpenAI \
  --api-key $AZURE_OPENAI_API_KEY \
  --base-url "https://my-resource.openai.azure.com/"
AWS Bedrock

AWS Bedrock uses IAM role-based auth. Provide the ARN of the role Arize should assume via --provider-metadata:

bash
ax ai-integrations create \
  --name "My Bedrock Integration" \
  --provider awsBedrock \
  --provider-metadata '{"role_arn": "arn:aws:iam::123456789012:role/ArizeBedrockRole"}'
Vertex AI

Vertex AI uses GCP service account credentials. Provide the GCP project and region via --provider-metadata:

bash
ax ai-integrations create \
  --name "My Vertex AI Integration" \
  --provider vertexAI \
  --provider-metadata '{"project_id": "my-gcp-project", "location": "us-central1"}'
Show full SKILL.md (346 more words)Show less
Gemini
bash
ax ai-integrations create \
  --name "My Gemini Integration" \
  --provider gemini \
  --api-key $GEMINI_API_KEY
NVIDIA NIM
bash
ax ai-integrations create \
  --name "My NVIDIA NIM Integration" \
  --provider nvidiaNim \
  --api-key $NVIDIA_API_KEY \
  --base-url "https://integrate.api.nvidia.com/v1"
Custom (OpenAI-compatible endpoint)
bash
ax ai-integrations create \
  --name "My Custom Integration" \
  --provider custom \
  --base-url "https://my-llm-proxy.example.com/v1" \
  --api-key $CUSTOM_LLM_API_KEY
Supported Providers
ProviderRequired extra flags
openAI--api-key <key>
anthropic--api-key <key>
azureOpenAI--api-key <key>, --base-url <azure-endpoint>
awsBedrock--provider-metadata '{"role_arn": "<arn>"}'
vertexAI--provider-metadata '{"project_id": "<gcp-project>", "location": "<region>"}'
gemini--api-key <key>
nvidiaNim--api-key <key>, --base-url <nim-endpoint>
custom--base-url <endpoint>
Optional flags for any provider
FlagDescription
--model-nameAllowed model name (repeat for multiple, e.g. --model-name gpt-4o --model-name gpt-4o-mini); omit to allow all models
--enable-default-modelsEnable the provider's default model list
--function-calling-enabledEnable tool/function calling support
--auth-typeAuthentication type: default, proxy_with_headers, or bearer_token
--headersCustom headers as JSON object or file path (for proxy auth)
--provider-metadataProvider-specific metadata as JSON object or file path
After creation

Capture the returned integration ID (e.g., TGxtSW50ZWdyYXRpb246MTI6YUJjRA==) — it is needed for evaluator creation and other downstream commands. If you missed it, retrieve it:

bash
ax ai-integrations list --space SPACE -o json
# or by name/ID directly:
ax ai-integrations get NAME_OR_ID

Update an AI Integration

update is a partial update — only the flags you provide are changed. Omitted fields stay as-is.

bash
# Rename
ax ai-integrations update NAME_OR_ID --name "New Name"

# Rotate the API key
ax ai-integrations update NAME_OR_ID --api-key $OPENAI_API_KEY

# Change the model list (replaces all existing model names)
ax ai-integrations update NAME_OR_ID --model-name gpt-4o --model-name gpt-4o-mini

# Update base URL (for Azure, custom, or NIM)
ax ai-integrations update NAME_OR_ID --base-url "https://new-endpoint.example.com/v1"

Add --space SPACE when using a name instead of ID. Any flag accepted by create can be passed to update.


Delete an AI Integration

Warning: Deletion is permanent. Evaluators that reference this integration will no longer be able to run.

bash
ax ai-integrations delete NAME_OR_ID --force
ax ai-integrations delete NAME_OR_ID --space SPACE --force   # required when using name instead of ID

Omit --force to get a confirmation prompt instead of deleting immediately.


Troubleshooting

ProblemSolution
ax: command not foundSee references/ax-setup.md
401 UnauthorizedAPI key may not have access to this space. Verify key and space ID at https://app.arize.com/admin > API Keys
No profile foundRun ax profiles show --expand; set ARIZE_API_KEY env var or write ~/.arize/config.toml
Integration not foundVerify with ax ai-integrations list --space SPACE
has_api_key: false after createCredentials were not saved — re-run update with the correct --api-key or --provider-metadata
Evaluator runs fail with LLM errorsCheck integration credentials with ax ai-integrations get INT_ID; rotate the API key if needed
provider mismatchCannot change provider after creation — delete and recreate with the correct provider

  • arize-evaluator: Create LLM-as-judge evaluators that use an AI integration → use arize-evaluator
  • arize-experiment: Run experiments that use evaluators backed by an AI integration → use arize-experiment

Save Credentials for Future Use

See references/ax-profiles.md § Save Credentials for Future Use.

© github, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in skills/arize-ai-provider-integration of github/awesome-copilot.

  • SKILL.md
  • references/ax-profiles.md
  • references/ax-setup.md

Open the folder on GitHubat commit 727ff2e

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in github/awesome-copilot, which our catalogue first saw on October 7, 2026.

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Questions about Arize AI Provider Integration

What does Arize AI Provider Integration do?

Creates, reads, updates, and deletes Arize AI integrations that store LLM provider credentials used by evaluators and other Arize features. Arize AI Provider Integration is an agent skill from github/awesome-copilot, published by the product's own GitHub organization. Creates, reads, updates, and deletes Arize AI integrations that store LLM provider credentials used by evaluators and other Arize features.

When should I use Arize AI Provider Integration?

Arize AI Provider Integration fits situations like: the user mentions AI integration; LLM provider credentials; create integration; list integrations.

How do I install Arize AI Provider Integration in Claude Code?

Run `npx skills add github/awesome-copilot --skill arize-ai-provider-integration -a claude-code`. Or copy the skill folder (skills/arize-ai-provider-integration in github/awesome-copilot) into .claude/skills/arize-ai-provider-integration in your project. Claude Code loads it when a task matches its description.

How do I install Arize AI Provider Integration in Codex?

Run `npx skills add github/awesome-copilot --skill arize-ai-provider-integration -a codex`. Or copy the skill folder (skills/arize-ai-provider-integration in github/awesome-copilot) into .agents/skills/arize-ai-provider-integration in your project. Codex loads it when a task matches its description.

Can I use Arize AI Provider Integration in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add github/awesome-copilot --skill arize-ai-provider-integration -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/arize-ai-provider-integration, .gemini/skills/arize-ai-provider-integration, .github/skills/arize-ai-provider-integration and .opencode/skills/arize-ai-provider-integration in your project.

What does Arize AI Provider Integration need to run?

Going by SKILL.md and its folder, Arize AI Provider Integration needs credentials named OPENAI_API_KEY, ANTHROPIC_API_KEY, ARIZE_API_KEY and CURSOR_TOKEN. Our summary lists: A credential in OPENAI_API_KEY; A credential in ANTHROPIC_API_KEY. Compatibility (from SKILL.md): Requires the ax CLI and a configured Arize profile..

Does Arize AI Provider Integration access the network?

SKILL.md names 1 domain. In commands or code: integrate.api.nvidia.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Arize AI Provider Integration safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Arize AI Provider Integration use?

Arize AI Provider Integration is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Arize AI Provider Integration use?

About 2.6k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.5k tokens, read only when the agent opens those files.

What are the alternatives to Arize AI Provider Integration?

Skills that share tags, products or a category with Arize AI Provider Integration: Neo4j Genai Plugin Skill (neo4j-contrib/neo4j-skills, 114 stars), Add Model Price (litefuse/litefuse, 100 stars), Sap AI Core (secondsky/sap-skills, 460 stars) and Open Code Review CLI (alibaba/open-code-review, 44k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Arize AI Provider Integration?

github (a GitHub organization, an official publisher) maintains it in github/awesome-copilot, which has 39,748 GitHub stars. The repository holds 417 skills in this directory. The repository was last updated on October 7, 2026.

Source: github/awesome-copilot on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.