Official agent skill

Azure AI Projects TS

by microsoft in microsoft/skills

Build AI applications using Azure AI Projects SDK for JavaScript (@azure/ai-projects).

OfficialMITAuto-check passedDevOps & Cloud

Install Azure AI Projects TS

skills CLI
$ npx skills add microsoft/skills --skill azure-ai-projects-ts -a claude-code

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

GitHub CLI
$ gh skill install microsoft/skills azure-ai-projects-ts --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/microsoft/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.github/plugins/azure-sdk-typescript/skills/azure-ai-projects-ts .claude/skills/azure-ai-projects-ts && 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
azure-ai-projects-ts
GitHub stars
3.1k
Used in
5 other repos
Token cost
~1.9k tokens
SKILL.md length
131 words
Files
3 (incl. references)
Skills in repo
150
Repo updated
First seen
Licence
MIT

At a glance

Build AI applications using Azure AI Projects SDK for JavaScript (@azure/ai-projects).

  • Works in 5 steps: Use getOpenAIClient() - For responses,… → Version your agents - Use createVersion… → Clean up resources - Delete agents,… → …
  • Working with Foundry project clients
  • SKILL.md covers Installation, Environment Variables, Authentication and Operation Groups, plus 8 more sections
  • Calls npm; reaches learn.microsoft.com; needs AZURE_TOKEN_CREDENTIALS

What it does

Azure AI Projects TS is an agent skill from microsoft/skills, published by the product's own GitHub organization. Build AI applications using Azure AI Projects SDK for JavaScript (@azure/ai-projects). Use when working with Foundry project clients, agents, connections, deployments, datasets, indexes, evaluations, or getting OpenAI clients.

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/connections.md` and `references/evaluations.md`).

It sits in DevOps & Cloud, covering Deployment. It works with Azure AI Foundry, OpenAI, TypeScript and Microsoft Azure. The repository describes itself as: Skills, MCP servers, Custom Agents, Agents.md for SDKs to ground Coding Agents. The licence is MIT.

When your agent uses it

  • Working with Foundry project clients
  • Getting OpenAI clients

Example prompts

  • “/azure-ai-projects-ts”

Requirements

  • Node.js

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Use getOpenAIClient() - For responses, conversations, files, and vector stores
  2. Version your agents - Use createVersion for reproducible agent definitions
  3. Clean up resources - Delete agents, conversations when done
  4. Use connections - Get credentials from project connections, don't hardcode
  5. Filter deployments - Use modelPublisher filter to find specific models

What it can do on your machine

Read from SKILL.md and the folder at commit 3898ec8. 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

    Shell commands in SKILL.md call:

    • npm

    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:

    • learn.microsoft.com

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

  • Credentials

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

    • AZURE_TOKEN_CREDENTIALS

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

Context cost

Azure AI Projects TS loads about 1.9k tokens when it runs, and up to ~5.4k if it reads all its reference files. Until then it costs about 62 tokens; SKILL.md has 131 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~62
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.4k

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 passed

The automated check found no risky patterns in SKILL.md.

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 microsoft/skills at commit 3898ec8, republished under its MIT licence (© microsoft). 131 words, ~1,889 tokens.

Download SKILL.mdSave it as .claude/skills/azure-ai-projects-ts/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
azure-ai-projects-ts
description
Build AI applications using Azure AI Projects SDK for JavaScript (@azure/ai-projects). Use when working with Foundry project clients, agents, connections, deployments, datasets, indexes, evaluations, or getting OpenAI clients.
license
MIT
metadata.author
Microsoft
metadata.version
1.0.0
metadata.package
@azure/ai-projects

Azure AI Projects SDK for TypeScript

High-level SDK for Azure AI Foundry projects with agents, connections, deployments, and evaluations.

Installation

bash
npm install @azure/ai-projects @azure/identity

For tracing:

bash
npm install @azure/monitor-opentelemetry @opentelemetry/api

Environment Variables

bash
AZURE_AI_PROJECT_ENDPOINT=https://<resource>.services.ai.azure.com/api/projects/<project>
MODEL_DEPLOYMENT_NAME=gpt-4o
AZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production

Authentication

typescript
import { AIProjectClient } from "@azure/ai-projects";
import { DefaultAzureCredential, ManagedIdentityCredential } from "@azure/identity";

// Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>
const credential = new DefaultAzureCredential({requiredEnvVars: ["AZURE_TOKEN_CREDENTIALS"]});
// Or use a specific credential directly in production:
// See https://learn.microsoft.com/javascript/api/overview/azure/identity-readme?view=azure-node-latest#credential-classes
// const credential = new ManagedIdentityCredential();

const client = new AIProjectClient(
  process.env.AZURE_AI_PROJECT_ENDPOINT!,
  credential
);

Operation Groups

GroupPurpose
client.agentsCreate and manage AI agents
client.connectionsList connected Azure resources
client.deploymentsList model deployments
client.datasetsUpload and manage datasets
client.indexesCreate and manage search indexes
client.evaluatorsManage evaluation metrics
client.memoryStoresManage agent memory

Getting OpenAI Client

typescript
const openAIClient = await client.getOpenAIClient();

// Use for responses
const response = await openAIClient.responses.create({
  model: "gpt-4o",
  input: "What is the capital of France?"
});

// Use for conversations
const conversation = await openAIClient.conversations.create({
  items: [{ type: "message", role: "user", content: "Hello!" }]
});

Agents

Create Agent
typescript
const agent = await client.agents.createVersion("my-agent", {
  kind: "prompt",
  model: "gpt-4o",
  instructions: "You are a helpful assistant."
});
Agent with Tools
typescript
// Code Interpreter
const agent = await client.agents.createVersion("code-agent", {
  kind: "prompt",
  model: "gpt-4o",
  instructions: "You can execute code.",
  tools: [{ type: "code_interpreter", container: { type: "auto" } }]
});

// File Search
const agent = await client.agents.createVersion("search-agent", {
  kind: "prompt",
  model: "gpt-4o",
  tools: [{ type: "file_search", vector_store_ids: [vectorStoreId] }]
});

// Web Search
const agent = await client.agents.createVersion("web-agent", {
  kind: "prompt",
  model: "gpt-4o",
  tools: [{
    type: "web_search_preview",
    user_location: { type: "approximate", country: "US", city: "Seattle" }
  }]
});

// Azure AI Search
const agent = await client.agents.createVersion("aisearch-agent", {
  kind: "prompt",
  model: "gpt-4o",
  tools: [{
    type: "azure_ai_search",
    azure_ai_search: {
      indexes: [{
        project_connection_id: connectionId,
        index_name: "my-index",
        query_type: "simple"
      }]
    }
  }]
});

// Function Tool
const agent = await client.agents.createVersion("func-agent", {
  kind: "prompt",
  model: "gpt-4o",
  tools: [{
    type: "function",
    function: {
      name: "get_weather",
      description: "Get weather for a location",
      strict: true,
      parameters: {
        type: "object",
        properties: { location: { type: "string" } },
        required: ["location"]
      }
    }
  }]
});

// MCP Tool
const agent = await client.agents.createVersion("mcp-agent", {
  kind: "prompt",
  model: "gpt-4o",
  tools: [{
    type: "mcp",
    server_label: "my-mcp",
    server_url: "https://mcp-server.example.com",
    require_approval: "always"
  }]
});
Run Agent
typescript
const openAIClient = await client.getOpenAIClient();

// Create conversation
const conversation = await openAIClient.conversations.create({
  items: [{ type: "message", role: "user", content: "Hello!" }]
});

// Generate response using agent
const response = await openAIClient.responses.create(
  { conversation: conversation.id },
  { body: { agent: { name: agent.name, type: "agent_reference" } } }
);

// Cleanup
await openAIClient.conversations.delete(conversation.id);
await client.agents.deleteVersion(agent.name, agent.version);

Connections

typescript
// List all connections
for await (const conn of client.connections.list()) {
  console.log(conn.name, conn.type);
}

// Get connection by name
const conn = await client.connections.get("my-connection");

// Get connection with credentials
const connWithCreds = await client.connections.getWithCredentials("my-connection");

// Get default connection by type
const defaultAzureOpenAI = await client.connections.getDefault("AzureOpenAI", true);

Deployments

typescript
// List all deployments
for await (const deployment of client.deployments.list()) {
  if (deployment.type === "ModelDeployment") {
    console.log(deployment.name, deployment.modelName);
  }
}

// Filter by publisher
for await (const d of client.deployments.list({ modelPublisher: "OpenAI" })) {
  console.log(d.name);
}

// Get specific deployment
const deployment = await client.deployments.get("gpt-4o");

Datasets

typescript
// Upload single file
const dataset = await client.datasets.uploadFile(
  "my-dataset",
  "1.0",
  "./data/training.jsonl"
);

// Upload folder
const dataset = await client.datasets.uploadFolder(
  "my-dataset",
  "2.0",
  "./data/documents/"
);

// Get dataset
const ds = await client.datasets.get("my-dataset", "1.0");

// List versions
for await (const version of client.datasets.listVersions("my-dataset")) {
  console.log(version);
}

// Delete
await client.datasets.delete("my-dataset", "1.0");

Indexes

typescript
import { AzureAISearchIndex } from "@azure/ai-projects";

const indexConfig: AzureAISearchIndex = {
  name: "my-index",
  type: "AzureSearch",
  version: "1",
  indexName: "my-index",
  connectionName: "search-connection"
};

// Create index
const index = await client.indexes.createOrUpdate("my-index", "1", indexConfig);

// List indexes
for await (const idx of client.indexes.list()) {
  console.log(idx.name);
}

// Delete
await client.indexes.delete("my-index", "1");

Key Types

typescript
import {
  AIProjectClient,
  AIProjectClientOptionalParams,
  Connection,
  ModelDeployment,
  DatasetVersionUnion,
  AzureAISearchIndex
} from "@azure/ai-projects";

Best Practices

  1. Use getOpenAIClient() - For responses, conversations, files, and vector stores
  2. Version your agents - Use createVersion for reproducible agent definitions
  3. Clean up resources - Delete agents, conversations when done
  4. Use connections - Get credentials from project connections, don't hardcode
  5. Filter deployments - Use modelPublisher filter to find specific models

© microsoft, 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 .github/plugins/azure-sdk-typescript/skills/azure-ai-projects-ts of microsoft/skills.

  • SKILL.md
  • references/connections.md
  • references/evaluations.md

Open the folder on GitHubat commit 3898ec8

Used in 5 other repositories

We found 14 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 5 other GitHub owners. This page covers the copy in microsoft/skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Azure AI Projects TS next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Azure AI Projects TS compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Azure AI Projects TS this skillmicrosoft/skills3.1k5 repos~1.9kAutomated safety check: PassMIT
Azure Architecture Autopilotgithub/awesome-copilot40k1 repos~1.9kAutomated safety check: PassMIT
Capacitymicrosoft/GitHub-Copilot-for-Azure2551 repos~1.7kAutomated safety check: PassMIT
Deploy Modelmicrosoft/GitHub-Copilot-for-Azure2551 repos~1.8kAutomated safety check: PassMIT
Letta Configurationletta-ai/skills149—~1.3kAutomated safety check: NotesMIT
Aspire DeploymentCommunityToolkit/Aspire629—~4.5kAutomated safety check: NotesMIT

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Categories

Questions about Azure AI Projects TS

What does Azure AI Projects TS do?

Build AI applications using Azure AI Projects SDK for JavaScript (@azure/ai-projects). Azure AI Projects TS is an agent skill from microsoft/skills, published by the product's own GitHub organization. Build AI applications using Azure AI Projects SDK for JavaScript (@azure/ai-projects).

When should I use Azure AI Projects TS?

Azure AI Projects TS fits situations like: working with Foundry project clients; getting OpenAI clients.

How do I install Azure AI Projects TS in Claude Code?

Run `npx skills add microsoft/skills --skill azure-ai-projects-ts -a claude-code`. Or copy the skill folder (.github/plugins/azure-sdk-typescript/skills/azure-ai-projects-ts in microsoft/skills) into .claude/skills/azure-ai-projects-ts in your project. Claude Code loads it when a task matches its description.

How do I install Azure AI Projects TS in Codex?

Run `npx skills add microsoft/skills --skill azure-ai-projects-ts -a codex`. Or copy the skill folder (.github/plugins/azure-sdk-typescript/skills/azure-ai-projects-ts in microsoft/skills) into .agents/skills/azure-ai-projects-ts in your project. Codex loads it when a task matches its description.

Can I use Azure AI Projects TS 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 microsoft/skills --skill azure-ai-projects-ts -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/azure-ai-projects-ts, .gemini/skills/azure-ai-projects-ts, .github/skills/azure-ai-projects-ts and .opencode/skills/azure-ai-projects-ts in your project.

What does Azure AI Projects TS need to run?

Going by SKILL.md and its folder, Azure AI Projects TS needs the command-line tools its instructions call (npm) and credentials named AZURE_TOKEN_CREDENTIALS. Our summary lists: Node.js.

Does Azure AI Projects TS access the network?

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

Is Azure AI Projects TS safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Azure AI Projects TS use?

Azure AI Projects TS is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Azure AI Projects TS use?

About 1.9k tokens (SKILL.md is roughly 7.6k 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 3.6k tokens, read only when the agent opens those files.

What are the alternatives to Azure AI Projects TS?

Skills that share tags, products or a category with Azure AI Projects TS: Azure Architecture Autopilot (github/awesome-copilot, 40k stars), Capacity (microsoft/GitHub-Copilot-for-Azure, 255 stars), Deploy Model (microsoft/GitHub-Copilot-for-Azure, 255 stars) and Letta Configuration (letta-ai/skills, 149 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Azure AI Projects TS?

microsoft (a GitHub organization, an official publisher) maintains it in microsoft/skills, which has 3,094 GitHub stars. The repository holds 150 skills in this directory. The repository was last updated on October 9, 2026.

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