azure-ai-projects-dotnet

azure-ai-projects-dotnet is a skill for Claude Code from sendralt/agentic-awesome-skills. It costs 38 tokens per session (2,528 once invoked), scanned A, a copy of azure-ai-projects-dotnet, MIT.

A .NET SDK for managing Microsoft Azure AI Foundry projects, including agents, data, model deployments, evaluations, and search indexes.

In plain words
What is it for?
Use it to create and manage AI agents, connect Azure resources, handle datasets and indexes, deploy models, and evaluate AI applications.
Why use it?
It gives .NET applications one client library for common Foundry project operations instead of requiring separate service calls.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the agentic-awesome-skills plugin — 196 skills shipped together

Good fit Use it to create and manage AI agents, connect Azure resources, handle datasets and indexes, deploy models, and evaluate AI applications.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/sendralt/agentic-awesome-skills/azure-ai-projects-dotnet
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add sendralt/agentic-awesome-skills --skill azure-ai-projects-dotnet
Clone the repo
git clone --depth 1 https://github.com/sendralt/agentic-awesome-skills

Made for: Claude Code.

Or install agentic-awesome-skills, the plugin that ships this one along with the rest of its 196 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for azure-ai-projects-dotnet

README.md
[![agentmods](https://agentmods.dev/badge/skills/sendralt/agentic-awesome-skills/azure-ai-projects-dotnet/github.svg)](https://agentmods.dev/skills/sendralt/agentic-awesome-skills/azure-ai-projects-dotnet)
Your own site
<a href="https://agentmods.dev/skills/sendralt/agentic-awesome-skills/azure-ai-projects-dotnet"><img src="https://agentmods.dev/badge/skills/sendralt/agentic-awesome-skills/azure-ai-projects-dotnet/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for azure-ai-projects-dotnet

Your own site · 80×15
<a href="https://agentmods.dev/skills/sendralt/agentic-awesome-skills/azure-ai-projects-dotnet"><img src="https://agentmods.dev/badge/skills/sendralt/agentic-awesome-skills/azure-ai-projects-dotnet.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 38 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,528 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 81% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00038 $0.02528
Opus 5 $0.00019 $0.01264
Sonnet 5 $0.00008 $0.00506
Haiku 4.5 $0.00004 $0.00253

Measured 7d ago against content hash 1d27ac94fba1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

azure-ai-projects-dotnet scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

81% identical to azure-ai-projects-dotnet — 37 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

plugins/agentic-awesome-skills-claude/skills/azure-ai-projects-dotnet/SKILL.md · 358 lines

How it starts

The opening of the file, as written. The whole thing — 358 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Azure.AI.Projects (.NET)

High-level SDK for Azure AI Foundry project operations including agents, connections, datasets, deployments, evaluations, and indexes.

Installation

dotnet add package Azure.AI.Projects
dotnet add package Azure.Identity

# Optional: For versioned agents with OpenAI extensions
dotnet add package Azure.AI.Projects.OpenAI --prerelease

# Optional: For low-level agent operations
dotnet add package Azure.AI.Agents.Persistent --prerelease

Current Versions: GA v1.1.0, Preview v1.2.0-beta.5

Environment Variables

PROJECT_ENDPOINT=https://<resource>.services.ai.azure.com/api/projects/<project>
MODEL_DEPLOYMENT_NAME=gpt-4o-mini
CONNECTION_NAME=<your-connection-name>
AI_SEARCH_CONNECTION_NAME=<ai-search-connection>

Authentication

using Azure.Identity;
using Azure.AI.Projects;

var endpoint = Environment.GetEnvironmentVariable("PROJECT_ENDPOINT");
AIProjectClient projectClient = new AIProjectClient(
    new Uri(endpoint), 
    new DefaultAzureCredential());

Client Hierarchy

AIProjectClient
├── Agents          → AIProjectAgentsOperations (versioned agents)
├── Connections     → ConnectionsClient
├── Datasets        → DatasetsClient
├── Deployments     → DeploymentsClient
├── Evaluations     → EvaluationsClient
├── Evaluators      → EvaluatorsClient
├── Indexes         → IndexesClient
├── Telemetry       → AIProjectTelemetry
├── OpenAI          → ProjectOpenAIClient (preview)
└── GetPersistentAgentsClient() → PersistentAgentsClient

Core Workflows

1. Get Persistent Agents Client

// Get low-level agents client from project client
PersistentAgentsClient agentsClient = projectClient.GetPersistentAgentsClient();

// Create agent
PersistentAgent agent = await agentsClient.Administration.CreateAgentAsync(
    model: "gpt-4o-mini",
    name: "Math Tutor",
    instructions: "You are a personal math tutor.");

// Create thread and run
PersistentAgentThread thread = await agentsClient.Threads.CreateThreadAsync();
await agentsClient.Messages.CreateMessageAsync(thread.Id, MessageRole.User, "Solve 3x + 11 = 14");
ThreadRun run = await agentsClient.Runs.CreateRunAsync(thread.Id, agent.Id);

// Poll for completion
do
{
    await Task.Delay(500);
    run = await agentsClient.Runs.GetRunAsync(thread.Id, run.Id);
}
while (run.Status == RunStatus.Queued || run.Status == RunStatus.InProgress);

// Get messages
await foreach (var msg in agentsClient.Messages.GetMessagesAsync(thread.Id))
{
    foreach (var content in msg.ContentItems)
    {
        if (content is MessageTextContent textContent)
            Console.WriteLine(textContent.Text);
    }
}

// Cleanup
await agentsClient.Threads.DeleteThreadAsync(thread.Id);
await agentsClient.Administration.DeleteAgentAsync(agent.Id);

Read the full file on GitHub · 358 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 7d ago First seen · 358 lines · 38 tokens per session scan A 1d27ac94fba1

Subscribe to this mod's changes

azure-ai-projects-dotnet is a skill published in the GitHub repository sendralt/agentic-awesome-skills (1 stars, last pushed 4d ago), licensed MIT. It adds 38 tokens to every session and 2,528 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 81% identical to azure-ai-projects-dotnet, differing in 37 lines, and is treated as a copy.

Related

Other skills, from other repositories

agent-platform-rag-engine-management

Manage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using the Google GenAI SDK. Use when listing RAG corpora or files, inspecting a corpus, retrieving contexts, or generating content grounded in a RAG corpus. Do not use for standard database queries (use SQL/Spanner skills), Google…

google/skills · 85 tokens

agent-platform-model-registry

Agent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform models.

google/skills · 60 tokens

foundry-config-setup

Resolve missing setup caused by a hardcoded Foundry project endpoint or model in a sample. Use when a sample fails because it uses a placeholder/hardcoded projectendpoint (for example "https://your-project.services.ai.azure.com") or a hardcoded model instead of reading them from the environment.

microsoft/agent-framework · 65 tokens

google-cloud-solution-agentic-analytics-spark-knowledge-catalog

Discovers requirements and generates guidance to design and deploy a governed, secure agentic-analytics solution for data that's distributed across Google Cloud, other cloud providers, or on-premises. Data that's outside Google Cloud (such as data from Databricks, Snowflake, Salesforce, SAP, or Oracle systems) is…

google/skills · 138 tokens

training-check

Interactively monitor training metrics from the current Codex session, periodically checking WandB or fallback logs for NaN, divergence, plateaus, and broken runs.

wanshuiyin/Auto-claude-code-research-in-sleep · 35 tokens

nemo-automodel-launcher-config

Configure NeMo AutoModel job launches for interactive runs, Slurm clusters, and SkyPilot cloud execution.

NVIDIA/skills · 30 tokens