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.
npx skills add Ghosteken/agent-harness --skill azure-ai-projects-pygit clone --depth 1 https://github.com/Ghosteken/agent-harnessWrote 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.
[](https://agentmods.dev/skills/ghosteken/agent-harness/azure-ai-projects-py)<a href="https://agentmods.dev/skills/ghosteken/agent-harness/azure-ai-projects-py"><img src="https://agentmods.dev/badge/skills/ghosteken/agent-harness/azure-ai-projects-py/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.
<a href="https://agentmods.dev/skills/ghosteken/agent-harness/azure-ai-projects-py"><img src="https://agentmods.dev/badge/skills/ghosteken/agent-harness/azure-ai-projects-py.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00022 | $0.01975 |
| Opus 5.5 | $0.00009 | $0.00790 |
| Sonnet 5.5 | $0.00004 | $0.00395 |
| Haiku 4.5 | $0.00002 | $0.00198 |
Grade A, and why
azure-ai-projects-py 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 1mo 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.
This is a copy
73% identical to azure-ai-projects-py — 9 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.
How it starts
The opening of the file, as written. The whole thing — 306 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Azure AI Projects Python SDK (Foundry SDK)
Build AI applications on Microsoft Foundry using the azure-ai-projects SDK.
Installation
pip install azure-ai-projects azure-identity
Environment Variables
AZURE_AI_PROJECT_ENDPOINT="https://<resource>.services.ai.azure.com/api/projects/<project>"
AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-4o-mini"
Authentication
import os
from azure.identity import DefaultAzureCredential
from azure.ai.projects import AIProjectClient
credential = DefaultAzureCredential()
client = AIProjectClient(
endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
credential=credential,
)
Client Operations Overview
| Operation | Access | Purpose |
|---|---|---|
client.agents |
.agents.* |
Agent CRUD, versions, threads, runs |
client.connections |
.connections.* |
List/get project connections |
client.deployments |
.deployments.* |
List model deployments |
client.datasets |
.datasets.* |
Dataset management |
client.indexes |
.indexes.* |
Index management |
client.evaluations |
.evaluations.* |
Run evaluations |
client.red_teams |
.red_teams.* |
Red team operations |
Two Client Approaches
1. AIProjectClient (Native Foundry)
from azure.ai.projects import AIProjectClient
client = AIProjectClient(
endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
credential=DefaultAzureCredential(),
)
# Use Foundry-native operations
agent = client.agents.create_agent(
model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
name="my-agent",
instructions="You are helpful.",
)
2. OpenAI-Compatible Client
# Get OpenAI-compatible client from project
openai_client = client.get_openai_client()
# Use standard OpenAI API
response = openai_client.chat.completions.create(
model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
messages=[{"role": "user", "content": "Hello!"}],
)
Agent Operations
Create Agent (Basic)
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.
- 1mo ago First seen · 306 lines · 22 tokens per session scan A abb2092f89d4
azure-ai-projects-py is a skill published in the GitHub repository Ghosteken/agent-harness (4 stars, last pushed yesterday), licensed MIT. It adds 22 tokens to every session and 1,975 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 73% identical to azure-ai-projects-py, differing in 9 lines, and is treated as a copy.
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