agents-v2-py

agents-v2-py is a skill for Claude Code from Ghosteken/agent-harness. It costs 39 tokens per session (2,130 once invoked), scanned A, a copy of agents-v2-py, MIT.

A Python workflow for creating hosted AI agents in Azure AI Foundry from custom container images. Azure AI Foundry is Microsoft's service for building and running AI applications.

In plain words
What is it for?
Use it when creating or deploying a container-based agent in Azure AI Foundry with the Azure AI Projects SDK.
Why use it?
It provides the setup and code pattern needed to connect a container image to Azure's hosted-agent service, including authentication and required permissions.

Skill for Claude Code

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

Part of the agent-harness plugin — 173 skills, 11 commands, 12 agents shipped together

Good fit Use it when creating or deploying a container-based agent in Azure AI Foundry with the Azure AI Projects SDK.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ghosteken/agent-harness/agents-v2-py
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 Ghosteken/agent-harness --skill agents-v2-py
Clone the repo
git clone --depth 1 https://github.com/Ghosteken/agent-harness

Made for: Claude Code.

Or install agent-harness, the plugin that ships this one along with the rest of its 173 skills, 11 commands, 12 agents.

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 agents-v2-py

README.md
[![agentmods](https://agentmods.dev/badge/skills/ghosteken/agent-harness/agents-v2-py.svg)](https://agentmods.dev/skills/ghosteken/agent-harness/agents-v2-py)
Your own site
<a href="https://agentmods.dev/skills/ghosteken/agent-harness/agents-v2-py"><img src="https://agentmods.dev/badge/skills/ghosteken/agent-harness/agents-v2-py.svg" alt="Measured on agentmods" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,130 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 97% 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 $0.00039 $0.02130
Opus 5 $0.00019 $0.01065
Sonnet 5 $0.00008 $0.00426
Haiku 4.5 $0.00004 $0.00213

Measured 7d ago against content hash 764fffdebaf0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

agents-v2-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 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

97% identical to agents-v2-py — 2 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.

archive/skills-community/agents-v2-py/SKILL.md · 332 lines

How it starts

The opening of the file, as written. The whole thing — 332 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Azure AI Hosted Agents (Python)

Build container-based hosted agents using ImageBasedHostedAgentDefinition from the Azure AI Projects SDK.

Installation

pip install azure-ai-projects>=2.0.0b3 azure-identity

Minimum SDK Version: 2.0.0b3 or later required for hosted agent support.

Environment Variables

AZURE_AI_PROJECT_ENDPOINT=https://<resource>.services.ai.azure.com/api/projects/<project>

Prerequisites

Before creating hosted agents:

  1. Container Image - Build and push to Azure Container Registry (ACR)
  2. ACR Pull Permissions - Grant your project's managed identity AcrPull role on the ACR
  3. Capability Host - Account-level capability host with enablePublicHostingEnvironment=true
  4. SDK Version - Ensure azure-ai-projects>=2.0.0b3

Authentication

Always use DefaultAzureCredential:

from azure.identity import DefaultAzureCredential
from azure.ai.projects import AIProjectClient

credential = DefaultAzureCredential()
client = AIProjectClient(
    endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
    credential=credential
)

Core Workflow

1. Imports

import os
from azure.identity import DefaultAzureCredential
from azure.ai.projects import AIProjectClient
from azure.ai.projects.models import (
    ImageBasedHostedAgentDefinition,
    ProtocolVersionRecord,
    AgentProtocol,
)

2. Create Hosted Agent

client = AIProjectClient(
    endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
    credential=DefaultAzureCredential()
)

agent = client.agents.create_version(
    agent_name="my-hosted-agent",
    definition=ImageBasedHostedAgentDefinition(
        container_protocol_versions=[
            ProtocolVersionRecord(protocol=AgentProtocol.RESPONSES, version="v1")
        ],
        cpu="1",
        memory="2Gi",
        image="myregistry.azurecr.io/my-agent:latest",
        tools=[{"type": "code_interpreter"}],
        environment_variables={
            "AZURE_AI_PROJECT_ENDPOINT": os.environ["AZURE_AI_PROJECT_ENDPOINT"],
            "MODEL_NAME": "gpt-4o-mini"
        }
    )
)

print(f"Created agent: {agent.name} (version: {agent.version})")

Read the full file on GitHub · 332 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 · 332 lines · 39 tokens per session scan A 764fffdebaf0

Subscribe to this mod's changes

agents-v2-py is a skill published in the GitHub repository Ghosteken/agent-harness (2 stars, last pushed 2d ago), licensed MIT. It adds 39 tokens to every session and 2,130 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 97% identical to agents-v2-py, differing in 2 lines, and is treated as a copy.

Related

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