foundry-config-setup

A setup fix for sample programs that use placeholder Foundry project endpoints or hardcoded model names. Foundry is Microsoft's service for building and running AI applications.

In plain words
What is it for?
Use it when fixing FoundryChatClient examples: read FOUNDRY_PROJECT_ENDPOINT and FOUNDRY_MODEL from environment variables and keep the provided Azure authentication.
Why use it?
It lets samples use the real project and model settings supplied through the environment instead of failing with invalid placeholder values.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/microsoft/agent-framework/foundry-config-setup
Any agent
npx skills add microsoft/agent-framework --skill foundry-config-setup
Clone the repo
git clone --depth 1 https://github.com/microsoft/agent-framework

Made for: Claude Code, Codex.

Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 430 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found 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 $0.00065 $0.00430
Opus 5 $0.00032 $0.00215
Sonnet 5 $0.00013 $0.00086
Haiku 4.5 $0.00006 $0.00043

Measured yesterday against content hash 72279cefeddb, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

foundry-config-setup 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 yesterday.

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.

python/scripts/sample_validation/skills/foundry-config-setup/SKILL.md · 53 lines

What it actually says

Usage

Some samples (notably those under 01-get-started) hardcode the Foundry project endpoint and model directly in the FoundryChatClient constructor using placeholder values, for example:

client = FoundryChatClient(
    project_endpoint="https://your-project.services.ai.azure.com",
    model="gpt-4o",
    credential=AzureCliCredential(),
)

These placeholder values are not real and the sample cannot run as written. The validation environment provides the real values through environment variables, so the sample must read them from the environment instead.

When you detect a hardcoded/placeholder project_endpoint (or model) that is causing the sample to fail with missing or invalid setup:

  1. Replace the hardcoded project_endpoint value with a read from the FOUNDRY_PROJECT_ENDPOINT environment variable.
  2. Replace the hardcoded model value with a read from the FOUNDRY_MODEL environment variable.
  3. Ensure import os is present at the top of the file.

The corrected constructor should look like:

import os

client = FoundryChatClient(
    project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
    model=os.environ["FOUNDRY_MODEL"],
    credential=AzureCliCredential(),
)

These samples are intentionally written with hardcoded placeholders, so this is expected setup—not a defect in the sample. After applying the change, re-run the sample and report the result as a success if it now runs.

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. yesterday First seen · 53 lines · 65 tokens per session scan A 72279cefeddb

Subscribe to this mod's changes

foundry-config-setup is a skill published in the GitHub repository microsoft/agent-framework (13,222 stars, last pushed 2d ago), licensed MIT. It adds 65 tokens to every session and 430 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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