Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/aiappsgbb/awesome-gbbnpx agentmods add skills/aiappsgbb/awesome-gbb/foundry-prompt-agentsWrote 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/aiappsgbb/awesome-gbb/foundry-prompt-agents)<a href="https://agentmods.dev/skills/aiappsgbb/awesome-gbb/foundry-prompt-agents"><img src="https://agentmods.dev/badge/skills/aiappsgbb/awesome-gbb/foundry-prompt-agents/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/aiappsgbb/awesome-gbb/foundry-prompt-agents"><img src="https://agentmods.dev/badge/skills/aiappsgbb/awesome-gbb/foundry-prompt-agents.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 97 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00236 | $0.05504 |
| Opus 5 | $0.00118 | $0.02752 |
| Sonnet 5 | $0.00047 | $0.01101 |
| Haiku 4.5 | $0.00024 | $0.00550 |
Grade A, and why
foundry-prompt-agents scanned grade A with 1 finding 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 5d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -X POST "https://<resource>.services.ai.azure.com/api/projects/<project>/agents/my-assistant/versions?api-version=v1" \ How it starts
The opening of the file, as written. The whole thing — 639 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Microsoft Foundry Prompt Agents — Reference Guide
Create declarative agents in Foundry Agent Service using only a model, instructions, and tools — no containers, no custom code, no build step. Prompt agents are the fastest path from zero to a working agent.
When to use prompt agents vs hosted agents
| Prompt agents | Hosted agents | |
|---|---|---|
| Definition | Declarative (model + instructions + tools) | Code-first (Python/C#/TS in container) |
| Runtime | Foundry Agent Service manages everything | You build & deploy a container image |
| SDK | azure-ai-projects (PromptAgentDefinition) |
MAF (agent-framework + agent-framework-foundry-hosting) |
| Build step | None — create via SDK, REST, or portal | Dockerfile → ACR → ACA or Foundry hosting |
| Tools | Built-in catalog + MCP + OpenAPI + functions | Full programmatic control (any Python library) |
| Customization | Instructions + tool config only | Unlimited (custom middleware, state, orchestration) |
| Best for | Q&A bots, RAG assistants, tool-using agents with standard tools | Complex orchestration, custom business logic, multi-agent systems |
Rule of thumb: Start with a prompt agent. Upgrade to a hosted agent only when you need custom code that can't be expressed as a tool.
Prerequisites
- Microsoft Foundry project with a deployed model (e.g.,
gpt-5-mini,gpt-5.4-mini,gpt-4.1) - Python 3.9+ with
azure-ai-projects ~= 2.4.0,azure-identity ~= 1.25.3, andhttpx ~= 0.28.1 - Azure CLI authenticated via
az login(orDefaultAzureCredential) - Foundry User role on the AI Services account (GUID
53ca6127-db72-4b80-b1b0-d745d6d5456d) — same role as hosted agents
pip install "azure-ai-projects~=2.4.0" "azure-identity~=1.25.3" "httpx~=0.28.1"
1 · Create a prompt agent
A prompt agent is created with PromptAgentDefinition — just a model name
and instructions. No container, no Dockerfile, no ACR.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 5d ago Changed · +5 lines bf651410bad5
- 10d ago First seen · 634 lines · 236 tokens per session scan A 24d70377bbca
foundry-prompt-agents is a skill published in the GitHub repository aiappsgbb/awesome-gbb (5 stars, last pushed 3d ago), licensed MIT. It adds 236 tokens to every session and 5,504 once invoked, about $0.0012 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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