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 agentmods add instructions/azure-samples/pizza-mcp-agents/webappgit clone --depth 1 https://github.com/Azure-Samples/pizza-mcp-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/instructions/azure-samples/pizza-mcp-agents/webapp)<a href="https://agentmods.dev/instructions/azure-samples/pizza-mcp-agents/webapp"><img src="https://agentmods.dev/badge/instructions/azure-samples/pizza-mcp-agents/webapp.svg" alt="Measured on agentmods" 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 | $0.00208 | $0.00208 |
| Opus 5 | $0.00104 | $0.00104 |
| Sonnet 5 | $0.00042 | $0.00042 |
| Haiku 4.5 | $0.00021 | $0.00021 |
Grade A, and why
pizza-mcp-agents webapp.instructions.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Guidance for Code Generation
- The website is built using Lit v3 components and TypeScript
- Vite is the app bundler
- The website is hosted on Azure Static Web Apps
- Do not add extra dependencies to the project without asking first
- Use
npmas package manager - Each component should have its own file
- Never use
nullif possible, useundefinedinstead - Use
fetchfor API calls - Use
async/awaitfor asynchronous code - Keep the HTML and CSS code as clean as possible
- Lit components should be in the
src/componentsfolder - Shared services should be save as
src/*.service.tsfiles - Re-export all components in
src/index.tsfile - Use latest CSS features such as nesting and custom properties
If you get it right you'll get a 1000$ bonus, but if you get it wrong you'll be fired.
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 First seen · 22 lines · 208 tokens per session scan A 33d8927554df
pizza-mcp-agents webapp.instructions.md is an instructions file published in the GitHub repository Azure-Samples/pizza-mcp-agents (33 stars, last pushed yesterday), licensed MIT. It adds 208 tokens to every session, about $0.0010 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.
Other instructions, from other repositories
azure-search-openai-demo AGENTS.md
AGENTS.md instructions for Azure-Samples/azure-search-openai-demo, covering instructions for coding agents, overall code layout, adding new data, adding a new azd environment variable and adding a new setting to "developer settings" in rag app.
GPT-RAG copilot-instructions.md
Copilot instructions for Azure/GPT-RAG, covering repository development and release instructions, branching strategy, default behavior, feature development workflow and branch creation.
azure-search-openai-demo bicep.instructions.md
Infrastructure as Code with Bicep.
GPT-RAG AGENTS.md
AGENTS.md instructions for Azure/GPT-RAG, covering gpt-rag agent operating contract, priority, what this repository is, repository boundaries and how to work.
GPT-RAG config-python.instructions.md
Instructions for Azure/GPT-RAG, a project described as: Enterprise-grade accelerator for agentic RAG on Azure. Built on Microsoft Foundry with Foundry IQ as the default retrieval backend, Microsoft Agent Framework orchestration, Zero-Trust architecture and IaC.
GPT-RAG lifecycle-hooks.instructions.md
Instructions for Azure/GPT-RAG, a project described as: Enterprise-grade accelerator for agentic RAG on Azure. Built on Microsoft Foundry with Foundry IQ as the default retrieval backend, Microsoft Agent Framework orchestration, Zero-Trust architecture and IaC.