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/gpt-rag/contractsgit clone --depth 1 https://github.com/Azure/GPT-RAGWhat 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 | $0.00128 | $0.00128 |
| Opus 5 | $0.00064 | $0.00064 |
| Sonnet 5 | $0.00026 | $0.00026 |
| Haiku 4.5 | $0.00013 | $0.00013 |
Grade A, and why
GPT-RAG contracts.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 2d 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
Shared contracts
- Treat schemas as cross-repository, versioned compatibility boundaries.
- Preserve existing consumers by default; use additive optional fields when appropriate.
- Update schema versions when interpretation changes.
- Keep logical and wire schemas aligned and regenerate integrity hashes from the exact committed bytes.
- Consumers must ignore unknown optional fields unless the contract explicitly says otherwise.
- Coordinate orchestrator, ingestion, and platform pins when a contract changes.
- Add or update contract tests and fixtures in every affected consumer.
- Do not claim legal or regulatory compliance from technical audit evidence.
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.
- 2d ago First seen · 19 lines · 128 tokens per session scan A eb33c9d4ad6c
GPT-RAG contracts.instructions.md is an instructions file published in the GitHub repository Azure/GPT-RAG (1,169 stars, last pushed 15d ago), licensed MIT. It adds 128 tokens to every session, about $0.0006 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
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.
azure-search-openai-demo bicep.instructions.md
Infrastructure as Code with Bicep.
chat-with-your-data-solution-accelerator copilot-instructions.md
Instructions for Azure-Samples/chat-with-your-data-solution-accelerator, covering chat with your data (cwyd) — repository instructions, repository layout (truth), mandatory references — consult before editing, external pattern sources — read-only and hard rules.
aisearch-openai-rag-audio AGENTS.md
Instructions for Azure-Samples/aisearch-openai-rag-audio, covering instructions for coding agents, code layout, running the code, prerequisites and local development setup.
azure-openai-rag-workshop AGENTS.md
Instructions for Azure-Samples/azure-openai-rag-workshop, covering azure openai rag workshop (node.js), key technologies and frameworks, constraints and requirements, challenges and mitigation strategies and development workflow.
openai-cookbook AGENTS.md
Instructions for openai/openai-cookbook, covering repository guidelines, project structure & module organization, build, test, and development commands, coding style & naming conventions and testing guidelines.