Chat with Your Data is an Azure-based application pattern that indexes an organization’s documents and lets users ask questions whose answers cite the source material. It is for organizations building conversational search and question-answering systems over contracts, policies, manuals, or other internal content. Its catalogue entry provides an instruction for working with the accelerator.
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/chat-with-your-data-solution-accelerator/copilot-instructionsgit clone --depth 1 https://github.com/Azure-Samples/chat-with-your-data-solution-acceleratorWrote 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/chat-with-your-data-solution-accelerator/copilot-instructions)<a href="https://agentmods.dev/instructions/azure-samples/chat-with-your-data-solution-accelerator/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/azure-samples/chat-with-your-data-solution-accelerator/copilot-instructions.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 | $0.08430 | $0.08430 |
| Opus 5 | $0.04215 | $0.04215 |
| Sonnet 5 | $0.01686 | $0.01686 |
| Haiku 4.5 | $0.00843 | $0.00843 |
Grade B, and why
chat-with-your-data-solution-accelerator copilot-instructions.md scanned grade B 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 4d 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
- **End-of-turn beep is the agent's responsibility.** GitHub Copilot does not execute Claude Code-style `~/.claude/settings.json` `Stop` hooks, so the agent **must** emit the chime as its **final tool call** before handi How it starts
The opening of the file, as written. The whole thing — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Chat With Your Data (CWYD) — Repository Instructions
These instructions are always loaded. Read them before doing anything else.
Repository layout (truth)
cwyd-v1/— v1 (legacy, frozen). Flask + Streamlit + Semantic Kernel + Prompt Flow + direct Azure OpenAI SDK. Do not extend. Only touch v1 to perform documented removals listed in v2/docs/development_plan.md §2.1. All v1 code, infra, docker, scripts, and tests live undercwyd-v1/.- Repo root (
src/,infra/,docker/,scripts/,tests/,azure.yaml,pyproject.toml,package.json) — v2 (active development). FastAPI + LangGraph + Agent Framework + Foundry IQ, promoted from the oldv2/subtree to the repo root. All new work goes here. infra/(root) — v2 Bicep. The v1 Bicep lives undercwyd-v1/infra/.tests/(root) — v2 tests (shared gates, backend, frontend, functions, infra, integration, smoke). The v1 e2e/integration tests live undercwyd-v1/tests/.v2/docs/— the only tree still underv2/: v2 development plan, pillars, ADRs, bugs registry, and worklog.
Mandatory references — consult before editing
- v2/docs/development_plan.md — phase ordering, file paths, scope, removals, additions. Source of truth for what to build and when. Always read §0 Status snapshot + the head of §0.1 debt queue before proposing a task. As of 2026-05-11 the active phase is Phase 6 — Functions blueprints / modular RAG indexing pipeline (
batch_start,batch_push,add_url,search_skillundersrc/functions/; ingestion-only extensions undersrc/functions/core/). Phases 1–5 + 5.5 are closed; #35d (FE admin merge) and #24 partial (FE SSE polish) are open and explicitly non-blocking for Phase 6. #35g (per-tenant overrides) is withdrawn as out of scope — the deployment is single-tenant, so per-tenantRuntimeConfigkeying is a no-op; see ADR 0024. - v2/docs/pillars_of_development.md — every new core element must declare its pillar (Stable Core, Scenario Pack, Configuration Layer, or Customization Layer) in the file/class docstring. Read-only product policy — never edited by agents.
- Repo memory
cwyd-tech-stack.md— current stack truth (versions, services, package managers, test counts).
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.
- 4d ago First seen · 92 lines · 8,430 tokens per session scan B 727de53a41ab
chat-with-your-data-solution-accelerator copilot-instructions.md is an instructions file published in the GitHub repository Azure-Samples/chat-with-your-data-solution-accelerator (1,177 stars, last pushed 3d ago), licensed MIT. It adds 8,430 tokens to every session, about $0.0421 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). 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.