langchain-ai/langchain-azure-js is an early-stage JavaScript integration project that connects LangChain.js and LangGraph.js applications with Microsoft Azure AI services. It is intended for developers building LangChain-compatible applications with Azure models and services using standard runnables and Azure SDK clients. The catalogue instruction relates to using this repository's integration scaffolding.
Borrowing it
Nothing to install: this file belongs to langchain-ai/langchain-azure-js. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/langchain-ai/langchain-azure-js/main/AGENTS.mdgit clone --depth 1 https://github.com/langchain-ai/langchain-azure-jsWrote 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/langchain-ai/langchain-azure-js/agents-md)<a href="https://agentmods.dev/instructions/langchain-ai/langchain-azure-js/agents-md"><img src="https://agentmods.dev/badge/instructions/langchain-ai/langchain-azure-js/agents-md/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/instructions/langchain-ai/langchain-azure-js/agents-md"><img src="https://agentmods.dev/badge/instructions/langchain-ai/langchain-azure-js/agents-md.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.02110 | $0.02110 |
| Opus 5 | $0.01055 | $0.01055 |
| Sonnet 5 | $0.00422 | $0.00422 |
| Haiku 4.5 | $0.00211 | $0.00211 |
Grade A, and why
langchain-azure-js AGENTS.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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repository Guidelines
Purpose and Scope
- This monorepo provides SDKs that help LangChain.js and LangGraph.js users connect to Azure resources.
- Treat LangChain.js and LangGraph.js as the upstream compatibility references.
- Use langchain-azure, the Python counterpart, as a secondary reference for feature coverage, service behavior, and design lessons. Aim for long-term capability convergence rather than line-by-line parity, and account for differences between the JavaScript and Python Azure SDKs and language ecosystems.
- A nested
AGENTS.mdextends these repository-wide instructions for its package. Follow both files; when guidance conflicts, the instruction closest to the edited file takes precedence. - Keep agent instructions in hierarchical
AGENTS.mdfiles. Do not add parallelcopilot-instructions.mdor*.instructions.mdfiles.
Upstream Compatibility
- Before designing or changing a public API, find the analogous upstream abstraction, implementation, tests, and documentation. Prefer upstream names, signatures, option shapes, return types, and lifecycle semantics.
- Preserve LangChain contracts for runnables, callbacks, streaming, tool calling, serialization, tracing, cancellation, and standardized input/output types wherever they apply.
- Keep integrations naturally usable from LangGraph.js. Prefer shared LangChain primitives over graph-specific wrappers unless the feature is inherently graph-specific.
- Introduce Azure-specific behavior only where the service requires it. Keep it additive and document any deliberate divergence from upstream behavior.
- Do not copy an upstream implementation blindly. Reconcile it with this repository's supported
@langchain/core, Azure SDK, TypeScript, and runtime versions. - Treat public exports, constructor options, serialized fields, and environment-variable names as compatibility surfaces. Avoid breaking them without an explicit migration plan and tests.
- Preserve published APIs by default. Change a public API only when a new capability or a deliberate change in the product's mental model requires it; align the new shape with LangChain.js conventions and clearly communicate compatibility impact and migration guidance to users.
- Prefer additive evolution and deprecation periods over immediate removal or renaming of published APIs. Record any public compatibility impact, before-and-after usage, and migration guidance in the corresponding SDK documentation.
- Refine internal interfaces proactively as understanding improves. Internal parameter shapes and module boundaries may change when doing so makes the implementation simpler, more coherent, or easier to extend.
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.
- 9d ago First seen · 79 lines · 2,110 tokens per session scan A 8965512eac10
langchain-azure-js AGENTS.md is an instructions file published in the GitHub repository langchain-ai/langchain-azure-js (10 stars, last pushed yesterday), licensed MIT. It adds 2,110 tokens to every session, about $0.0106 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 2026-08-31.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.