mcp-agent-langchainjs: Instructions file for GitHub Copilot

.github/instructions/genaiscript.instructions.md

mcp-agent-langchainjs genaiscript.instructions.md is an instructions file for GitHub Copilot from Azure-Samples/mcp-agent-langchainjs. It costs 238 tokens per session, scanned A, original, MIT.

A set of coding rules for GenAIScript, a TypeScript-based tool for writing programs that use generative AI. It describes how such files should be written and stored.

In plain words
What is it for?
Use it when creating or editing GenAIScript files, especially TypeScript modules saved in the genaisrc folder.
Why use it?
It keeps GenAIScript code consistent with the runtime's conventions and gives generated code a predictable structure.

Instructions file for GitHub Copilot

Written for GitHub Copilot: a Copilot instructions file.

This is Azure-Samples/mcp-agent-langchainjs's own configuration. It tells GitHub Copilot how to work on mcp-agent-langchainjs itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything mcp-agent-langchainjs configures →

Reuse

Borrowing it

Nothing to install: this file belongs to Azure-Samples/mcp-agent-langchainjs. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/Azure-Samples/mcp-agent-langchainjs/main/.github/instructions/genaiscript.instructions.md
Clone the repo
git clone --depth 1 https://github.com/Azure-Samples/mcp-agent-langchainjs

Made for: GitHub Copilot.

Wrote 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.

agentmods badge for mcp-agent-langchainjs genaiscript.instructions.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/azure-samples/mcp-agent-langchainjs/genaiscript/github.svg)](https://agentmods.dev/instructions/azure-samples/mcp-agent-langchainjs/genaiscript)
Your own site
<a href="https://agentmods.dev/instructions/azure-samples/mcp-agent-langchainjs/genaiscript"><img src="https://agentmods.dev/badge/instructions/azure-samples/mcp-agent-langchainjs/genaiscript/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.

agentmods 80×15 button for mcp-agent-langchainjs genaiscript.instructions.md

Your own site · 80×15
<a href="https://agentmods.dev/instructions/azure-samples/mcp-agent-langchainjs/genaiscript"><img src="https://agentmods.dev/badge/instructions/azure-samples/mcp-agent-langchainjs/genaiscript.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 238 This file is loaded in full into every session.
When invoked 238 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00238 $0.00238
Opus 5.5 $0.00095 $0.00095
Sonnet 5.5 $0.00048 $0.00048
Haiku 4.5 $0.00024 $0.00024

Measured 1mo ago against content hash ddaef327a935, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

mcp-agent-langchainjs genaiscript.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 1mo 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

.github/instructions/genaiscript.instructions.md · 21 lines

What it actually says

GenAIScript Code Generation Instructions

GenAIScript is a custom runtime for node.js. It provides a set of unique APIs and support the TypeScript syntax, ESM, await/async.

Guidance for Code Generation

  • you always generate TypeScript code using ESM modules for Node.JS.
  • you prefer using APIs from GenAIScript genaiscript.d.ts rather than node.js. Do NOT use node.js imports.
  • you keep the code simple, avoid exception handlers or error checking.
  • you add TODOs where you are unsure so that the user can review them
  • you use the global types in genaiscript.d.ts are already loaded in the global context, no need to import them.
  • save generated code in the ./genaisrc folder with .genai.mts extension
Changes

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.

  1. 1mo ago First seen · 21 lines · 238 tokens per session scan A ddaef327a935

Subscribe to this mod's changes

mcp-agent-langchainjs genaiscript.instructions.md is an instructions file published in the GitHub repository Azure-Samples/mcp-agent-langchainjs (204 stars, last pushed 3mo ago), licensed MIT. It adds 238 tokens to every session, about $0.0010 per session on Opus 5.5. 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.

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