Borrowing it
Nothing to install: this file belongs to agentailor/fullstack-langgraph-nextjs-agent. 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/agentailor/fullstack-langgraph-nextjs-agent/main/.github/copilot-instructions.mdgit clone --depth 1 https://github.com/agentailor/fullstack-langgraph-nextjs-agentWrote 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/agentailor/fullstack-langgraph-nextjs-agent/copilot-instructions)<a href="https://agentmods.dev/instructions/agentailor/fullstack-langgraph-nextjs-agent/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/agentailor/fullstack-langgraph-nextjs-agent/copilot-instructions/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/agentailor/fullstack-langgraph-nextjs-agent/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/agentailor/fullstack-langgraph-nextjs-agent/copilot-instructions.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 | $0.01200 | $0.01200 |
| Opus 5.5 | $0.00480 | $0.00480 |
| Sonnet 5.5 | $0.00240 | $0.00240 |
| Haiku 4.5 | $0.00120 | $0.00120 |
Grade A, and why
fullstack-langgraph-nextjs-agent copilot-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.
How it starts
The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Agent Instructions
This is a Next.js 15 fullstack application that implements an AI agent chat interface using LangGraph.js with Model Context Protocol (MCP) server integration and streaming responses.
Architecture Overview
Core Agent System
- LangGraph Agent: Built with
AgentBuilderclass insrc/lib/agent/builder.ts- creates a StateGraph with agent→tool_approval→tools flow - MCP Integration: Dynamically loads tools from MCP servers stored in Postgres (
src/lib/agent/mcp.ts) - Persistent Memory: Uses LangGraph's Postgres checkpointer for conversation history across sessions
- Tool Approval: Implements human-in-the-loop pattern with interrupts for tool execution approval
Data Flow
- User message →
/api/agent/streamSSE endpoint →streamResponse()inagentService.ts - Agent processes with tools from enabled MCP servers → streams incremental responses
- Frontend uses
useChatThread()hook with React Query for optimistic UI and streaming - Thread persistence via Prisma → Postgres (threads + MCP server configs)
Essential Development Commands
# Setup (requires Postgres running on port 5434)
docker compose up -d
pnpm install
pnpm prisma:generate
pnpm prisma:migrate
# Development
pnpm dev # Next.js with Turbopack
pnpm prisma:studio # Database UI
# Database operations
pnpm prisma:generate # After schema changes
pnpm prisma:migrate # Create new migrations
Project-Specific Patterns
Agent Configuration
- One-time setup:
ensureAgent()ensures Postgres checkpointer is initialized before agent creation - Dynamic tool loading: MCP servers are queried from database on each agent creation
- Model flexibility: Supports switching between OpenAI/Google models via
AgentConfigOptions
Streaming Architecture
- SSE with React Query:
useChatThreadmanages optimistic UI + streaming updates - Message accumulation: Frontend concatenates text chunks by message ID for smooth UX
- Tool approval flow: Uses Command objects with
resumeaction instead of regular inputs
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.
- 1mo ago First seen · 135 lines · 1,200 tokens per session scan A 05f2d468c471
fullstack-langgraph-nextjs-agent copilot-instructions.md is an instructions file published in the GitHub repository agentailor/fullstack-langgraph-nextjs-agent (134 stars, last pushed 1mo ago), licensed MIT. It adds 1,200 tokens to every session, about $0.0048 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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