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AI-RAG-Assistant-Chatbot: Instructions file for Codex

AGENTS.md

AI-RAG-Assistant-Chatbot AGENTS.md is an instructions file for Codex, OpenCode from hoangsonww/AI-RAG-Assistant-Chatbot. It costs 1,038 tokens per session, scanned A, original, MIT.

Repository guidance for Lumina, a full-stack AI chatbot with a web interface, an API server, document search, a standalone tool server, and a multi-agent pipeline.

In plain words
What is it for?
Use it when developing or changing Lumina's client, server, tool server, agent pipeline, infrastructure, deployment files, or tests.
Why use it?
It defines the project's boundaries and working rules, helping changes stay focused and avoid generated files, secrets, or unrelated edits.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: mentions Codex.

This is hoangsonww/AI-RAG-Assistant-Chatbot's own configuration. It tells Codex and OpenCode how to work on AI-RAG-Assistant-Chatbot 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 AI-RAG-Assistant-Chatbot configures →

not rated 47repo yesterday A scan 1,038 tokens original MIT
View source ↗ hoangsonww/AI-RAG-Assistant-Chatbot lumina-david.vercel.app
Reuse

Borrowing it

Nothing to install: this file belongs to hoangsonww/AI-RAG-Assistant-Chatbot. 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/hoangsonww/AI-RAG-Assistant-Chatbot/master/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/hoangsonww/AI-RAG-Assistant-Chatbot

Made for: Codex, OpenCode.

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README.md
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Per session 1,038 This file is loaded in full into every session.
When invoked 1,038 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 $0.01038 $0.01038
Opus 5 $0.00519 $0.00519
Sonnet 5 $0.00208 $0.00208
Haiku 4.5 $0.00104 $0.00104

Measured 9d ago against content hash 04011887e296, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

AI-RAG-Assistant-Chatbot 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.

AGENTS.md · 92 lines

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.

Lumina Codex Guide

Repository Overview

Lumina is a full-stack AI-powered chatbot with RAG, a standalone MCP server, and a multi-agent pipeline:

  • client/ — React 18 + Vite + MUI + Framer Motion frontend with branded chat UI, markdown/math rendering, and SSE streaming.
  • server/ — Express + TypeScript API handling auth, conversations, chat, Gemini AI, Pinecone vector search, and knowledge CLI.
  • mcp_server/ — Standalone Model Context Protocol server with 32 tools, 7 resources, 6 prompts across 8 categories.
  • agentic_ai/ — Python multi-agent LangGraph pipeline with MCP client integration for tool-augmented autonomous execution.
  • terraform/, aws/, docker-compose.yml — Infrastructure, deployment, and orchestration assets.

Scope Rules

  • Prefer the smallest-area change that solves the task.
  • Do not perform repository-wide formatting or incidental refactors unless explicitly asked.
  • Treat unrelated dirty files as user-owned. Do not revert or reorganize them.
  • Do not edit generated artifacts (client/build/, server/dist/, node_modules/).
  • Avoid touching .env files unless the user explicitly asks for environment changes.

Working Rules

  • Read the matching skill in .agents/skills/ when the task clearly maps to a subsystem:
    • lumina-frontend-ui for React/Vite frontend work.
    • lumina-backend-api for Express backend and API work.
    • lumina-rag-knowledge for RAG, knowledge ingestion, and citation work.
    • lumina-agentic-mcp for Python pipeline and MCP client work.
    • lumina-mcp-server for standalone MCP server development.
    • lumina-infra-deploy for Terraform, Docker, and deployment work.
  • Use README.md, ARCHITECTURE.md, RAG.md, DEPLOYMENT.md, and openapi.yaml as primary references before broad changes.
  • Preserve Lumina's branded frontend personality — do not flatten into generic boilerplate.
  • Keep knowledge management CLI-driven unless the user explicitly requests a product change.
  • Preserve grounded answers and inline citations when modifying retrieval behavior.
  • Update openapi.yaml when API request or response contracts change.
  • MCP tool names and input schemas are external contracts — rename carefully.

Read the full file on GitHub · 92 lines

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. 9d ago First seen · 92 lines · 1,038 tokens per session scan A 04011887e296

Subscribe to this mod's changes

AI-RAG-Assistant-Chatbot AGENTS.md is an instructions file published in the GitHub repository hoangsonww/AI-RAG-Assistant-Chatbot (47 stars, last pushed yesterday), licensed MIT. It adds 1,038 tokens to every session, about $0.0052 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.

Data and AIRAG and vectorsapiartificial-intelligencechat-applicationchatbotdockerexpress
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