Agentic ColdBox

The ColdBox CLI has tons of AI features to help build context and skills for any LLM and Agent

Introduction

Agentic ColdBox supercharges your development workflow by providing comprehensive AI assistance for both BoxLang and CFML applications through the ColdBox CLI.

The system combines four key components:

  1. Guidelines - Framework documentation stored locally in .agents/guidelines/core/ and referenced via read_file

  2. Skills - On-demand coding cookbooks sourced from skills.boxlang.io

  3. Agents - AI assistant configurations (Claude, Copilot, Cursor, Codex, Gemini, OpenCode)

  4. MCP Servers - Context protocol servers tracked in .mcp.json for live documentation and application introspection

Make sure you are on the latest coldbox-cli in your CommandBox installation before getting started.

Key Features

  • Dual-Language Support - First-class support for BoxLang and CFML with automatic detection

  • Multi-Agent Ecosystem - Works with Claude, GitHub Copilot, Cursor, Codex, Gemini, and OpenCode

  • 3 Core Guidelines - ColdBox, BoxLang, and CFML guidelines ship on-disk; agent files stay lean (~250 lines)

  • 200+ Skills Registry - All skills sourced from skills.boxlang.io, the centralized Ortus ecosystem skill repository

  • 30+ MCP Servers - Built-in documentation servers auto-matched to installed modules

  • Live App Introspection - cbMCP (BoxLang only) lets AI agents query your running application in real time

  • Override System - Customize core guidelines and skills at the project level


Installation

The wizard guides you through agent selection, language detection, and MCP server configuration. After installation, the following structure is created:

Agent configuration files are generated automatically:

Agent
Config File

Claude

CLAUDE.md

GitHub Copilot

AGENTS.md (shared)

Cursor

.cursorrules

Codex

AGENTS.md (shared)

Gemini

GEMINI.md

OpenCode

AGENTS.md (shared)

After installation, add your project context to the generated agent file — business domain, key services, authentication approach, and API endpoints. This gives AI assistants the application-specific knowledge they need.

Keeping Resources Updated

Automate with CommandBox scripts:


Core Concepts

Guidelines vs Skills

Guidelines teach AI agents what the framework is and how it works — architecture, conventions, and API references. They answer: "What tools do I have?"

Skills teach AI agents how to do specific things — step-by-step cookbooks with working code patterns. They answer: "How do I build this exact feature?"

Core guidelines (ColdBox + language) live on-disk in .agents/guidelines/core/ and are referenced via read_file in agent files — keeping agent files lean (~250 lines) while maintaining full framework knowledge. Skills are sourced from skills.boxlang.io and loaded on-demand.


AI Guidelines

Three core guidelines are installed automatically:

Guideline
File
Description

coldbox

coldbox.md

ColdBox framework architecture and conventions

boxlang

boxlang.md

BoxLang language features and syntax

cfml

cfml.md

CFML language fundamentals

Custom Guidelines

Custom guidelines live in .agents/guidelines/custom/ and are always available to the AI without needing to be explicitly requested. Use them to document your business domain, third-party integrations, architecture decisions, and team conventions:

Example guideline structure:

Overriding Guidelines


AI Skills

skills.boxlang.io is the centralized skill repository for the entire Ortus ecosystem — ColdBox, BoxLang, TestBox, CommandBox, and all major modules. With 200+ skills available, it is the single source of truth for implementation cookbooks. Skills are installed per-project and loaded on-demand by AI agents when the task matches.

Custom Skills

Create project-specific skills for workflows not covered by the registry. Each skill lives in its own folder with a SKILL.md file:

A SKILL.md should include a brief description of when to use the skill, step-by-step implementation instructions, and working code examples:


MCP Servers

Model Context Protocol (MCP) servers provide AI agents with live documentation and application introspection. All servers are tracked in .mcp.json at your project root.

Installing the ColdBox Live MCP Server (cbMCP)

The cbMCP module turns your running BoxLang ColdBox application into an MCP server, giving AI agents real-time access to routes, handlers, WireBox mappings, and more. See the ColdBox MCP Server documentation for the full tool reference, custom tool development, and AI client setup.

Once installed, AI agents can introspect your live app:

Managing MCP Servers

During coldbox ai refresh, the CLI auto-detects MCP servers from installed modules and updates .mcp.json automatically.

Built-in MCP Servers

Server
Description

boxlang

BoxLang Language Documentation

boxlang-ide

BoxLang IDE Documentation

modern-cfml

Modern CFML Guide

coldbox

ColdBox Framework Documentation

commandbox

CommandBox CLI Documentation

testbox

TestBox Testing Framework

wirebox

WireBox Dependency Injection

cachebox

CacheBox Caching Framework

logbox

LogBox Logging Framework

docbox

DocBox Documentation Generator

bxorm

BoxLang ORM

cborm

ColdBox ORM Utilities

qb

Query Builder (QB)

quick

Quick ORM Active Record

cfmigrations

Database Migrations

cbsecurity

CBSecurity Authentication/Authorization

cbauth

CBAuth User Authentication

cbsso

CBSSO Single Sign-On

cbvalidation

CBValidation Validation Framework

cbi18n

CBI18N Internationalization

cbmailservices

CBMailServices Email Integration

cbdebugger

CBDebugger Debugging Tools

cbelasticsearch

CBElasticsearch Integration

cbfs

CBFS File System Abstraction

cfconfig

CFConfig Server Configuration

cbwire

CBWire Reactive Components

cbq

CBQ Job Queues

megaphone

Megaphone Messaging

contentbox

ContentBox CMS

relax

Relax REST API Documentation


CLI Commands

Setup & Management

Component Management

Diagnostics


Best Practices

Version Control — commit your custom guidelines and skills to share them with your team:

Stay Synced — run coldbox ai refresh after pulling updates or installing new modules to keep agent configs current.

Custom Guidelines — use .agents/guidelines/custom/ for business domain concepts, third-party service integrations, and team conventions that the AI should always know about.

Custom Skills — use .agents/skills/ for project-specific workflows, deployment procedures, and domain patterns not covered by skills.boxlang.io.

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