One Context For All Your AI Coding Tools

Every AI coding tool wants its own configuration file and instructions. Over time, they drift apart and your agents behave differently in every editor. AgentCTX fixes this by turning one shared context into tool specific configs for all your AI coding assistants.

Install AgentCTX View quickstart

Configuration sprawl across AI coding tools

Modern engineering teams rarely use a single AI assistant. A typical repository now contains separate configuration files for each tool:

AGENTS.md

.cursor/rules

.github/instructions

Each file repeats the same project description, coding standards, and security guidelines with slight variations. Some are updated, others are forgotten, and nobody is sure which one is the source of truth.

The result is context drift. Different tools give different answers to the same request, and new team members are never quite sure what the rules are.

A single source of truth that syncs everywhere

AgentCTX introduces a shared context file for your project. You maintain your project description, coding standards, workflows, and constraints in one place. From that context, AgentCTX generates the tool specific configuration files your AI assistants expect.

.agentctx

AGENTS.md

.cursor/

.opencode/

.github/

Key ideas:

One human maintained context file in your repository

Automatic generation of Claude, Cursor, Copilot, and other tool configs

Consistent instructions and standards across every editor and assistant

You edit the context once, run AgentCTX, and every supported tool is up to date.

Simple workflow for any project

Install AgentCTX

Install AgentCTX with a single command.

curl -fsSL https://downloads.agenstra.com/agentctx/install.sh | bash

Add context file

Add a project context file to your repository that describes architecture, standards, workflows, and security notes.

Run AgentCTX

Run AgentCTX to generate tool specific config files for the AI coding tools you use.

agentctx

Commit or keep as artifacts

Commit the generated files if needed or let them stay as build artifacts.

When you update your project context, you rerun AgentCTX and all configs are regenerated. No manual copy and paste, no stale instructions.

Give your AI coding tools the information they really need

AgentCTX encourages teams to treat context as a first class asset. Instead of long, unfocused prompts, you maintain structured knowledge that AI tools can rely on, such as:

Architecture & domain

High level architecture and domain overview

# Project overview...

Coding style

Coding styles, naming conventions, and review expectations

# Conventions...

Security

Security considerations, secrets handling, and what must never be changed automatically

# Security...

Documentation

Links to documentation, ADRs, and design docs

# Docs...

The richer and more accurate your context file is, the more reliable your AI coding tools become.

Less drift, more alignment

Every assistant follows the same rules and understands the same project story.

New team members get clear guidance through the context file and consistent behavior from their tools.

Context lives in your repository with pull requests, reviews, and history.

You can add or swap AI tools without redefining everything from scratch.

AgentCTX turns context from an afterthought into an asset.

Built for teams that code with AI every day

AgentCTX is a natural fit for software development teams!

Platform engineers

Standardize tool config across repos

Dev leads

Keep teams aligned on standards

Security-conscious teams

Govern what AI can see and do

Open source maintainers

One context for all contributors

Uses multiple AI coding tools across different editors
Works in monorepos or large codebases with many contributors
Cares about consistent standards and secure defaults
Wants AI to feel like part of the engineering system, not a personal side tool

Add AgentCTX to your next sprint

Set up AgentCTX in a single project first. Define a minimal context file that covers architecture, standards, and how to run the app. Generate configs for your existing tools, gather feedback from the team, and evolve the context over time.

Once your team feels the difference, you can roll out AgentCTX across repositories to standardize how AI coding tools understand your systems.

View installation guide Explore example context files