An AI agent is only as good as the instructions you give it. Context engineering designs those instructions to be reliable and lasting. You craft files that sit in your project root. Every agent reads them before acting.
This guide explains how to build AGENTS.md, CLAUDE.md, and GEMINI.md files. You will also learn why token count matters less than context quality.
| Context element | Purpose | Example |
|---|---|---|
| Tech stack | Tells agent which languages and frameworks to use | TypeScript, Next.js, Tailwind CSS |
| Code style | Defines naming conventions and formatting | Use functional components. Prefer named exports. |
| Architecture rules | Specifies folder structure and design patterns | /app for routes, /components for shared UI |
| Forbidden actions | Lists commands the agent must never run | Never drop a database table. Never force push. |
| Workflow instructions | Defines how the agent should approach tasks | Plan first, then implement, then review |
What is context engineering and why does it matter?
Context engineering is the practice of designing the instructions that guide AI agents. You write a file like AGENTS.md once. Every agent session reads it. This gives your agents consistent behavior across teams and time.
Without context engineering, agents guess your preferences. They might use the wrong framework or skip important conventions. A good context file removes ambiguity. It makes agents predictable and safe.
Learn to build effective context files step by step.
What are AGENTS.md, CLAUDE.md, and GEMINI.md files?
These are plain text files placed in your project’s root folder. AGENTS.md is the emerging standard across tools. CLAUDE.md is the format for Claude Code. GEMINI.md works with Google’s Gemini models.
All three serve the same function. They inject project‑wide rules into every agent conversation. You define the stack, style, architecture, and constraints once. The agents follow them in every session.
See templates and examples for building each type of context file.
How is context quality more important than token volume?
A common mistake is trying to pack everything into the context. More tokens do not mean better results. The agent gets confused by conflicting or irrelevant information.
Focus on curation. Remove outdated instructions. Prioritize rules that change behavior. Deduplicate repeated constraints. A short, high‑quality context file outperforms a long, cluttered one every time.
Read why token count is not the real bottleneck.
How do I maintain context files as my project grows?
Version your context files alongside your code. Review them when you change frameworks or team conventions. Keep a changelog at the bottom. This helps new team members understand why rules exist.
Run periodic audits. Ask the agent to list which context rules it used for a task. Remove rules it never references. Context engineering is an ongoing practice, not a one‑time setup.
(1) Create an AGENTS.md file in your project root.
(2) Add sections for tech stack, code style, and architecture.
(3) List forbidden actions explicitly.
(4) Keep it short. Review and prune monthly.
(5) Test. Ask the agent to explain how it used the context.
References
- Context Engineering: How to Build Agent Context Files
- Context Quality vs Context Volume
- Anthropic Claude Code documentation — CLAUDE.md guidelines
Always refer to the official documentation.
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