AI Coding Agent Instruction Files: From Purpose to Loading Mechanism

When using an AI coding agent to assist development, many people run into the same frustration: using the same tool, some can get it to reliably produce code that follows project conventions, while others have to correct it over and over. The difference usually lies not in the tool itself, but in whether there is a high-quality agent instruction file. This article breaks down, from a general perspective, the purpose, loading mechanism, and writing methods of these files, so you can write context configuration that helps the agent “understand the craft.”

01 Why You Need an Agent Instruction File

Coding agents driven by large language models have an inherent constraint: their context window is limited, and each session does not naturally know the details of your project. What are the build commands, how do you run tests, what code style conventions apply, which directories must not be touched—if this knowledge is not provided explicitly, the agent has to guess, and the probability of guessing wrong rises sharply as project complexity increases.

The purpose of an agent instruction file is to distill this “project-level common knowledge” into a persistent configuration. It is equivalent to giving the agent a long-term “onboarding manual”: instead of repeating everything in every conversation, the agent reads it once at startup and it carries through the entire workflow. For team collaboration or scenarios that continue across sessions, the value of this file is even more pronounced—it turns verbal, easily lost conventions into version-controlled, reviewable engineering assets.

02 How Instruction Files Fundamentally Differ from Documentation

When first getting started, many people write an instruction file as if it were a piece of documentation, and the results are poor. Both may look like Markdown, but their target readers and writing logic are entirely different.

• Documentation is written for humans: it answers “what does this project do, how do you install it, how do you contribute code,” emphasizing background, motivation, and readability.
• Instruction files are written for the agent: they answer “which executable rules should be followed when performing operations,” emphasizing determinism, executability, and low ambiguity.

Put differently, documentation focuses on “understanding and persuasion,” while instruction files focus on “constraints and execution.” The former can lay out background and tell a story; the latter should use imperatives and explicit checklists as much as possible, avoiding ambiguous adjectives. Understanding this distinction is what keeps you from writing an instruction file that is really just “a README dressed up as a configuration.”

03 The Loading Mechanism of Instruction Files

To write a good instruction file, you must first understand how it is loaded. Most AI coding agents build an instruction chain at startup, and this process usually runs only once, with the result carrying through the entire session. Where you place a file and how you organize it therefore directly determine whether the content takes effect.

Loading order generally follows a layered principle of “from global to local, with the latter overriding or supplementing the former”:

1. Global layer: located in a configuration directory under the user’s home directory, storing cross-project personal preferences, such as preferred language, general commit conventions, and universal security baselines.
2. Project layer: located in the project root, storing project-specific build, test, style, and directory constraints.

The significance of layered design lies in reuse and isolation: general conventions live in the global layer and take effect everywhere with one configuration; project-specific rules live in the project layer and are distributed with the repository, so that team members get consistent agent behavior simply by pulling the code. Note in particular that many tools use override-style loading within the same layer—that is, if a higher-priority override file exists, only that file is read, and it is not merged with the original. Naming and layering therefore need clear planning to avoid configurations silently failing.

04 What a High-Quality Instruction File Should Contain

A practical and effective instruction file usually covers the following categories of information. Each item should be written specifically and executably, avoiding vague slogans.

• Build and run commands: state the exact commands for installing dependencies, compiling, and starting the project, ideally with code block examples so the agent does not have to guess.
• Test and validation commands: explain how to run unit tests, static analysis, and formatting tools, along with the validation steps that must pass before committing.
• Code style conventions: naming rules, indentation, import ordering, comment requirements, and so on. Whatever can be automated should be left to tools; the instruction file only supplements.
• Directory and file constraints: mark which directories are generated artifacts, which hold core logic, and which must not be freely modified, to prevent the agent from altering critical files.
• Change synchronization requirements: when an interface or data structure is modified, specify which documentation, configuration, or tests must be updated in sync, forming a closed loop.
• Security and boundary red lines: baseline rules such as forbidding the commit of secrets, forbidding external network access, and forbidding destructive operations.

A sample instruction file structure looks like this:

# Project Conventions
## Common Commands
- Install dependencies: `pnpm install`
- Run locally: `pnpm dev`
- Run tests: `pnpm test`
- Pre-commit validation: `pnpm lint && pnpm test`
## Code Style
- Use TypeScript strict mode
- Name component files with PascalCase
- Public APIs must include comments
## Directory Constraints
- `src/`: core business logic, changes require caution
- `dist/`: build artifacts, manual editing forbidden
## Change Synchronization
- After modifying a public interface, update the documentation under `docs/api` and the corresponding test cases in sync

05 Common Mistakes and How to Improve

In practice, a few types of problems recur and are worth deliberately avoiding:

• Writing an instruction file like documentation: full of background yet lacking executable commands, so the agent still doesn’t know what to do after reading it. The fix is to write it as a checklist-style structure of “commands + constraints.”
• Rules that are too general: statements like “write high-quality code” impose almost no constraint on the agent. Replace them with verifiable, specific standards, such as “no function exceeds 50 lines” or “errors must be handled explicitly.”
• Long, unfocused files: piling up irrelevant background dilutes key information and increases the chance of misreading. Follow the principle of “minimum necessary”—keep only the rules that genuinely affect agent behavior, and organize them by topic so they are easy to locate.

Conclusion

The essence of an agent instruction file is to make the implicit engineering conventions of a project explicit and executable. When written well, the agent can produce reliable output like a senior team member familiar with the project; when written poorly, even the strongest model can only trial and error repeatedly. By grasping how it differs from documentation, understanding the layered loading and override mechanism, and following the writing principles of “specific, executable, minimum necessary,” you can turn this seemingly ordinary Markdown file into a key engineering asset that improves the reliability of AI-assisted coding.