Most developers now use coding assistants. I do too—Copilot at work, Claude Code at home. As a developer, I prefer not to repeat myself. This post explains why and how to avoid repetition as a skill.
Don't Repeat Yourself
The DRY principle has been present in the software development field for ages. The idea is that if you copy and paste code in multiple places and a bug appears, you'll need to fix the bug in all these places. The more the number of duplications, the more chances you'll miss one of them when fixing.
In the context of coding assistants, DRY means something entirely different. From a personal point of view, it means you don't need to ask the assistant to analyze your project at every session. Or to reference your language's coding conventions again. Or that your project favors immutability.
When a new developer joins a good project, they are told what the project's features, architecture, and conventions are. In great projects, conventions are formalized in written form and sometimes even kept up-to-date. Your coding assistant is a team member like any other: it requires written documentation.
Less is more
Both coding assistants I use allow the use of such instructions. I assume all do. For example, GitHub Copilot automatically reads the .github/instructions.md file.
The problem with such instructions is that the assistant may read them automatically. If they are too broad and don't apply to the tasks, you'll pollute the context with irrelevant data. Conclusion: you need to keep the file relatively small. Thus, focus file instructions on general information.
Sizing advices differ depending on the exact source. For example, docs.factory.ai mentions less than 150 lines. A Q&A on Reddit clarifies that 700 lines is too long. My advice would be to start small, increment when needed, analyze results, and refactor when it grows too large.
Token economics
Today, critical resources aren't CPU, RAM, or storage, but tokens. Tokens are a finite and expensive resource. My opinion is that soon, developers will be measured on their token usage: the better one will be the one using the fewest tokens to achieve similar results.
Most agents will load the default instructions file, AGENTS.md. Claude will load CLAUDE.md. The smaller the file, the fewer tokens used in the context.
A good context contains all the necessary tokens, but not more. That's where skills come into play.
Skills
Agent Skills are folders of instructions, scripts, and resources that agents can discover and use to do things more accurately and efficiently.
Skills are different from AGENTS.md in that they aren't loaded automatically. Hence, they don't bloat the context. Now comes the fun part: depending on the coding assistant, it may discover the skill and load it automatically, or not.
I will describe how Claude works. I think its approach is superior, so I guess other assistants will implement it soon.
By default, both you and Claude can invoke any skill. You can type
/skill-nameto invoke it directly, and Claude can load it automatically when relevant to your conversation.
Claude knows when to invoke a skill by transforming all SKILL.md files' front matter into tools. Here's the front matter of the Kotlin skill I created:
---
name: kotlin
description: "|"
Use this skill when working with Kotlin code in any capacity:
- Reading, writing, editing, or reviewing Kotlin files (*.kt, *.kts)
- Running Gradle tasks for Kotlin modules
- Writing or debugging Kotlin/JS code that targets Node.js
- Working with external JavaScript libraries from Kotlin
- Writing tests for Kotlin code (@Test, @BeforeTest, @AfterTest)
- Setting up dependency injection or mocking in Kotlin
- Dealing with multiplatform Kotlin projects (common, jsMain, jsTest, jvmMain)
- Troubleshooting Kotlin compilation or runtime errors
- Any task involving Kotlin/JS modules targeting Node.js
This skill provides Kotlin/JS technical knowledge (especially JS interop gotchas)
and coding style preferences beyond the official conventions.
---
The above gives Claude information on when to invoke the tool. Obviously, the skill is about Kotlin and Kotlin/JS.
For the content, follow the same rules as regular AGENTS.md files:
You can reference other documents, textual and others, local in the same skill folder or accessible online. I have copied and pasted the whole Kotlin coding conventions in a dedicated file.
SKILL.mdsummarizes the main items and links to the conventions.
The full conventions are cached locally in this skill directory at `kotlin-coding-conventions.md`.
Key reminders:
- Prefer `val` over `var` - immutability first
- Use immutable collection interfaces (`List`, `Set`, `Map`, not `MutableList`, etc.)
- Use `it` for short lambdas, named parameters for nested/complex ones
- Prefer expression form of `if`, `when`, `try` over statement form
- Prefer functional style (`filter`, `map`) over imperative loops
You should structure the document using headings, subheadings, and lists.
You should use good and bad examples.
### 1. External Interfaces vs Kotlin Classes
**Problem**: Kotlin classes have methods on their prototype. External interfaces expect methods directly on the object. You cannot use `unsafeCast` to convert between them.
```
kotlin
// ❌ WRONG: This will fail at runtime
class MockSql {
fun unsafe(query: String) = ...
}
val sql: Sql = mockSql.unsafeCast<Sql>() // Will throw: sql.unsafe is not a function
// ✅ CORRECT: Use extension function to build plain JS object
fun MockSql.toExternal(): Sql {
val obj = Any().asDynamic()
val mock = this
obj.unsafe = { query: String -> mock.unsafe(query) }
obj.end = { mock.end() }
return obj.unsafeCast<Sql>()
}
// Then use it:
val sql: Sql = mockSql.toExternal()
```
```
`
- etc.
Conclusion
Skills are great for avoiding repeating the same instructions over and over. The main difference with instructions is that they don't bloat the context for nothing. Depending on your coding assistants, they may trigger when required, or you may need to explicitly activate them.
The complete source code for this post can be found on Codeberg.
To go further:
Originally published at A Java Geek on March 15th, 2026.
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