Researchers urge developers to see that less is more when it comes to instructions
If you're exposing your agent to a strong odor, it's time to clean up your instructions. Risky or poorly structured code patterns are known as "code smells," and it turns out coding agent directives can be similarly redolent, leading to wasted tokens and worse output. Coding agents rely on configuration files that summarize expected agent behavior. These context-enhancing files are commonly written in Markdown and named either CLAUDE.md for those using Anthropic models or AGENTS.md for pretty much everyone else.
They include various text instructions that advise the coding agent about desired behavior and tool use. And they can get rather wordy. Anthropic advises no more than 200 lines of text because longer files consume model context and may hinder model coherence.
Researchers affiliated with the computer science department of the Federal Institute of Minas Gerais in Brazil recently scoured some 532,000 files to build and analyze a dataset of 100 popular open-source projects containing either an AGENTS.md or a CLAUDE.md file."Our results show that configuration smells are widespread," the authors state. "Lint Leakage was the most common smell, affecting 62 percent of the files, followed by Context Bloat (42 percent) and Skill Leakage (35 percent)."Linting is the process of running automated tools to check code for programming and style errors. Lint Leakage refers to agent instructions that repeat rules already enforced by linters, format checkers, and static analysis tools. Duplicative rules waste tokens by burdening the underlying model with guidance for a task already handled reliably by programmatic tools.
