A Complete Guide to Agents.md (www.aihero.dev)

A recent article emphasizes the importance of maintaining a well-structured AGENTS.md file, which is critical for optimizing the behavior of AI coding agents within repositories. This markdown file serves as a configuration layer that defines the agent's preferences and project-specific guidelines. If poorly managed, it can grow bloated, leading to inefficiencies and confusion due to redundant or conflicting instructions, ultimately wasting tokens and harming agent performance. The article outlines recommendations to keep AGENTS.md concise by employing progressive disclosure—providing only essential information while directing the agent to additional resources when necessary. Significantly, as AI agents increasingly assist in coding, the size and clarity of AGENTS.md directly impact their effectiveness. Every token in the file is loaded with each request, making it imperative that only relevant instructions remain. Outdated documentation poses additional challenges, particularly as file paths change within projects. Developers are encouraged to focus on stable domain concepts and essential specifics like project purpose and package manager. By adopting these best practices, AI/ML practitioners can ensure their agents operate more effectively, securing a better balance between instruction budget and task-specific performance.