A new method called Agent Action Grammar (AAG) has been developed to improve the reliability and efficiency of AI agents, particularly within the Cursor IDE. This approach replaces lengthy English prose in configuration files with a more structured, pseudocode-like syntax. AAG significantly reduces the token count required for instructions, cutting it by up to 73%, which in turn minimizes the "context tax" and prevents models like Claude and GPT from "forgetting" instructions. The grammar utilizes EBNF-style guard clauses and RFC 2119 verbs to enforce deterministic compliance, and an open-source Go CLI tool, `okf`, helps manage these rules across different AI tools. AI
IMPACT This method could significantly reduce the computational cost and improve the reliability of AI agents by optimizing instruction formats.
RANK_REASON This is a new method for configuring AI agents, presented as an open-source tool, rather than a release from a frontier lab.
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