This post introduces a Python-based linter and GitHub Action designed to enforce specific rules for tool descriptions used by AI agents. The linter checks for provenance, usage cues (when-to-call), token budget adherence, and consistency between different language versions of tool descriptions. The author demonstrates the linter catching its own errors, highlighting the importance of treating wording changes as interface modifications, especially when agents consume these descriptions. AI
IMPACT Enhances reliability and maintainability of AI agent integrations by treating natural language descriptions as code.
RANK_REASON The item describes a new tool (a linter and GitHub Action) for managing AI agent tool descriptions, not a core AI model release or research.
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