When Your Tool Returns Garbage, Agents Loop Forever. Here's the 30-Line Guard.
The article discusses the challenges faced when AI tools return malformed data, leading to endless retry loops. It emphasizes the need for a 30-line Python guard to handle different types of tool failures effectively. By categorizing failures and providing structured error messages, the guard can prevent unnecessary costs and improve user experience.
- ▪Malformed JSON responses can cause AI models to endlessly retry calls, leading to increased costs and user frustration.
- ▪The article outlines three classes of tool failures: schema mismatch, partial data, and semantic garbage, each requiring different handling strategies.
- ▪Implementing a 30-line guard can help classify failures and provide appropriate feedback to the AI model, preventing wasted resources.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 425693) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Gabriel Anhaia Posted on May 24 When Your Tool Returns Garbage, Agents Loop Forever. Here's the 30-Line Guard. #agents #ai #llm #python Book: AI Agents Pocket Guide: Patterns for Building Autonomous Systems with LLMs Also by me: Thinking in Go (2-book series) — Complete Guide to Go Programming + Hexagonal Architecture in Go My project: Hermes IDE | GitHub — an IDE for developers who ship with Claude Code and other AI coding tools Me: xgabriel.com | GitHub A tool returns a malformed…
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