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Book Overview & Buying
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Table Of Contents
Design Multi-Agent AI Systems Using MCP and A2A
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Tool use is where agents interact with the real world, and it’s also where things most frequently go wrong. An agent might call the wrong tool, pass invalid parameters, misinterpret tool results, or chain tools together incorrectly. Unlike pure reasoning errors that stay within the LLM, tool use failures have real consequences: failed deployments, incorrect database updates, or broken integrations. Debugging these issues requires understanding both what the agent intended to do and what actually happened.
Let’s review again how AI systems, AI frameworks, agents, and LLMs interact with tools and consider the failure modes. Every tool invocation goes through a predictable life cycle, and failures can occur at each stage: