Debugging Claude AI Agents: Loops, Bad Tool Calls, Fixes
Field guide to debugging Claude agents: why they loop, pick wrong tools, and hallucinate arguments — with concrete traces and fixes that hold.
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Field guide to debugging Claude agents: why they loop, pick wrong tools, and hallucinate arguments — with concrete traces and fixes that hold.
Learn what to put in a Claude agent's context and what to leave out, and why: working-set thinking, compression, and system prompts that grant bounded agency.
Connect tools and MCP servers to a Claude agent the right way: auth at the boundary, strict schemas, structured errors, and idempotency for safe writes.
Code-level Claude agent patterns: layer prompts, design intent-shaped tools, budget context, enforce output contracts, and externalize know-how into Skills.
Follow a concrete walkthrough to build a working Claude agent: define tools, run the loop, handle results, add a scratchpad, and test against real inputs.
See how agentic AI architecture fits together with Claude: the model loop, context assembler, tool layer, memory, and orchestration explained end to end.
Learn how agentic AI is reshaping the hospitality industry through personalized guest experiences, intelligent booking management, and automated concierge services across global hotel and tourism markets.
Discover how agentic AI is transforming mining exploration through intelligent geological analysis, optimized drilling operations, and predictive mineral deposit modeling across major mining regions worldwide.
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