When to Use an Agent complex workflows multiple decision steps tool orchestration When NOT to Use an Agent simple automation no reasoning required direct workflows Why This Matters Using an agent when not needed: increases complexity reduces efficiency
Tool Execution Flow model decides to call a tool tool executes structured output is returned AI uses the result in its response Common Errors missing required fields unclear parameters invalid inputs Best Practices for Errors prevent missing fields include validation return structured errors avoid vague messages Do’s be specific about missing fields explain why it failed provide clear status Don’ts vague messages no explanation no guidance
Why Tools Matter Well-designed tools: improve accuracy reduce cost enable scalability Poor Tool Design too much data unclear structure confusing outputs Best Practices manage tool outputs keep structure consistent handle errors properly Tool Output Impact large outputs increase token usage affects performance and cost Designing Effective Tools for AI Agents Why Tools Matter Well-designed tools: improve accuracy reduce cost enable scalability Poor Tool Design too much data unclear structure confusing outputs Best Practices manage tool outputs keep structure consistent handle errors properly Tool Output Impact large outputs increase token usage affects performance and cost
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