Agent Application DevelopmentAccount
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Practice 60FundamentalsConceptsAbout 6 minutes

Corresponding knowledge: Capacity, response shapes, and execution boundaries of LLM interfaces

What LLM interface basics must be mastered to do Agent development?

Focus only on context budgeting, structured output, tool invocation, and bounded retries that affect Agent engineering behavior.

Learn corresponding knowledgeInterview questions · Answer independently →
TokenContextStructured OutputTool Calling

Knowledge content check2026-10-03 · Check the source of the original question2026-10-02

The knowledge corresponding to this exercise:

Your first model call and response contract · Hierarchical deep learning →Prompts, structured output, and iterative acceptance checks · Hierarchical deep learning →
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Knowledge exercises·Independent answers

My notes and review ↗

Principles and Solutions have been collapsed. Explain the core mechanism, boundaries and verification methods in your own words, and then compare them.

Answers and personal notes

Each modified commit will be kept as an independent history. Your level of mastery is up to you to evaluate yourself against the standards.

Explain in your own words first

The core principles, analysis, Q&A and migration cases have been closed. When you are ready, unfold it and compare it with the content to find any omissions.

Hands-on verificationComplete on demand · Suggestions15 minutes

Read a model response that contains both tool calls and text indicating the next execution boundary.

Expand acceptance requirements and checkpoints
  • Tools are verified first and then executed.
  • Model text is not a proof of success
  • Context is considered separately from output budget

Key inspections

  • Know that the tool schema, historical messages, and tool results all impact context budgeting.
  • Distinguish between valid JSON structure, correct business parameters and execution with permission.
  • Different processing paths can be given for rejection, truncation and timeout.