Improving AI Agent Response Completeness with max_tokens

AI-103 By islever Editorial Last updated

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Short answer

B Increasing max_tokens does not ensure required clauses are included when the model omits them despite their presence in the source text.

Question

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You have a Microsoft Foundry project that contains an agent. The agent generates summaries from retrieved policy documents.
Users report that some responses omit required regulatory clauses, even when the clauses are present in the retrieved content.
You need to improve response completeness.
Solution: You increase the value of the max_tokens parameter.
Does this meet the goal?
  1. Yes
  2. No Correct Answer

Key Takeaways

The question tests the difference between output truncation and faithfulness/selection errors in generative AI agents, highlighting that max_tokens does not influence what information is selected for inclusion.

This question addresses the misconception that increasing max_tokens improves response completeness when content is omitted due to selection issues rather than length constraints. It establishes that max_tokens only controls output length, not factual inclusion.

Common mistake: Many learners incorrectly choose 'Yes' (A), assuming that providing more token budget will allow the model to include all necessary clauses, failing to recognize that the issue is selective omission, not space limitation.

Expert Analysis

Why the Answer Is Correct

Correct answer: B — Increasing max_tokens does not meet the goal because the problem is one of fidelity or selection, not truncation. The prompt states that required clauses are present in the retrieved content but are being omitted from the summary. This indicates the model is choosing to exclude them, likely due to poor prompting or alignment issues, not because it ran out of space.

Why the Other Options Are Wrong

Option A is incorrect because max_tokens is a hard limit on output length; it cannot force the model to prioritize specific content if the underlying generation process decides to skip it. Even if increased, if the model's attention mechanism ignores the clauses, they will still be omitted regardless of the token budget. Community comments confirm this, noting that "Increasing max_tokens does not force inclusion" and that the issue is "selection/faithfulness, not output length truncation."

Community Comment Notes

Several users correctly identified that the solution fails. One user noted that "Clauses are present... so the problem is selection/faithfulness." Another emphasized that "the issue is response completeness, not output truncation." A third suggested that proper solutions involve updating system instructions or using structured outputs, reinforcing that max_tokens is the wrong lever here.

Exam Strategy

When troubleshooting LLM behavior, distinguish between length-related failures (truncation) and content-related failures (hallucination, omission). Adjusting max_tokens only solves the former; use prompt engineering, retrieval optimization, or post-processing for the latter.

Frequently Asked Questions

Why doesn't max_tokens help if clauses are missing?

Max_tokens limits length, not selection. If the model chooses to omit content, more tokens won't force it back.

What fixes omitted clauses in Foundry agents?

Improve prompts, add explicit instructions to include all clauses, or use structured output schemas to enforce completeness.

More AI-103 FAQ →

Discussion 9 contributions

Compiled from public community threads and reader submissions, lightly edited for clarity. Handles and vote tallies are shown as recorded, and comments reflect the views of individual contributors.

From public community threads 9

  1. RICHARDALEX007 👍 4 Answered B
    Clauses are present in the retrieved content but omitted from the summary, so the problem is selection/faithfulness, not output length truncation. Increasing max_tokens does not force inclusion of the missing clauses, so it does not meet the goal.
  2. Mattt 👍 3 Answered B
    B. No. Increasing max_tokens only allows a longer response; it does not ensure that required clauses are included. The issue is response completeness, not output truncation.
  3. ArindamPal 👍 1 Answered A
    Increasing the max_tokens parameter allows the model to generate a longer response, which can improve the likelihood that all required clauses are included in the summary. Therefore, increasing max_tokens can improve response completeness and meets the stated goal.
  4. 8ac3742 👍 1 Answered B
    To ensure completeness for regulatory clauses, you should update the agent's system instructions (prompt engineering), enforce a structured output schema, or add a pre-response evaluation/retry loop in the application logic
  5. AIBoss 👍 1
    It says increase max_token but how much to increase? Suppose, previous max_token was 1000 , then increased to 1500 token. If response is 2000 tokens, then result is still truncated.
Show 4 more comments
  1. Vasent 👍 1 Answered A
    As Richard already explained, Increasing max_tokens does not force inclusion of the missing clauses (which is already present), so it does not meet the goal.
  2. cloudera 👍 1 Answered A
    Increasing max_tokens can help improve response completeness because it gives the model more output budget to include all required regulatory clauses.
  3. mamaMia2 👍 1 Answered B
    as the rest said it only makes it longer, doesnt gaurantee what we need
  4. fc2fb70 👍 1
    cloudera is Wrong....

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