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LLM structured output fails on value constraints, not shape

By PulseAugur Editorial · [1 sources] ·

A developer encountered issues with LLM-generated summaries, specifically with title length constraints. While structured output formats like JSON with Zod schemas guarantee the data's shape, they do not enforce value constraints like maximum character limits. The model missed the 120-character limit on four summaries by only a few characters, indicating it was attempting to adhere to the instruction but struggled with precise arithmetic during generation. A proposed solution involves creating a buffer by increasing the schema's maximum length while keeping the prompt's limit lower, allowing for minor overshoots without discarding valid summaries. AI

IMPACT Highlights limitations in LLM's ability to strictly adhere to value-based constraints within structured outputs, impacting practical applications.

RANK_REASON Developer's personal blog post discussing limitations of LLM structured output.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

LLM structured output fails on value constraints, not shape

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Developer's personal blog post discussing limitations of LLM structured output.
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · robzepdev ·

    Structured output guarantees the shape, not the lengths

    <p>I run the first real batch of my release tracker on 2026-09-28: 126 releases, one Message Batches<br /> call, done in 17 minutes. The API reported 126 successes out of 126. My pipeline stored 122.</p> <p>Four summaries were thrown away by my own validation. Not because the mod…

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