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agentsop-structured-output-picker

Decide where to enforce structured LM output (constrain at decode time with Outlines vs validate-and-retry with Instructor vs grammar with Guidance) and which failure stance to take (Assert/hard-fail vs Suggest/soft-retry). Use when an LM's output is parsed or typed by downstream code and you must pick one enforcement library plus its failure handling, when malformed output is burning tokens on retries, or when choosing between decode-time vs validation-time constraints for local vs API models.

skills/agentsop-structured-output-picker/SKILL.md

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Oct 24, 2026
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# Structured-Output-Picker — 在解码处约束，还是在校验处约束？

> **One-liner**: Three local libraries (Outlines, Instructor, Guidance) plus
> provider-native structured outputs all "make the model emit valid structure",
> but they enforce at *different points* and *fail differently*. Pick by **how
> costly a malformed output is** and **whether you control the decoder**. Then
> pick the failure stance — **Assert** (hard-fail + retry) vs **Suggest** (soft
> nudge, degrade gracefully) — borrowed from DSPy's constraint primitives.

This is an **ENHANCE overlay**. The four enforcement mechanisms each have a
working local skill; what no single one provides is the cross-library *which-one
+ how-to-handle-failure* decision. That gap is hit every time an LM output is
consumed by code. For **what shape the content should take** (code vs JSON vs
prose), descend first to `[[agentsop-output-format-by-model]]` — this skill assumes the