Individual skill
instructor
Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-tested structured output library
16-prompt-engineering/instructor/SKILL.md
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- Last checked
- Nov 9, 2026
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Repository context
- Repository stars (not skill ratings)
- 14,480
- Repository last updated
- Oct 11, 2026
- License
- MIT
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- ai Repository topic
- ai-research Repository topic
- claude Repository topic
- claude-code Repository topic
- claude-skills Repository topic
- codex Repository topic
- gemini Repository topic
- gpt-5 Repository topic
- grpo Repository topic
- huggingface Repository topic
- prompt-engineering Declared skill tag
- instructor Declared skill tag
- structured-output Declared skill tag
- pydantic Declared skill tag
- data-extraction Declared skill tag
- json-parsing Declared skill tag
- type-safety Declared skill tag
- validation Declared skill tag
- streaming Declared skill tag
- openai Declared skill tag
- anthropic Declared skill tag
- engineering Derived category
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Read excerpt
# Instructor: Structured LLM Outputs
## When to Use This Skill
Use Instructor when you need to:
- **Extract structured data** from LLM responses reliably
- **Validate outputs** against Pydantic schemas automatically
- **Retry failed extractions** with automatic error handling
- **Parse complex JSON** with type safety and validation
- **Stream partial results** for real-time processing
- **Support multiple LLM providers** with consistent API
**GitHub Stars**: 15,000+ | **Battle-tested**: 100,000+ developers