Extract structured data from LLM responses and validate against Pydantic schemas.
npx skills add https://github.com/zerwiz/wayofpi --skill instructor-zerwiz
Please help me install this Agent Skill. Skill: instructor Source: https://github.com/zerwiz/wayofpi/tree/main/.hermes/hermes-agent/optional-skills/mlops/instructor Command: npx skills add https://github.com/zerwiz/wayofpi --skill instructor-zerwiz
Instructor turns unreliable model text into structured, validated data so you can trust LLM outputs instead of manually cleaning and retrying them.
Use Instructor to extract a validated structured object from a model response with automatic retry handling.
High-intent search queries and answers about installing and using this skill.
You extract structured data from LLM responses by mapping model outputs directly into typed Pydantic models. This enforces type safety and ensures consistent downstream processing without manual cleaning.
The best way to validate LLM output is using automatic validation and retries. This catches malformed fields, feeds errors back to the model, and recovers from bad outputs without manual intervention.
Yes, structured output validation supports both Anthropic and OpenAI providers. It handles streaming and partial results across these providers, as well as local model setups, for production workflows.
Yes, you need Pydantic models to parse type-checked data from LLMs. They are required to define the typed schemas used for schema-driven extraction and validation against model responses.
LLM data extraction fails without automatic retry handling because model text is inherently unreliable. Without validation and error feedback loops, malformed outputs break downstream parsing and require manual intervention.
NovaAI-innovationInteract with OpenAI, Anthropic, Google, and Ollama LLM providers.
twjarviszyra-webExtract LLM responses into validated Pydantic objects with automatic retries.
tadod12Extract structured data from LLM responses with Pydantic validation and automatic retries.
telum-aiIntegrate OpenAI and Anthropic Claude APIs for structured outputs, streaming, and function calling.
