Constrain LLM outputs with regex and grammar rules for structured formats.
npx skills add https://github.com/zerwiz/wayofpi --skill guidance-zerwiz
Please help me install this Agent Skill. Skill: guidance Source: https://github.com/zerwiz/wayofpi/tree/main/.hermes/hermes-agent/optional-skills/mlops/guidance Command: npx skills add https://github.com/zerwiz/wayofpi --skill guidance-zerwiz
This Skill helps you make LLMs produce reliable, structured outputs instead of free-form text that can break downstream systems, waste retries, or fail validation.
Ask this skill to create a constrained Guidance workflow for your chosen model, output format, and validation rules.
High-intent search queries and answers about installing and using this skill.
To force valid structured output, apply grammar and regex constraints during constrained generation. This guarantees the LLM emits valid JSON, XML, or specific formats without breaking downstream systems or failing validation.
Yes, constrained generation workflows apply across API and local model backends. You can use the same regex and grammar constraints across Anthropic, OpenAI, Transformers, and llama.cpp setups for consistent structured output.
Token healing fixes unconstrained LLM generation by correcting token boundaries during inference. It prevents format-breaking artifacts, ensuring generated text aligns with required grammar, regex, and structured output constraints.
Build multi-step LLM workflows by composing reusable Pythonic generation functions for extraction and classification. This routes inputs like customer emails into clean JSON entities without manual cleanup or wasted retries.
Yes, constrained generation supports selection-based branching for agent loops. You can enforce grammar constraints on dynamic choices, allowing reliable multi-step prompt execution and structured control flow within LLM agents.
LLM output breaks required formats due to unconstrained generation producing free-form text. Applying hard constraints via regex and grammar rules forces the model to satisfy validation rules, preventing downstream system failures.
pmcdowallEnforce structured output formats and validation constraints on language model generation.
HKUDSSummarize URLs, YouTube videos, PDFs, and text files into concise overviews.
GregsGreyCodeEnforce regex and grammar constraints on LLM outputs for structured JSON, XML, and code.
Clay-HHKServe LLMs with prefix caching and constrained JSON, regex, or grammar outputs.
