guidance
CommunityControl LLM output with precision.
Software Engineering#prompt engineering#grammar#llm#structured output#json validation#constrained generation
AuthorAum08Desai
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill allows you to precisely control the output of Large Language Models (LLMs) by enforcing specific formats, structures, and constraints, ensuring reliable and predictable generation.
Core Features & Use Cases
- Constrained Generation: Guarantee valid JSON, XML, or code output using regex and grammars.
- Structured Data: Enforce specific formats for dates, emails, IDs, and more.
- Multi-Step Workflows: Build complex conversational agents and automated processes with Pythonic control flow.
- Use Case: Generate a JSON object representing a user profile, ensuring all fields (name, age, email) adhere to strict validation rules before the output is accepted.
Quick Start
Use the guidance skill to generate a JSON object for a user with name, age, and email.
Dependency Matrix
Required Modules
None requiredComponents
references
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: guidance Download link: https://github.com/Aum08Desai/hermes-research-agent/archive/main.zip#guidance Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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