Guidelines To Prompt Large Language Models For Cod
ASecurity
Implement techniques from Guidelines to Prompt Large Language Models for Code Generation: An Empirical Characterization. Large Language Models (LLMs) are nowadays extensively used for various types of software engineering tasks, primarily code generation
Installs into .claude/skills of the current project.
Are you the author of Guidelines To Prompt Large Language Models For Cod?
Add the live security badge to your README. It updates with every re-scan.
[](https://www.skillsdirectory.com/skills/adu2021-guidelines-to-prompt-large-language-models-for-cod)
---
name: guidelines-to-prompt-large-language-models-for-cod
title: "Guidelines to Prompt Large Language Models for Code Generation: An Empirical Characterization"
version: 0.0.2
engine: skillxiv-v0.0.2-claude-opus-4.6
license: MIT
url: "https://arxiv.org/abs/2601.13118"
keywords: ["model"]
description: "Implement techniques from Guidelines to Prompt Large Language Models for Code Generation: An Empirical Characterization. Large Language Models (LLMs) are nowadays extensively used for various types of software engineering tasks, primarily code generation"
---
## Overview
This skill implements concepts from the research paper [[2601.13118](https://arxiv.org/abs/2601.13118)].
## When to Use
- When you need to implement techniques described in this paper
- When working on problems that this research addresses
- When you want to understand the core concepts and methodology
## When NOT to Use
- This skill provides research-level insights; production implementations may require additional engineering
- Some concepts may require significant tuning for specific use cases
- Always evaluate applicability to your specific problem domain
## Key Concepts
The paper addresses: Large Language Models (LLMs) are nowadays extensively used for various types of software engineering tasks, primarily code generation. Previous research has shown how suitable prompt engineering could help developers in improving their code generatio...
For detailed methodology, refer to the [full paper](https://arxiv.org/html/2601.13118).