Code Directory Explainer
Act as a code directory expert to explain the structure and components of a given codebase directory.
Tag Collection
9 published prompts tagged “Software engineering”. Browse by scenario and copy in one click.
9 prompts
Act as a code directory expert to explain the structure and components of a given codebase directory.
Act as a GitHub Code Tutor to help users understand code structure, function implementations, and provide modification suggestions.
Act as a career counselor to help users analyze skills, interests, and experience, and provide career advice, industry trends, and qualifications for software engineering.
A binding engineering policy distilled from Clean Code, Clean Architecture, Domain-Driven Design, and Designing Data-Intensive Applications. Enforces human-readable code, inward dependencies, explicit domain boundaries, and fault-tolerant data systems for AI-generated software.
Design a coordination system where humans provide direction via lightweight chat messages and autonomous coding agents ("claws") self-coordinate to plan, build, test, recover, and push code without micromanagement, emphasizing externalization of meta-tasks and context-window purity.
Transforms code, databases, infrastructure, and documentation into a structured knowledge graph, identifying architectural key points, dependencies, and design decisions.
A system prompt for a software engineering assistant embedded in the command-line development environment, guiding AI to complete programming tasks such as coding, debugging, refactoring, and test management. Emphasizes safe operations, cautious execution of changes, preference for dedicated tools, and requires output in GitHub-flavored Markdown format.
This prompt guides the model to act as a senior refactoring specialist who helps developers systematically improve maintainable but problematic code while preserving all existing behavior through safe, incremental transformations.
Professional prompt design and optimization framework covering the entire workflow from requirements analysis to production deployment, suitable for large language model systems in production environments.
They are reusable LLM prompt templates labeled with “Software engineering” in Easy Prompt, selected for practical workflows and clear structure.
Open a prompt, adjust variables or constraints for your context, then copy it into ChatGPT, Claude, or your internal model.
This page lists published prompts with the tag. Individual bulk-synced items may still be noindex; prefer structured templates with scoring rubrics when evaluating quality.