Generate and Refine Code Prompts
A curated library of role-based, task-specific, and prompt-engineering templates for common dev and writing tasks.
Why it matters
Leverage a curated library of battle-tested prompts to enhance code generation, debugging, testing, and documentation tasks. Improve your AI interactions for better software development outcomes.
Outcomes
What it gets done
Access expert developer and code reviewer prompts.
Utilize task-specific prompts for debugging and test generation.
Employ analysis prompts for code complexity and performance.
Generate prompts for creative brainstorming and naming.
Install
Add it to your toolbox
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/ag-prompt-library | bash Overview
Prompt Library
A curated library of role-based, task-specific, analysis, creative, and transformation prompt templates, plus named prompt-engineering techniques like Chain of Thought, Few-Shot Learning, and the Persona Pattern. Use it when a ready-to-use prompt template or prompt-engineering technique is needed rather than writing a prompt from scratch.
What it does
A curated library of battle-tested prompt templates, inspired by the community awesome-chatgpt-prompts collection. Role-based prompts include an Expert Developer prompt for code review (identify bugs, suggest performance improvements, recommend better patterns), a Code Reviewer prompt formatted into red/yellow/green severity tiers, a Technical Writer prompt for turning technical concepts into accessible documentation, and a System Architect prompt weighing scalability, reliability, maintainability, performance, and cost with explicit trade-off analysis.
Task-specific prompts include Debug This Code (problem identification, root cause, fix, and prevention), Explain Like I'm 5, Code Refactoring (readability first, remove duplication, single responsibility, meaningful names), Write Tests (happy-path scenarios, edge cases, error conditions, boundary values, arrange-act-assert structure), and API Documentation generation formatted as OpenAPI/Swagger or Markdown. Analysis prompts cover Code Complexity Analysis (cyclomatic complexity, coupling, cohesion, dependencies, technical debt), Performance Analysis (time and space complexity, I/O bottlenecks, algorithmic issues, quick wins), and a Security Review across input validation, authentication and authorization, data protection, and injection vulnerabilities, classified by severity. Creative prompts cover Brainstorm Features (ranked by impact-to-effort ratio) and a Name Generator across descriptive, evocative, acronym, and metaphorical categories. Transformation prompts cover migrating code between languages and converting between data formats, both requiring exact functionality or data preservation and edge-case handling.
It closes with four named prompt-engineering techniques - Chain of Thought, Few-Shot Learning, the Persona Pattern, and Structured Output for JSON-schema responses - and a six-point prompt-improvement checklist covering clear objective, context, format, examples, constraints, and success criteria.
When to use - and when NOT to
Use it when a ready-to-use prompt template is needed - a role-based persona, a task-specific pattern (debugging, refactoring, test-writing, documentation), an analysis prompt, or a prompt-engineering technique - rather than writing a prompt from scratch.
Inputs and outputs
Input: a task or persona needing a prompt template, with placeholders like [CONCEPT], [PRODUCT], [SOURCE]/[TARGET] to fill in. Output: a ready-to-use prompt template, filled in with the specifics of the current task. A Few-Shot Learning template, for instance, structures the fill-in as numbered input/output example pairs followed by the actual input to complete, rather than a single instruction.
Integrations
Built on and credits the community awesome-chatgpt-prompts GitHub repository, with prompts.chat and Learn Prompting listed as further-reading resources for prompt engineering.
Who it's for
Anyone who wants a ready-made prompt for a common task - code review, debugging, documentation, brainstorming - or a reusable pattern like Chain of Thought, Few-Shot, or Persona to structure a new one.
FAQ
Common questions
Discussion
Questions & comments · 0
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