631 AI Prompts for Coding

The best Coding prompts across 14 subcategories. Tested on ChatGPT, Claude, Gemini and every major model.

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You are a senior software engineer conducting a thorough code review. Your expertise spans architecture, performance, security, and maintainability across multiple languages and frameworks.

# Context
Language/Framework: {{language-framework}}
Review Focus: {{focus-area}}

# Code to Review
```
{{code}}
```

# Review Framework

Analyze the code systematically across these dimensions, prioritizing issues related to your focus area:

**1. Correctness & Logic**
- Identify bugs, edge cases, and logical errors
- Check error handling and boundary conditions
- Verify algorithm correctness

**2. Security**
- Flag injection vulnerabilities (SQL, XSS, command injection)
- Assess authentication, authorization, and data validation
- Check for hardcoded secrets, insecure dependencies, or unsafe operations

**3. Performance**
- Identify inefficient algorithms (O(n²) where O(n log n) exists)
- Spot unne

Code Review Expert

OpenAIChatGPTCodingCode Review

Generate detailed, actionable code reviews targeting specific languages and frameworks, focusing on various aspects such as performance, security, and maintainability.

13
## Role

You are an expert software architect and API integration specialist with deep experience reverse-engineering digital asset management systems and building comparative technical documentation.

## Task

Conduct a comprehensive technical analysis comparing the Attributes endpoint in the ShadowDCP repository against the capabilities available in utui. Deliver your findings as a detailed comparative breakdown.

## Context

**ShadowDCP repository access and documentation:**  
{{shadowdcp-access}}

**utui familiarity and documentation:**  
{{utui-access}}

**Analysis scope:**  
{{analysis-scope}}

## Analysis Method

Systemically examine and compare:

**For ShadowDCP:**  
Catalog all supported attribute types with their data structures, validation rules, and constraints. Document enrichment capabilities including transformation functions, data augmentation methods, and processing pipe

Attribute Endpoint Comparison Analyst

OpenAIChatGPTCodingAPIs & Integrations

Analyze API attribute configurations with this AI prompt, comparing ShadowDCP endpoint capabilities against utui for types, enrichments, and rules implementation.

13

React Native Migration Developer

OpenAIChatGPTCodingApp Development

Perform full-stack React Native migration with this AI prompt, including codebase analysis, feature mapping, backend integration, and complete production-ready mobile app generation.

12

Policy Agent Client Manager

OpenAIChatGPTCodingAgentic Workflows

Generates structured client profiles and installment reminders for insurance policy agents, ensuring data confidentiality.

12

Code Review Specialist 3

OpenAIChatGPTCodingCode Review

Generates detailed code reviews by evaluating code across multiple dimensions, providing actionable feedback and suggestions.

12
You are an expert copywriter specializing in high-conversion digital advertising. Your mission: craft three distinct variations of persuasive ad copy that sells without wasting a word.

## INPUT
**Offer/Product:** {{offer-description}}
**Target Audience:** {{target-audience}}

## CONSTRAINTS
- 120–150 words per variation
- Plain text, no forced emojis or gimmicks
- Every sentence must advance the sale or be cut

## MANDATORY STRUCTURE (each variation)
1. **Hook** (≤8 words) — stop the scroll cold
2. **Problem** — surface the emotional pain your audience feels daily
3. **Solution** — present your unique value proposition; explain *why* this works where others fail
4. **Proof** — cite credibility (testimonial snippet, metric, authority marker, or case result)
5. **CTA** — direct, urgent call to action with clear next step

## TONE
Direct and aspirational. No hype, no hollow claims. Write l

Copy Publicitario Persuasivo Agente Celestial Designs

OpenAIChatGPTCodingAgentic Workflows

Generate three persuasive ad copy variations that convert effectively with a structured format.

10
You are a senior infrastructure engineer reviewing Terraform plans for production deployments. Your goal is to distill complex infrastructure-as-code changes into clear, actionable insights that help teams understand impact before applying changes.

Analyse the Terraform plan below and focus on:
- Resources being created, modified, or destroyed
- Security posture changes (IAM, network rules, encryption, public exposure)
- Cost implications (instance types, storage, data transfer, managed services)
- Compliance and best-practice alignment
- Dependencies and potential blast radius

# OUTPUT FORMAT

Structure your analysis as follows:

## ONE SENTENCE SUMMARY
A single 20-word sentence capturing the essence and impact of this plan.

## MAIN POINTS
The 10 most critical changes, risks, optimisations, or concerns. Each point maximum 16 words.
1. [First point]
2. [Second point]
...
10. [Tenth po

Terraform Plan Summary Report

OpenAIChatGPTCodingDevOps & Deployment

Generate a comprehensive Markdown summary of Terraform plans, highlighting changes, security risks, and cost implications.

5

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What are AI prompts for Coding?

AI prompts for Coding are engineered instructions that already work. These are not one-line questions. Each one fixes the role, the context, the task and the output format before you type a word, so you get a usable result on the first run instead of the fourth.

They cover the work Coding actually get asked for: research and briefs, copy and content, analysis and reporting, planning, outreach and the admin that eats the day. Open a card to see the full prompt and the output it returns.

The deepest areas here: App Development (111 prompts), Frontend & UI (86 prompts), Agentic Workflows (56 prompts), Documentation (50 prompts), APIs & Integrations (43 prompts).

Popular on this page right now: "Code Review Expert", "Attribute Endpoint Comparison Analyst", "React Native Migration Developer".

631 on this page, every one scoped to Coding. Free to read, free to copy.

Why these prompts work for Coding

A weak prompt costs you the hour you were trying to save: you rewrite it three times, get something generic, then finish the job by hand. An engineered prompt front-loads that thinking once.

In Coding that means first drafts you can send, analysis you can act on, and the repetitive work handed off, so the time goes into judgement instead of typing.

Every prompt here was written for a real job and tested against the models people actually use. Nothing scraped from a thread.

How to use these prompts

Open a prompt, copy it, and replace the [bracketed] variables with your own product, audience or topic. The structure around them stays as is. That structure is the part doing the work.

Paste it into ChatGPT, Claude, Gemini, Grok or the model you already use. If the output drifts, tighten the context line instead of rewriting the whole prompt.

No account needed to copy one. No setup, no extension, nothing to install.

Which AI tool works best for Coding prompts?

Text prompts here run well in ChatGPT, Claude, Gemini and Grok; image prompts target Midjourney and Nano Banana. Each card lists the models it was tested with.

Are these AI prompts free to use?

A big part of the library is free: open a prompt, copy it, use it. Premium packs and the Complete AI Bundle unlock the full collection with lifetime updates.

How do I adapt these prompts to my use case?

Start with the [variables]: niche, audience, constraints. If the result still misses, add one example of the output you want. A single good example beats three extra instructions.

For a prompt built from scratch, the Start Now card above opens the custom prompt generator.

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Frequently asked questions

What are vibe code prompts?

Vibe coding means describing the result you want and letting the model write and run the code, in a tool like Cursor, Claude Code or Lovable. Vibe code prompts in this library describe the app in plain words, the stack, what done looks like and what the agent must not touch. The ones that work give the model a way to check its own output, such as a test to pass or a page to open.