AI Prompt Library

This folder contains reusable AI prompts for:

• software engineering
• research
• academic work
• technical writing
• productivity
• debugging
• architecture guidance
• automation workflows

The prompts are designed for:

• Claude
• ChatGPT
• Cursor
• Windsurf
• Cline
• Roo
• OpenAI API agents
• Anthropic API agents

---

Purpose

This folder acts as a centralized AI prompt library to:

• organize reusable prompts
• standardize workflows
• improve output consistency
• reduce repetitive prompting
• reduce token waste
• improve research and engineering quality

---

Recommended Folder Structure

/prompts
 ├── README.md
 │
 ├── engineering
 │    ├── backend
 │    ├── frontend
 │    ├── security
 │    ├── testing
 │    ├── debugging
 │    ├── architecture
 │    └── workflows
 │
 ├── research
 │    ├── literature-review.md
 │    ├── source-analysis.md
 │    ├── hypothesis-generation.md
 │    ├── comparative-analysis.md
 │    ├── citation-support.md
 │    └── research-methodology.md
 │
 ├── academic
 │    ├── assignment-writing.md
 │    ├── report-writing.md
 │    ├── thesis-support.md
 │    ├── presentation-generation.md
 │    ├── study-guide.md
 │    ├── exam-preparation.md
 │    └── academic-editing.md
 │
 ├── writing
 │    ├── documentation.md
 │    ├── technical-writing.md
 │    ├── summarization.md
 │    ├── proofreading.md
 │    └── content-structuring.md
 │
 ├── productivity
 │    ├── planning.md
 │    ├── automation.md
 │    ├── brainstorming.md
 │    └── task-management.md
 │
 ├── templates
 │    ├── api-template.md
 │    ├── research-template.md
 │    ├── report-template.md
 │    ├── presentation-template.md
 │    └── architecture-template.md
 │
 └── misc
      ├── general-analysis.md
      ├── reasoning.md
      └── structured-output.md

---

Prompt Design Principles

Prompts should be:

• concise
• deterministic
• reusable
• domain-specific
• low ambiguity
• retrieval-friendly

Avoid:

• giant prompts
• duplicated instructions
• vague philosophy
• excessive examples
• unnecessary AI personality constraints

---

Prompt Writing Guidelines

Good prompts:

• define exact objectives
• define constraints clearly
• define output expectations
• minimize ambiguity

Bad prompts:

• are overly verbose
• contain conflicting instructions
• contain abstract motivational language
• attempt excessive personality control

---

Recommended Prompt Structure

Each prompt should include:

1. Purpose
2. Scope
3. Constraints
4. Rules
5. Anti-patterns
6. Output expectations

---

Example Prompt Layout

# Purpose

Generate structured academic reports.

---

# Constraints

- use formal academic tone
- include logical structure
- avoid unsupported claims

---

# Rules

- explain reasoning clearly
- cite assumptions when uncertain
- maintain factual consistency

---

# Avoid

- filler text
- unsupported conclusions
- excessive repetition

---

# Output Expectations

Generate:
- structured sections
- concise explanations
- academically formatted content

---

Engineering Prompt Guidelines

Engineering prompts should prioritize:

• maintainability
• correctness
• security
• architecture consistency
• minimal token waste

Avoid:

• giant monolithic prompts
• vague “best practices”
• duplicated rules

---

Research Prompt Guidelines

Research prompts should:

• prioritize evidence-based reasoning
• separate facts from assumptions
• encourage source validation
• compare viewpoints objectively
• avoid hallucinated citations

Good research prompts:

• request structured analysis
• request limitations
• request confidence levels

---

Academic Prompt Guidelines

Academic prompts should:

• maintain formal structure
• avoid plagiarism
• encourage critical thinking
• prioritize clarity and logic
• support structured argumentation

Avoid:

• fabricated references
• unsupported conclusions
• excessive verbosity

---

Writing Prompt Guidelines

Writing prompts should:

• define audience clearly
• define tone clearly
• prioritize clarity
• maintain structure

Avoid:

• redundant explanations
• unnecessary filler
• inconsistent formatting

---

Why Modular Prompts Are Better

Small focused prompts perform better than giant prompt files.

Benefits:

• lower token usage
• fewer hallucinations
• better retrieval precision
• reduced instruction conflicts
• more predictable outputs

Load only prompts relevant to the task.

Example:

• research task → load research prompts only
• backend task → load engineering/backend prompts only
• academic report → load academic/report prompts only

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Recommended Usage

Engineering Work

Load:

engineering/backend/api.md
engineering/architecture/clean-architecture.md
engineering/security/api-security.md

---

Research Work

Load:

research/literature-review.md
research/source-analysis.md
research/comparative-analysis.md

---

Academic Writing

Load:

academic/report-writing.md
academic/academic-editing.md
writing/content-structuring.md

---

Naming Conventions

Prompt filenames should be:

• short
• explicit
• domain-oriented

Good:

react.md
literature-review.md
report-writing.md

Bad:

misc.md
general-rules.md
random-prompts.md

---

Anti-Patterns

Avoid:

• giant prompt collections in one file
• duplicated instructions
• conflicting constraints
• vague AI philosophy
• excessive framework dumping

These increase:

• token usage
• hallucinations
• retry loops
• inconsistency

---

Expected Benefits

A properly structured prompt library improves:

• consistency
• output quality
• maintainability
• retrieval efficiency
• workflow speed

And reduces:

• repetitive prompting
• token waste
• architecture drift
• hallucinations

---

Final Principle

The best AI prompt libraries are:

• modular
• concise
• domain-specific
• deterministic
• retrieval-friendly
• easy to maintain

Not giant collections of AI philosophy or duplicated rules.