AI Prompt Engineering Cheatsheet: Essential Action Verbs for Better Results
Effective AI prompt engineering requires precise action verbs to eliminate ambiguity and improve output quality. This cheatsheet categorizes 60+ essential verbs across eight functional domains with comparative examples demonstrating improved prompt construction.
Methodology
Action verbs are categorized by cognitive and operational functions. Each category includes weak versus strong prompt examples demonstrating measurable improvement in specificity and output quality.
Verb Categories and Applications
Analysis & Understanding
Function: Information examination and interpretation Implementation: Replace vague requests with specific analytical tasks
Weak: Tell me about this code
Strong: Analyze this Python function for security vulnerabilities and performance bottlenecks
Creation & Generation
Function: Novel content and solution development Implementation: Specify deliverable type, constraints, and success criteria
Weak: Make a website layout
Strong: Design a responsive landing page layout for SaaS product with hero section, feature highlights, and CTA buttons
Explanation & Teaching
Function: Knowledge transfer and conceptual clarification Implementation: Define audience expertise level and learning objectives
Weak: What is Docker?
Strong: Explain Docker containerization to a developer familiar with VMs, including key benefits and basic commands
Problem-Solving
Function: Issue resolution and optimization Implementation: Identify specific problems and define optimization targets
Weak: This code isn't working
Strong: Debug this React component causing infinite re-renders and optimize for performance
Information Processing
Function: Data transformation and content manipulation Implementation: Specify input format, desired output, and transformation parameters
Weak: Change this text
Strong: Rewrite technical blog post for non-technical audience while preserving key concepts
Reasoning & Logic
Function: Evidence-based analysis and conclusion generation Implementation: Request logical frameworks and justification criteria
Weak: What do you think will happen?
Strong: Predict microservices implementation outcomes based on current team size and technical constraints
Creative Tasks
Function: Original ideation and innovative solution development Implementation: Define creative constraints and evaluation criteria
Weak: Give me some ideas
Strong: Brainstorm 10 innovative features for project management tool targeting remote software teams
Research & Discovery
Function: Information gathering and synthesis Implementation: Specify scope, sources, and synthesis requirements
Weak: Find information about React
Strong: Research React 18 features and compile comparison with React 17 focusing on performance improvements
Optimization Strategies
Verb Combination: Layer multiple verbs for complex tasks
Analyze user feedback data, categorize issues by severity, generate actionable recommendations
Context Specification: Include technical constraints and success metrics
Optimize database query for high-traffic e-commerce site (10M+ daily users) focusing on read performance
Quick Reference: Complete Verb Taxonomy
| Category | Primary Function | Complete Verb Set |
|---|---|---|
| Analysis & Understanding | Information examination | analyze, evaluate, examine, interpret, compare, contrast, critique, investigate, diagnose, identify, distinguish, categorize, classify, assess |
| Creation & Generation | Content development | create, generate, write, compose, draft, develop, design, formulate, devise, build, synthesize, compile, construct |
| Explanation & Teaching | Knowledge transfer | explain, describe, clarify, illustrate, demonstrate, teach, guide, walk through, break down, simplify, elaborate, define, outline, summarize |
| Problem-Solving | Issue resolution | solve, troubleshoot, debug, fix, resolve, optimize, improve, refine, streamline, transform, convert, adapt, modify, refactor |
| Information Processing | Data manipulation | extract, organize, structure, format, condense, expand, translate, paraphrase, rewrite, edit, revise, fact-check, compile |
| Reasoning & Logic | Evidence-based analysis | reason, deduce, infer, conclude, predict, calculate, determine, validate, verify, justify, argue, reflect, chain |
| Creative Tasks | Innovation and ideation | brainstorm, imagine, innovate, conceive, invent, reimagine, roleplay, simulate, model, visualize, prototype, storyboard |
| Research & Discovery | Information gathering | research, investigate, explore, search, find, discover, trace, track, locate, gather, curate, contextualize |
| Process & Coordination | Task management | iterate, prioritize, orchestrate, systematize, decompose, sequence, coordinate, schedule, delegate |
Claude-Specific Optimizations
Leveraging Claude's Strengths:
- Parallel processing: Use "orchestrate" for multi-tool coordination
- Extended context: Apply "contextualize" for large document analysis
- Structured thinking: Employ "chain" for step-by-step reasoning
- Reflection capabilities: Utilize "reflect" for self-assessment and iteration
- Format control: Implement "structure" and "format" with XML tags
Claude-Optimized Verb Combinations:
Analyze this codebase, then decompose the issues by priority, and systematize solutions for each component
Error Prevention
Common Failures:
- Vague verb usage ("help me with")
- Multiple conflicting objectives
- Insufficient context specification
- Absence of success criteria
Mitigation: Apply specific verbs with defined parameters, constraints, and measurable outcomes.
Conclusion
Precise verb selection significantly improves AI prompt effectiveness. Implementation of this taxonomy enhances output quality through reduced ambiguity and improved task specification. Claude 4 models respond well to clear, explicit instructions and benefit from structured, specific prompting approaches.