Guidelines for creating effective prompts that maximize AI understanding and response quality. Helps developers craft clear, specific, actionable prompts with appropriate context for optimal AI assistance.
--- name: prompt-optimization description: Guidelines for creating effective prompts that maximize AI understanding and response quality. Helps developers craft clear, specific, actionable prompts with appropriate context for optimal AI assistance. license: MIT metadata: author: Claude Code version: "1.0.0" --- # Prompt Optimization Guide Comprehensive guide for crafting high-quality prompts that maximize AI understanding and effectiveness. Contains best practices for clarity, context, structure, and tactical approaches to prompt engineering. ## When to Apply Reference these guidelines when: - Crafting initial prompts for complex tasks - Improving AI response quality and accuracy - Training team members on effective AI interaction - Iterating on prompts that aren't producing desired results - Creating reusable prompt templates ## Rule Categories by Priority | Priority | Category | Impact | Prefix | |----------|----------|--------|--------| | 1 | Clarity and Precision | CRITICAL | `clarity-` | | 2 | Context Provisioning | CRITICAL | `context-` | | 3 | Structure and Formatting | HIGH | `structure-` | | 4 | Tactical Tips | MEDIUM | `tactical-` | | 5 | Examples and Patterns | MEDIUM | `example-` | | 6 | Advanced Techniques | HIGH | `advanced-` | ## Quick Reference ### 1. Clarity and Precision (CRITICAL) - `clarity-specific-language` - Use precise terminology instead of vague concepts - `clarity-define-terms` - Define technical terms or acronyms - `clarity-clear-objectives` - State specific goals and expectations - `clarity-avoid-ambiguity` - Eliminate vague pronouns and references ### 2. Context Provisioning (CRITICAL) - `context-project-info` - Include relevant project background - `context-current-state` - Describe current situation and constraints - `context-goals-outcomes` - Specify desired outcomes and success criteria - `context-priorities-tradeoffs` - Explain important priorities and trade-offs ### 3. Structure and Formatting (HIGH) - `structure-segmentation` - Break complex requests into logical sections - `structure-order-of-info` - Present information in logical sequence - `structure-formatting-visual` - Use markdown for readability - `structure-sequential-steps` - Number steps when sequence matters ### 4. Tactical Tips (MEDIUM) - `tactical-role-definition` - Assign specific roles to AI - `tactical-expectation-setting` - Explicitly state output format - `tactical-feedback-loops` - Include iteration and refinement cycles - `tactical-constraints-clarification` - Clearly define limitations ### 5. Examples and Patterns (MEDIUM) - `example-good-vs-bad` - Compare effective and ineffective approaches - `example-template-patterns` - Provide reusable prompt templates - `example-industry-specific` - Show domain-specific best practices - `example-error-patterns` - Highlight common mistakes to avoid ### 6. Advanced Techniques (HIGH) ## How to Use Follow the systematic approach outlined in USAGE.md for consistent prompt optimization results.--- name: prompt-optimization description: Guidelines for creating effective prompts that maximize AI understanding and response quality. Helps developers craft clear, specific, actionable prompts with appropriate context for optimal AI assistance. license: MIT metadata: author: Claude Code version: "1.0.0" --- # Prompt Optimization Guide Comprehensive guide for crafting high-quality prompts that maximize AI understanding and effectiveness. Contains best practices for clarity, context, structure, and tactical approaches to prompt engineering. ## When to Apply Reference these guidelines when: - Crafting initial prompts for complex tasks - Improving AI response quality and accuracy - Training team members on effective AI interaction - Iterating on prompts that aren't producing desired results - Creating reusable prompt templates ## Rule Categories by Priority | Priority | Category | Impact | Prefix | |----------|----------|--------|--------| | 1 | Clarity and Precision | CRITICAL | `clarity-` | | 2 | Context Provisioning | CRITICAL | `context-` | | 3 | Structure and Formatting | HIGH | `structure-` | | 4 | Tactical Tips | MEDIUM | `tactical-` | | 5 | Examples and Patterns | MEDIUM | `example-` | | 6 | Advanced Techniques | HIGH | `advanced-` | ## Quick Reference ### 1. Clarity and Precision (CRITICAL) - `clarity-specific-language` - Use precise terminology instead of vague concepts - `clarity-define-terms` - Define technical terms or acronyms - `clarity-clear-objectives` - State specific goals and expectations - `clarity-avoid-ambiguity` - Eliminate vague pronouns and references ### 2. Context Provisioning (CRITICAL) - `context-project-info` - Include relevant project background - `context-current-state` - Describe current situation and constraints - `context-goals-outcomes` - Specify desired outcomes and success criteria - `context-priorities-tradeoffs` - Explain important priorities and trade-offs ### 3. Structure and Formatting (HIGH) - `structure-segmentation` - Break complex requests into logical sections - `structure-order-of-info` - Present information in logical sequence - `structure-formatting-visual` - Use markdown for readability - `structure-sequential-steps` - Number steps when sequence matters ### 4. Tactical Tips (MEDIUM) - `tactical-role-definition` - Assign specific roles to AI - `tactical-expectation-setting` - Explicitly state output format - `tactical-feedback-loops` - Include iteration and refinement cycles - `tactical-constraints-clarification` - Clearly define limitations ### 5. Examples and Patterns (MEDIUM) - `example-good-vs-bad` - Compare effective and ineffective approaches - `example-template-patterns` - Provide reusable prompt templates - `example-industry-specific` - Show domain-specific best practices - `example-error-patterns` - Highlight common mistakes to avoid ### 6. Advanced Techniques (HIGH) ## How to Use Follow the systematic approach outlined in USAGE.md for consistent prompt optimization results.
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.