Claude-Code-Workflow/.claude/commands/enhance-prompt.md

name: enhance-prompt description: Dynamic prompt enhancement for complex requirements - Structured enhancement of user prompts before agent execution usage: /enhance-prompt <user_input> argument-hint: [--gemini] "user input to enhance" examples: - /enhance-prompt "add user profile editing" - /enhance-prompt "fix login button" - /enhance-prompt "clean up the payment code"

🚀 Command Overview: /enhance-prompt

• Type: Prompt Engineering Command
• Purpose: To systematically enhance raw user prompts, translating them into clear, context-rich, and actionable specifications before agent execution.
• Key Feature: Dynamically integrates with Gemini for deep, codebase-aware analysis.

📥 Command Parameters

• <user_input>: (Required) The raw text prompt from the user that needs enhancement.
• --gemini: (Optional) An explicit flag to force the full Gemini collaboration flow, ensuring codebase analysis is performed even for simple prompts.

🔄 Core Enhancement Protocol

This is the standard pipeline every prompt goes through for structured enhancement.

Step 1: Intent Translation -> Step 2: Context Extraction -> Step 3: Key Points Identification -> Step 4: Optional Gemini Consultation

🧠 Gemini Collaboration Logic

This logic determines when to invoke Gemini for deeper, codebase-aware insights.

FUNCTION decide_enhancement_path(user_prompt, options):
  // Set of keywords that indicate high complexity or architectural changes.
  critical_keywords = ["refactor", "migrate", "redesign", "auth", "payment", "security"]

  // Conditions for triggering Gemini analysis.
  use_gemini = FALSE
  IF options.gemini_flag is TRUE:
    use_gemini = TRUE
  ELSE IF prompt_affects_multiple_modules(user_prompt, threshold=3):
    use_gemini = TRUE
  ELSE IF any_keyword_in_prompt(critical_keywords, user_prompt):
    use_gemini = TRUE

  // Execute the appropriate enhancement flow.
  enhanced_prompt = run_standard_enhancement(user_prompt) // Steps 1-3

  IF use_gemini is TRUE:
    // This action corresponds to calling the Gemini CLI tool programmatically.
    // e.g., `gemini --all-files -p "..."` based on the derived context.
    gemini_insights = execute_tool("gemini", enhanced_prompt) // Calls the Gemini CLI
    enhanced_prompt.append(gemini_insights)

  RETURN enhanced_prompt
END FUNCTION

📚 Enhancement Rules

• Ambiguity Resolution: Generic terms are translated into specific technical intents.
  • "fix" → Identify the specific bug and preserve existing functionality.
  • "improve" → Enhance performance or readability while maintaining compatibility.
  • "add" → Implement a new feature and integrate it with existing code.
  • "refactor" → Restructure code to improve quality while preserving external behavior.
• Implicit Context Inference: Missing technical context is automatically inferred.

  # User: "add login"
  # Inferred Context:
  # - Authentication system implementation
  # - Frontend login form + backend validation
  # - Session management considerations
  # - Security best practices (e.g., password handling)
  

• Technical Translation: Business goals are converted into technical specifications.

  # User: "make it faster"
  # Translated Intent:
  # - Identify performance bottlenecks
  # - Define target metrics/benchmarks
  # - Profile before optimizing
  # - Document performance gains and trade-offs
  

🗺️ Enhancement Translation Matrix

User Says	→ Translate To	Key Context	Focus Areas
"make it work"	Fix functionality	Debug implementation	Root cause → fix → test
"add [feature]"	Implement capability	Integration points	Core function + edge cases
"improve [area]"	Optimize/enhance	Current limits	Measurable improvements
"fix [bug]"	Resolve issue	Bug symptoms	Root cause + prevention
"refactor [code]"	Restructure quality	Structure pain points	Maintain behavior
"update [component]"	Modernize	Version compatibility	Migration path

⚡ Automatic Invocation Triggers

The /enhance-prompt command is designed to run automatically when the system detects:

• Ambiguous user language (e.g., "fix", "improve", "clean up").
• Tasks impacting multiple modules or components (>3).
• Requests for system architecture changes.
• Modifications to critical systems (auth, payment, security).
• Complex refactoring requests.

🛠️ Gemini Integration Protocol (Internal)

Core Principles: @~/.claude/workflows/core-principles.md

This section details how the system programmatically interacts with the Gemini CLI.

• Primary Tool: All Gemini analysis is performed via direct calls to the gemini command-line tool (e.g., gemini --all-files -p "...").
• Central Guidelines: All CLI usage patterns, syntax, and context detection rules are defined in the central guidelines document:
• Specialized Templates: For specific analysis types, the system references dedicated templates:
  • Pattern/Architecture: gemini-core-templates.md
  • Security: gemini-core-templates.md (for vulnerability scanning)
  • Documentation: gemini-dms-templates.md

📝 Enhancement Examples

This card contains the original, unmodified examples to demonstrate the command's output.

Example 1: Feature Request (with Gemini Integration)

# User Input: "add user profile editing"

# Standard Enhancement:
TRANSLATED_INTENT: Implement user profile editing feature
DOMAIN_CONTEXT: User management system
ACTION_TYPE: Create new feature
COMPLEXITY: Medium (multi-component)

# Gemini Analysis Added:
GEMINI_PATTERN_ANALYSIS: FormValidator used in AccountSettings, PreferencesEditor
GEMINI_ARCHITECTURE: UserService → ProfileRepository → UserModel pattern

# Final Enhanced Structure:
ENRICHED_CONTEXT:
- Frontend: Profile form using FormValidator pattern
- Backend: API endpoints following UserService pattern
- Database: User model via ProfileRepository
- Auth: Permission checks using AuthGuard pattern

KEY_POINTS:
- Data validation using existing FormValidator
- Image upload via SecureUploadService
- Field permissions with AuthGuard middleware

ATTENTION_AREAS:
- Security: Use SecureUploadService for file handling
- Performance: Lazy loading patterns (ProfileImage.tsx)

Example 2: Bug Fix

# User Input: "login button doesn't work"

# Enhanced Structure:
TRANSLATED_INTENT: Debug and fix non-functional login button
DOMAIN_CONTEXT: Authentication UI
ACTION_TYPE: Fix bug
COMPLEXITY: Simple (single component)

KEY_POINTS:
- Identify root cause (event/state/API)
- Preserve existing auth flow
- Add error handling if missing

ATTENTION_AREAS:
- Don't break existing functionality
- Test edge cases and user states

Example 3: Refactoring Request

# User Input: "clean up the payment code"

# Enhanced Structure:
TRANSLATED_INTENT: Refactor payment module for maintainability
DOMAIN_CONTEXT: Payment processing system
ACTION_TYPE: Refactor
COMPLEXITY: Complex (critical system)

KEY_POINTS:
- Maintain exact functionality
- Improve code organization
- Extract reusable components

ATTENTION_AREAS:
- Critical: No behavior changes
- Security: Maintain PCI compliance
- Testing: Comprehensive coverage

✨ Key Benefits

1. Clarity: Ambiguous requests become clear specifications.
2. Completeness: Implicit requirements become explicit.
3. Context: Missing context is automatically inferred.
4. Codebase Awareness: Gemini provides actual patterns from the project.
5. Quality: Attention areas prevent common mistakes.
6. Efficiency: Agents receive structured, actionable input.
7. Smart Flow Control: Seamless integration with workflows.