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Transform vague prompts into actionable specs using intelligent analysis and session memory. Use when user input contains -e or --enhance flag.

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SKILL.md

name Prompt Enhancer
description Transform vague prompts into actionable specs using intelligent analysis and session memory. Use when user input contains -e or --enhance flag.
allowed-tools (none)

Prompt Enhancer

Transform: Vague intent → Structured specification (Memory-based, Direct Output)

Languages: English + Chinese (中英文语义识别)

Process (Internal → Direct Output)

Internal Analysis: Intelligently extract session context, identify tech stack, and structure into actionable format.

Output: Direct structured prompt (no intermediate steps shown)

Output Format

Dynamic Structure: Adapt fields based on task type and context needs. Not all fields are required.

Core Fields (always present):

  • INTENT: One-sentence technical goal
  • ACTION: Concrete steps with technical details

Optional Fields (include when relevant):

  • TECH STACK: Relevant technologies (when tech-specific)
  • CONTEXT: Session memory findings (when context matters)
  • ATTENTION: Critical constraints (when risks/requirements exist)
  • SCOPE: Affected modules/files (for multi-module tasks)
  • METRICS: Success criteria (for optimization/performance tasks)
  • DEPENDENCIES: Related components (for integration tasks)

Example (Simple Task):

📋 ENHANCED PROMPT

INTENT: Fix authentication token validation in JWT middleware

ACTION:
1. Review token expiration logic in auth middleware
2. Add proper error handling for expired tokens
3. Test with valid/expired/malformed tokens

Example (Complex Task):

📋 ENHANCED PROMPT

INTENT: Optimize API performance with caching and database indexing

TECH STACK:
- Redis: Response caching
- PostgreSQL: Query optimization

CONTEXT:
- API response times >2s mentioned in previous conversation
- PostgreSQL slow query logs show N+1 problems

ACTION:
1. Profile endpoints to identify slow queries
2. Add PostgreSQL indexes on frequently queried columns
3. Implement Redis caching for read-heavy endpoints
4. Add cache invalidation on data updates

METRICS:
- Target: <500ms API response time
- Cache hit ratio: >80%

ATTENTION:
- Maintain backward compatibility with existing API contracts
- Handle cache invalidation correctly to avoid stale data

Workflow

Trigger (-e/--enhance) → Internal Analysis → Dynamic Output
         ↓                       ↓                  ↓
   User Input           Assess Task Type      Select Fields
                    Extract Memory Context    Structure Prompt
  1. Detect: User input contains -e or --enhance
  2. Analyze:
    • Determine task type (fix/optimize/implement/refactor)
    • Extract relevant session context
    • Identify tech stack and constraints
  3. Structure:
    • Always include: INTENT + ACTION
    • Conditionally add: TECH STACK, CONTEXT, ATTENTION, METRICS, etc.
  4. Output: Present dynamically structured prompt

Enhancement Guidelines (Internal)

Always Include:

  • Clear, actionable INTENT
  • Concrete ACTION steps with technical details

Add When Relevant:

  • TECH STACK: Task involves specific technologies
  • CONTEXT: Session memory provides useful background
  • ATTENTION: Security/compatibility/performance concerns exist
  • SCOPE: Multi-module or cross-component changes
  • METRICS: Performance/optimization goals need measurement
  • DEPENDENCIES: Integration points matter

Quality Checks:

  • Make vague intent explicit
  • Resolve ambiguous references
  • Add testing/validation steps
  • Include constraints from memory

Best Practices

  • ✅ Trigger only on -e/--enhance flags
  • ✅ Use dynamic field selection based on task type
  • ✅ Extract memory context ONLY (no file reading)
  • ✅ Always include INTENT + ACTION as core fields
  • ✅ Add optional fields only when relevant to task
  • ✅ Direct output (no intermediate steps shown)
  • ❌ NO tool calls
  • ❌ NO file operations (Bash, Read, Glob, Grep)
  • ❌ NO fixed template - adapt to task needs