diff --git a/.claude/skills/prompt-enhancer/SKILL.md b/.claude/skills/prompt-enhancer/SKILL.md
index 7d43eae1..f51c72e1 100644
--- a/.claude/skills/prompt-enhancer/SKILL.md
+++ b/.claude/skills/prompt-enhancer/SKILL.md
@@ -1,6 +1,6 @@
---
name: Prompt Enhancer
-description: Transform vague prompts into actionable specs using session memory ONLY (no file analysis). AUTO-TRIGGER on (1) -e/--enhance flags, (2) vague keywords (fix/improve/refactor/修复/优化/重构), (3) unclear refs (it/that/这个/那个), (4) multi-module scope. Supports English + Chinese semantic recognition.
+description: Transform vague prompts into actionable specs using intelligent analysis and session memory. Trigger with -e/--enhance flags.
allowed-tools: (none)
---
@@ -10,35 +10,9 @@ allowed-tools: (none)
**Languages**: English + Chinese (中英文语义识别)
-## Triggers
-
-| Priority | Condition | Examples | Action |
-|----------|-----------|----------|--------|
-| **P1** | `-e` / `--enhance` flag | "fix auth -e", "优化性能 --enhance" | Immediate enhancement |
-| **P2** | Vague keywords | EN: fix/improve/refactor
CN: 修复/优化/重构/更新/改进 | Semantic analysis |
-| **P3** | Unclear references | EN: it/that/the code
CN: 这个/那个/它/代码 | Context extraction |
-| **P4** | Multi-module scope | >3 modules or critical systems | Dependency analysis |
-
## Process (Internal → Direct Output)
-**Internal Analysis (Silent)**:
-
-1. **Semantic Analysis**
- - Intent keywords (EN/CN): fix/修复, improve/优化, add/添加, refactor/重构
- - Scope identification: file → module → system
- - Domain mapping: auth/API/DB/UI/Performance
-
-2. **Memory Extraction** (NO File Reading)
- - Recent user requests and context
- - Tech stack mentioned in session (frameworks, libraries, patterns)
- - Design patterns discussed or implied
- - User preferences and constraints
- - Known dependencies from conversation
-
-3. **Enhancement Dimensions**
- - **Structure**: Convert to INTENT/CONTEXT/ACTION/ATTENTION format
- - **Supplement**: Add tech stack, design patterns, testing requirements
- - **Clarify**: Make intent explicit, resolve ambiguous references
+**Internal Analysis**: Intelligently extract session context, identify tech stack, and structure into actionable format.
**Output**: Direct structured prompt (no intermediate steps shown)
@@ -66,18 +40,6 @@ ATTENTION: [Critical constraints / 关键约束]
- [Security/compatibility/performance concerns]
- [Design pattern requirements]
```
-
-## Semantic Patterns (EN + CN)
-
-| Intent (EN/CN) | Semantic Meaning | Enhancement Focus |
-|----------------|------------------|-------------------|
-| fix/修复 + vague target | Debug & resolve | Root cause + tech stack + testing |
-| improve/优化 + no metrics | Enhance/optimize | Performance metrics + patterns + benchmarks |
-| add/添加 + feature | Implement feature | Integration points + edge cases + tests |
-| refactor/重构 + module | Restructure | Design patterns + backward compatibility |
-| update/更新 + version | Modernize | Migration path + breaking changes |
-| clean up/清理 + area | Simplify/organize | Code quality patterns + tech debt |
-
## Workflow
```
@@ -134,87 +96,3 @@ Trigger → Internal Analysis → Direct Output
3. **Added tech stack section** - Supplement with technologies
4. **Enhanced internal analysis** - 3 dimensions (structure + supplement + clarify)
5. **Focus on memory** - Session context only, no file reading
-
-## Examples
-
-### Example 1: Vague Fix Request
-
-**Input**: "fix auth -e" / "修复认证 --enhance"
-
-**Internal Analysis**:
-- Semantic: "fix/修复" → debug intent
-- Memory: Recent mention of JWT, token expiration issues
-- Tech stack: JWT, Express.js middleware (from session)
-- Enhancement: Add testing, security patterns
-
-**Output**:
-```
-📋 ENHANCED PROMPT
-
-INTENT: Fix authentication token expiration handling in JWT-based auth system
-
-TECH STACK:
-- JWT: Token generation and validation
-- Express.js: Middleware implementation
-- Jest: Unit testing framework
-
-CONTEXT:
-- User reported token expiration issues in previous conversation
-- Session indicates JWT-based authentication system
-- Preference for backward compatibility with existing tokens
-
-ACTION:
-1. Analyze JWT token lifecycle and expiration validation logic
-2. Implement proper token refresh mechanism with sliding expiration
-3. Add middleware for token validation with detailed error handling
-4. Write unit tests for token expiration and refresh scenarios
-5. Update API documentation for token refresh endpoints
-
-ATTENTION:
-- Must maintain backward compatibility with existing valid tokens
-- Security: Follow JWT best practices (HS256/RS256, secure secret storage)
-- Testing: Cover edge cases (expired, malformed, missing tokens)
-- Performance: Consider token validation caching for high-traffic endpoints
-```
-
-### Example 2: Vague Optimization Request
-
-**Input**: "optimize performance --enhance" / "优化性能 -e"
-
-**Internal Analysis**:
-- Semantic: "optimize/优化" → performance intent
-- Memory: Previous discussion about API response times, React rendering
-- Tech stack: React, Node.js, PostgreSQL (from session)
-- Enhancement: Add metrics, profiling, specific optimizations
-
-**Output**:
-```
-📋 ENHANCED PROMPT
-
-INTENT: Optimize API response times and React component rendering performance
-
-TECH STACK:
-- React: Component optimization (memo, useMemo, useCallback)
-- Node.js: API endpoint optimization
-- PostgreSQL: Query optimization and indexing
-
-CONTEXT:
-- User mentioned slow API responses (>2s) in previous conversation
-- React app shows rendering performance issues on large lists
-- PostgreSQL database queries identified as bottleneck
-
-ACTION:
-1. Profile API endpoints using Node.js profiler to identify slow queries
-2. Optimize PostgreSQL queries with proper indexing and query analysis (EXPLAIN)
-3. Implement React.memo for expensive list components
-4. Add useMemo/useCallback for derived data and event handlers
-5. Implement pagination/virtualization for large data lists
-6. Add performance monitoring with metrics (response time, render time)
-7. Write performance benchmarks and regression tests
-
-ATTENTION:
-- Metrics: Target <500ms API response, <100ms render time
-- Patterns: Use React.memo judiciously (avoid over-optimization)
-- Testing: Add performance regression tests with benchmarks
-- Compatibility: Ensure optimizations don't break existing functionality
-```