From 99cb29ed23ad49b47c66739be73c0d272569a8b5 Mon Sep 17 00:00:00 2001 From: catlog22 Date: Sat, 18 Oct 2025 22:41:25 +0800 Subject: [PATCH] refactor: simplify prompt-enhancer skill description and internal analysis MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - Update description: focus on intelligent analysis and session memory - Simplify trigger mechanism to only -e/--enhance flags - Condense internal analysis section to single concise statement - Remove verbose semantic analysis details for cleaner documentation 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude --- .claude/skills/prompt-enhancer/SKILL.md | 126 +----------------------- 1 file changed, 2 insertions(+), 124 deletions(-) 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 -```