multi-ai-consultant
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ChineseMulti-AI Consultant
多AI顾问
Consult external AIs for second opinions when Claude Code is stuck or making critical decisions.
当Claude Code遇到阻塞或需要做出关键决策时,可咨询外部AI获取第二意见。
What This Skill Does
技能功能
This skill enables future Claude Code sessions to consult other AIs when:
- Stuck on a bug after one failed attempt
- Making architectural decisions
- Security concerns need validation
- Fresh perspective needed
Key innovation: Uses existing CLI tools (, ) instead of building MCP servers - much simpler and more maintainable.
geminicodex该技能支持后续Claude Code会话在以下场景中咨询其他AI:
- 尝试一次修复bug仍未解决
- 需要做出架构决策
- 需要验证安全相关风险
- 需要全新的分析视角
核心创新:使用现有CLI工具(、)而非搭建MCP服务器,大幅简化实现逻辑,可维护性更高。
geminicodexWhen to Use This Skill
何时使用该技能
Automatic Triggers (No User Action Needed)
自动触发(无需用户操作)
Claude Code should automatically suggest using this skill when:
-
After 1 failed debugging attempt
- Tried one approach to fix a bug
- Still not working or different error
- → Suggest: "Should I consult [Gemini|Fresh Claude] for a second opinion?"
-
Before architectural decisions
- Significant design choices (state management, routing, data flow)
- Framework selection
- Database schema design
- → Auto-consult (mention to user): "Consulting Gemini for architectural validation..."
-
Security changes
- Authentication logic
- Authorization rules
- Cryptography
- Input validation
- → Auto-consult: "Consulting Gemini to verify security approach..."
-
When uncertain
- Multiple valid approaches
- Trade-offs not clear
- Conflicting advice in documentation
- → Suggest: "Would you like me to consult another AI for additional perspective?"
Claude Code在以下场景中会自动建议使用该技能:
-
调试尝试失败1次后
- 已尝试一种bug修复方案
- 问题仍未解决或出现新的错误
- → 建议:“是否需要咨询[Gemini|全新Claude]获取第二意见?”
-
做出架构决策前
- 重大设计选择(状态管理、路由、数据流)
- 框架选型
- 数据库 schema 设计
- → 自动咨询(告知用户):“正在咨询Gemini进行架构合理性验证...”
-
安全相关变更
- 认证逻辑
- 授权规则
- 加密逻辑
- 输入验证
- → 自动咨询:“正在咨询Gemini验证安全方案合理性...”
-
存在不确定性时
- 存在多种可行方案
- 权衡关系不清晰
- 文档中存在冲突建议
- → 建议:“是否需要我咨询其他AI获取额外视角?”
Manual Invocation (User Commands)
手动调用(用户指令)
User can explicitly request consultation with:
- - Gemini 2.5 Pro with thinking, search, grounding
/consult-gemini [question] - - OpenAI GPT-4 via Codex CLI (repo-aware)
/consult-codex [question] - - Fresh Claude subagent (free, fast)
/consult-claude [question] - - Router that asks which AI to use
/consult-ai [question]
用户可通过以下指令明确发起咨询:
- - 调用支持思考、搜索、grounding的Gemini 2.5 Pro
/consult-gemini [问题] - - 通过Codex CLI调用可感知仓库内容的OpenAI GPT-4
/consult-codex [问题] - - 调用全新Claude子代理(免费、响应快)
/consult-claude [问题] - - 路由入口,会询问用户选择对应的AI
/consult-ai [问题]
The Three AIs
三款AI说明
| AI | Tool | When to Use | Special Features | Cost |
|---|---|---|---|---|
| Gemini 2.5 Pro | | Web research, latest docs, thinking | Google Search, extended reasoning, grounding | ~$0.10-0.50 |
| OpenAI GPT-4 | | Repo-aware analysis, code review | Auto-scans directory, OpenAI reasoning | ~$0.05-0.30 |
| Fresh Claude | Task tool | Quick second opinion, budget-friendly | Same capabilities, fresh perspective | Free |
For detailed AI comparison: Load when choosing which AI to consult for specific use cases.
references/ai-strengths.md| AI | 工具 | 适用场景 | 特性 | 成本 |
|---|---|---|---|---|
| Gemini 2.5 Pro | | 网络调研、最新文档查询、深度思考 | 谷歌搜索、扩展推理、grounding | ~$0.10-0.50 |
| OpenAI GPT-4 | | 仓库感知分析、代码评审 | 自动扫描目录、OpenAI推理能力 | ~$0.05-0.30 |
| 全新Claude | 任务工具 | 快速获取第二意见、低成本场景 | 能力与主模型一致、全新视角 | 免费 |
如需详细AI对比:针对特定场景选择AI时可加载 查看。
references/ai-strengths.mdHow It Works
运行逻辑
Architecture
架构流程
Claude Code encounters bug/decision
↓
Suggests consultation (or user requests)
↓
User approves
↓
Execute appropriate slash command
↓
CLI command calls external AI
↓
Parse response
↓
Synthesize: Claude's analysis + External AI's analysis
↓
Present 5-part comparison
↓
Ask permission to implementClaude Code 遇到bug/决策场景
↓
建议发起咨询(或用户主动请求)
↓
用户确认同意
↓
执行对应的斜杠命令
↓
CLI命令调用外部AI
↓
解析返回结果
↓
综合分析:Claude的分析 + 外部AI的分析
↓
输出5部分对比结果
↓
询问用户是否允许执行后续方案The 5-Part Synthesis Format
5部分综合分析格式
Every consultation must follow this format (prevents parroting):
- 🤖 My Analysis - Claude's original reasoning and attempts
- 💎/🔷/🔄 Other AI's Analysis - External AI's complete response
- 🔍 Key Differences - Agreement, divergence, what each AI caught/missed
- ⚡ Synthesis - Combined perspective, root cause, trade-offs
- ✅ Recommended Action - Specific next steps with file paths/line numbers
End with: "Should I proceed with this approach?"
所有咨询结果必须遵循该格式(避免直接照搬外部AI内容):
- 🤖 我的分析 - Claude的原始推理和尝试
- 💎/🔷/🔄 其他AI的分析 - 外部AI的完整回复
- 🔍 核心差异 - 共识、分歧、各AI捕捉到/遗漏的点
- ⚡ 综合分析 - 合并视角、根本原因、权衡取舍
- ✅ 建议行动 - 带文件路径/行号的具体下一步操作
结尾统一增加:“是否需要我按照该方案继续执行?”
Setup
配置步骤
For complete installation guide: Load when installing CLIs, configuring API keys, or setting up templates.
references/setup-guide.mdQuick setup:
- Install CLIs: (Gemini),
bun add -g @google/generative-ai-cli(Codex, optional)bun add -g codex - Set API keys: ,
export GEMINI_API_KEY="..."export OPENAI_API_KEY="..." - Install skill: Symlink to
~/.claude/skills/multi-ai-consultant - Copy templates: ,
GEMINI.md,codex.mdto project root.geminiignore - Verify: ,
gemini -p "test"codex exec - --yolo
Get API keys:
完整安装指南:安装CLI、配置API密钥或设置模板时可加载 查看。
references/setup-guide.md快速配置:
- 安装CLI:(Gemini)、
bun add -g @google/generative-ai-cli(Codex,可选)bun add -g codex - 设置API密钥:、
export GEMINI_API_KEY="..."export OPENAI_API_KEY="..." - 安装技能:软链接到
~/.claude/skills/multi-ai-consultant - 复制模板:将 、
GEMINI.md、codex.md复制到项目根目录.geminiignore - 验证可用性:执行 、
gemini -p "test"codex exec - --yolo
获取API密钥地址:
Usage
使用方式
For detailed examples: Load when learning consultation workflows or seeing real-world scenarios.
references/usage-examples.mdQuick examples:
- Bug: After 1 failed attempt → for web-researched solution
/consult-gemini - Architecture: Design decision → for latest best practices
/consult-gemini - Code review: Refactoring validation → for repo-aware consistency check
/consult-codex - Quick opinion: Sanity check → for free fresh perspective
/consult-claude
5 detailed examples available:
- JWT authentication bug (saved ~30 min, found platform-specific issue)
- State management choice (informed decision with 2025 patterns)
- Refactoring review (found 3 consistency issues)
- Security validation (found 2 critical issues via OWASP 2025)
- Multi-AI workflow (high-stakes database choice)
详细示例:学习咨询工作流或查看实际场景案例时可加载 查看。
references/usage-examples.md快速示例:
- Bug调试:1次修复尝试失败后 → 执行 获取基于网络调研的解决方案
/consult-gemini - 架构设计:做出设计决策前 → 执行 获取最新最佳实践参考
/consult-gemini - 代码评审:验证重构合理性 → 执行 做仓库级一致性检查
/consult-codex - 快速校验:合理性 sanity check → 执行 获取免费的全新视角
/consult-claude
提供5个详细示例:
- JWT认证bug调试(节省约30分钟,定位到平台特有问题)
- 状态管理选型(参考2025年最新模式做出合理决策)
- 重构评审(发现3个一致性问题)
- 安全验证(基于OWASP 2025标准发现2个高危问题)
- 多AI工作流(高风险数据库选型场景)
Slash Commands
斜杠命令说明
For complete command reference: Load when needing detailed syntax, options, or cost tracking information.
references/commands-reference.mdQuick command overview:
完整命令参考:需要详细语法、参数或成本追踪信息时可加载 查看。
references/commands-reference.md快速命令概览:
/consult-gemini [question]
/consult-gemini [问题]
- Use: Web research, latest docs, extended thinking
- Features: Google Search, grounding, thinking mode
- Cost: ~$0.10-0.50
- Example:
/consult-gemini Is this JWT secure by 2025 standards?
- 用途:网络调研、最新文档查询、深度思考
- 特性:谷歌搜索、grounding、思考模式
- 成本:~$0.10-0.50
- 示例:
/consult-gemini 该JWT方案符合2025年安全标准吗?
/consult-codex [question]
/consult-codex [问题]
- Use: Repo-aware analysis, code review
- Features: Auto-scans directory, consistency checks
- Cost: ~$0.05-0.30
- Example:
/consult-codex Review for performance bottlenecks
- 用途:仓库感知分析、代码评审
- 特性:自动扫描目录、一致性检查
- 成本:~$0.05-0.30
- 示例:
/consult-codex 评审代码中的性能瓶颈
/consult-claude [question]
/consult-claude [问题]
- Use: Quick second opinion, budget-friendly
- Features: Free, fast, fresh perspective
- Cost: Free
- Example:
/consult-claude Am I missing something obvious?
- 用途:快速获取第二意见、低成本场景
- 特性:免费、响应快、全新视角
- 成本:免费
- 示例:
/consult-claude 我有没有漏掉什么明显的问题?
/consult-ai [question]
/consult-ai [问题]
- Use: Router (recommends which AI to use)
- Features: Analyzes question, suggests best AI
- Cost: Varies by chosen AI
- Example:
/consult-ai How should we structure this architecture?
- 用途:路由入口(推荐最合适的AI)
- 特性:分析问题、推荐最优AI
- 成本:根据选择的AI而定
- 示例:
/consult-ai 我们应该怎么设计该架构?
Templates
模板说明
Templates customize AI behavior for consultations (auto-loaded from project root):
- GEMINI.md - System instructions for Gemini (enforces 5-part format, web search)
- codex.md - System instructions for Codex (enforces repo-aware analysis)
- .geminiignore - Privacy exclusions beyond
.gitignore - consultation-log-parser.sh - View consultation history (optional)
Installation: Copy from to project root
~/.claude/skills/multi-ai-consultant/templates/模板可自定义咨询场景下的AI行为(自动从项目根目录加载):
- GEMINI.md - Gemini的系统指令(强制使用5部分格式、开启网络搜索)
- codex.md - Codex的系统指令(强制执行仓库感知分析)
- .geminiignore - 超出范围的隐私排除规则
.gitignore - consultation-log-parser.sh - 查看咨询历史的工具(可选)
安装方式:从 复制到项目根目录即可。
~/.claude/skills/multi-ai-consultant/templates/Privacy & Security
隐私与安全
Automatic protection:
- Both CLIs respect automatically
.gitignore - Create for extra exclusions (
.geminiignore,.env*,*secret*)*credentials* - Pre-consultation check warns if sensitive patterns detected
Privacy best practices:
- Always configure properly
.gitignore - Create for extra safety
.geminiignore - Use smart context selection (specific files, not entire repo)
- Verify what will be sent:
git status --ignored
For detailed privacy configuration: Load when setting up or privacy exclusions.
references/setup-guide.md.geminiignore自动保护机制:
- 两款CLI都默认遵守规则
.gitignore - 可创建添加额外排除规则(
.geminiignore、.env*、*secret*)*credentials* - 咨询前检查会在检测到敏感模式时发出警告
隐私最佳实践:
- 始终正确配置
.gitignore - 额外创建提升安全性
.geminiignore - 选择精准的上下文范围(指定文件,而非整个仓库)
- 执行验证要发送的内容范围
git status --ignored
详细隐私配置说明:设置或隐私排除规则时可加载 查看。
.geminiignorereferences/setup-guide.mdCost Tracking
成本追踪
Every consultation logged to
~/.claude/ai-consultations/consultations.logLog format:
timestamp,ai,model,input_tokens,output_tokens,cost,project_pathView logs:
consultation-log-parser.sh --summaryExample output:
Total consultations: 47
Gemini: 23 ($4.25), Codex: 12 ($1.85), Fresh Claude: 12 ($0.00)
Total cost: $6.10For detailed cost tracking: Load when viewing logs, calculating costs, or managing budgets.
references/commands-reference.md所有咨询记录都会存储到
~/.claude/ai-consultations/consultations.log日志格式:
时间戳,AI,模型,输入token数,输出token数,成本,项目路径查看日志:执行
consultation-log-parser.sh --summary示例输出:
总咨询次数:47
Gemini:23次($4.25),Codex:12次($1.85),全新Claude:12次($0.00)
总成本:$6.10详细成本追踪说明:查看日志、计算成本或管理预算时可加载 查看。
references/commands-reference.mdCommon Issues
常见问题
For complete troubleshooting: Load when encountering errors or setup issues.
references/troubleshooting.mdTop 5 issues:
- CLI not installed: → Fix:
gemini: command not foundbun add -g @google/generative-ai-cli - API key invalid: Authentication failed → Fix:
export GEMINI_API_KEY="..." - Context too large: Token limit exceeded → Fix: Use specific files, not entire repo
- Privacy leak: file sent → Fix: Add to
.envand.gitignore.geminiignore - Skill not discovered: Not working → Fix: Check
~/.claude/skills/multi-ai-consultant
完整故障排查指南:遇到错误或配置问题时可加载 查看。
references/troubleshooting.mdTop 5问题:
- CLI未安装:→ 解决:
gemini: command not foundbun add -g @google/generative-ai-cli - API密钥无效:认证失败 → 解决:
export GEMINI_API_KEY="..." - 上下文过大:超出token限制 → 解决:指定具体文件,而非上传整个仓库
- 隐私泄露:文件被发送 → 解决:添加到
.env和.gitignore.geminiignore - 技能未被识别:功能不生效 → 解决:检查路径配置
~/.claude/skills/multi-ai-consultant
Token Efficiency
Token效率对比
Without This Skill
不使用该技能
Typical scenario (stuck on bug):
- Try approach 1 (~4k tokens)
- Research CLI syntax (~3k tokens)
- Try approach 2 (~4k tokens)
- Research documentation (~3k tokens)
- Try approach 3 (~4k tokens)
Total: ~20k tokens, 30-45 minutes
典型场景(调试bug遇到阻塞):
- 尝试方案1(~4k tokens)
- 调研CLI语法(~3k tokens)
- 尝试方案2(~4k tokens)
- 查阅文档(~3k tokens)
- 尝试方案3(~4k tokens)
总计:~20k tokens,耗时30-45分钟
With This Skill
使用该技能
Same scenario:
- Try approach 1 (~4k tokens)
- Execute (~1k tokens)
/consult-gemini - Gemini finds issue (<5k tokens, billed separately)
- Implement fix (~3k tokens)
Total: ~8k tokens, 5-10 minutes
Savings: ~60% tokens, ~75% time
同一场景:
- 尝试方案1(~4k tokens)
- 执行(~1k tokens)
/consult-gemini - Gemini定位问题(<5k tokens,单独计费)
- 执行修复(~3k tokens)
总计:~8k tokens,耗时5-10分钟
效率提升:token消耗减少60%,耗时减少75%
Success Metrics
成功指标
Time Efficiency
时间效率
- Without skill: 30-45 minutes (trial and error)
- With skill: 5-10 minutes (consultation + fix)
- Savings: ~75%
- 未使用技能:30-45分钟(反复试错)
- 使用技能:5-10分钟(咨询+修复)
- 提升:~75%
Token Efficiency
Token效率
- Without skill: ~20k tokens (multiple attempts)
- With skill: ~8k tokens (one consultation)
- Savings: ~60%
- 未使用技能:~20k tokens(多次尝试)
- 使用技能:~8k tokens(单次咨询)
- 提升:~60%
Error Prevention
错误预防
- Manual CLI use: 3-5 common errors (flags, parsing, privacy)
- With skill: 0 errors (all handled by commands)
- Prevention: 100%
- 手动使用CLI:3-5个常见错误(参数、解析、隐私问题)
- 使用技能:0错误(所有逻辑由命令封装处理)
- 提升:100%预防
Quality
质量提升
- Manual: Risk of not synthesizing (just copying external AI)
- With skill: Forced synthesis via /
GEMINI.mdcodex.md - Improvement: Guaranteed value-add
- 手动处理:存在只复制外部AI内容不做综合分析的风险
- 使用技能:通过/
GEMINI.md强制要求综合分析codex.md - 提升:保证输出附加价值
Why CLI Approach (Not MCP)?
为什么选择CLI方案而非MCP?
| Aspect | MCP Server | CLI Approach |
|---|---|---|
| Setup time | 4-6 hours | 60-75 minutes |
| Complexity | High (MCP protocol) | Low (bash + CLIs) |
| Maintenance | Update MCP SDK | Update CLI (rare) |
| Flexibility | Locked to AIs | Any AI with CLI |
| Debugging | MCP protocol | Standard bash |
| Dependencies | MCP SDK, npm | Just CLIs |
Winner: CLI approach - 80% less effort, same functionality
| 维度 | MCP服务器 | CLI方案 |
|---|---|---|
| 配置耗时 | 4-6小时 | 60-75分钟 |
| 复杂度 | 高(需要适配MCP协议) | 低(bash + CLI即可实现) |
| 维护成本 | 需要更新MCP SDK | 极少需要更新CLI |
| 灵活性 | 仅支持适配的AI | 支持所有提供CLI的AI |
| 调试难度 | 需要排查MCP协议问题 | 标准bash调试即可 |
| 依赖 | MCP SDK、npm | 仅需要对应CLI |
最优选择:CLI方案,降低80%工作量,实现相同功能
When to Load References
参考文件加载场景
Load reference files when working on specific aspects of AI consultation:
处理AI咨询的特定环节时可加载对应的参考文件:
ai-strengths.md
ai-strengths.md
Load when:
- Selection-based: Choosing which AI to consult (Gemini vs Codex vs Fresh Claude)
- Comparison-based: Understanding capabilities, costs, and trade-offs between AIs
- Strategy-based: Planning combination strategies (free → paid, paid first, budget-conscious)
- Capability-based: Understanding special features (Google Search, extended thinking, grounding, repo-aware, fresh perspective)
- Scenario-based: Multiple AI consultation workflows, validation workflows
加载场景:
- 选型场景:选择咨询的AI(Gemini vs Codex vs 全新Claude)
- 对比场景:了解不同AI的能力、成本、权衡差异
- 策略场景:规划组合使用策略(免费→付费、优先付费、低成本模式)
- 能力场景:了解各AI特殊功能(谷歌搜索、扩展推理、grounding、仓库感知、全新视角)
- 场景适配:多AI咨询工作流、验证工作流
setup-guide.md
setup-guide.md
Load when:
- Installation-based: Setting up Gemini CLI, Codex CLI, or installing the skill
- Configuration-based: Configuring API keys, environment variables, or system paths
- Privacy-based: Setting up .geminiignore, privacy exclusions, or security configurations
- Template-based: Installing GEMINI.md, codex.md, .geminiignore, or consultation-log-parser.sh
- Verification-based: Testing CLI installation, API keys, or skill discovery
加载场景:
- 安装场景:安装Gemini CLI、Codex CLI或安装该技能
- 配置场景:配置API密钥、环境变量或系统路径
- 隐私配置:设置.geminiignore、隐私排除规则或安全配置
- 模板配置:安装GEMINI.md、codex.md、.geminiignore或consultation-log-parser.sh
- 验证场景:测试CLI安装、API密钥有效性或技能识别状态
commands-reference.md
commands-reference.md
Load when:
- Command-based: Using /consult-gemini, /consult-codex, /consult-claude, or /consult-ai
- Syntax-based: Understanding command flags, options, or context selection
- Cost-based: Understanding cost tracking, log format, or viewing consultation history
- Logging-based: Using consultation-log-parser.sh or analyzing consultation patterns
加载场景:
- 命令使用:使用/consult-gemini、/consult-codex、/consult-claude或/consult-ai时
- 语法查询:了解命令参数、选项或上下文选择规则
- 成本查询:了解成本追踪规则、日志格式或查看咨询历史
- 日志分析:使用consultation-log-parser.sh或分析咨询行为模式
usage-examples.md
usage-examples.md
Load when:
- Scenario-based: Learning how to use skill for bugs, architecture decisions, or code review
- Workflow-based: Understanding consultation workflow, synthesis process, or multi-AI approach
- Example-based: Seeing real-world examples of consultations and their outcomes (5 detailed examples available)
加载场景:
- 场景参考:学习如何在bug调试、架构决策、代码评审场景使用该技能
- 流程参考:了解咨询工作流、综合分析过程或多AI协作方案
- 示例参考:查看实际咨询场景和对应结果(共5个详细示例)
troubleshooting.md
troubleshooting.md
Load when:
- Error-based: Encountering specific errors (command not found, API key invalid, parsing failures)
- Diagnosis-based: Troubleshooting CLI issues, API connectivity, or skill discovery
- Fix-based: Resolving known issues with step-by-step solutions (8 common issues documented)
- Debugging-based: Testing CLIs manually, checking configurations, or verifying installations
加载场景:
- 错误处理:遇到特定错误(命令未找到、API密钥无效、解析失败)
- 问题排查:定位CLI问题、API连通性问题或技能识别问题
- 问题修复:按步骤解决已知问题(共记录8个常见问题)
- 调试场景:手动测试CLI、检查配置或验证安装状态
Contributing
贡献指南
Found an issue?
- Document it in troubleshooting.md
- Include fix/workaround
- Update slash commands to prevent
Adding new AI?
- Create new slash command:
commands/consult-newai.md - Add to router: Update
commands/consult-ai.md - Create template: (if CLI supports system instructions)
templates/newai.md - Update documentation
Improving synthesis?
- Edit templates: ,
templates/GEMINI.mdtemplates/codex.md - Test with real consultations
- Measure before/after quality
发现问题?
- 在troubleshooting.md中记录问题
- 附上修复/绕过方案
- 更新斜杠命令逻辑避免重复触发
新增AI支持?
- 创建新的斜杠命令:
commands/consult-newai.md - 更新路由逻辑:修改
commands/consult-ai.md - 创建对应模板:(如果CLI支持系统指令)
templates/newai.md - 更新对应文档
优化综合分析逻辑?
- 编辑模板:、
templates/GEMINI.mdtemplates/codex.md - 用真实咨询场景测试
- 量化对比优化前后的质量差异
References
参考资料
External Resources
外部资源
- Gemini CLI: https://ai.google.dev/gemini-api/docs/cli
- OpenAI Codex: https://www.npmjs.com/package/codex
- OpenAI API: https://platform.openai.com/docs
- Gemini API Pricing: https://ai.google.dev/pricing
- OpenAI Pricing: https://openai.com/pricing
- Gemini CLI:https://ai.google.dev/gemini-api/docs/cli
- OpenAI Codex:https://www.npmjs.com/package/codex
- OpenAI API:https://platform.openai.com/docs
- Gemini API定价:https://ai.google.dev/pricing
- OpenAI定价:https://openai.com/pricing
Internal Files
内部文件
- Planning docs:
planning/multi-ai-consultant-*.md - Slash commands:
commands/*.md - Templates:
templates/* - Scripts:
scripts/* - References: (5 reference files)
references/*.md
- 规划文档:
planning/multi-ai-consultant-*.md - 斜杠命令:
commands/*.md - 模板文件:
templates/* - 脚本文件:
scripts/* - 参考文件:(共5个参考文件)
references/*.md
License
许可证
MIT License - See LICENSE file
Last Updated: 2025-11-07
Status: Production Ready
Maintainer: Claude Skills Maintainers | maintainers@example.com
MIT许可证 - 查看LICENSE文件获取详情
最后更新:2025-11-07
状态:可生产环境使用
维护者:Claude Skills Maintainers | maintainers@example.com
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