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资深软件架构师顾问——分析模块间关系、评估重大改动方案、解答架构疑惑。 当用户说"帮我分析架构"、"这个改动合理吗"、"我想重构 X"、"这样设计有什么问题"、 "帮我评估方案"、"架构上怎么看"、"我有个大改动"时立即触发。 也适用于:"这个模块怎么拆"、"依赖关系合理吗"、"接口怎么设计"、 "该用哪种模式"、"迁移方案怎么做"、"这个 PR 改动太大了"等架构决策场景。 只要用户面临影响多个模块、涉及接口变更、或需要权衡取舍的技术决策,就应使用此 skill。 --- # Architect — 架构顾问 Skill 以资深软件架构师的视角,分析**模块之间的关系与边界**,评估变更影响,给出有理有据的建议。 核心关注点是:**谁依赖谁、谁负责什么、消息/数据如何在模块间流动**——而不是某个模块内部的实现细节。 --- ## 第一步:建立项目上下文 先阅读架构层面的文档,不深入源码实现。**并行执行**: ``` read_file("CLAUDE.md") # 项目架构说明(最重要) glob_files("**/Cargo.toml") # Workspace 模块结构(Rust 项目) bash("git log --oneline -15") # 近期改动方向 ``` 如果存在 spec/global/ 目录,还需读取: ``` glob_files("spec/global/**/*.md") # 全局架构文档 ``` > 目标:搞清楚项目有哪些模块、它们之间的依赖关系是什么、数据流的大方向——然后才能讨论改动的影响。 --- ## 第二步:理解问题 明确用户面临的决策点: - **涉及哪些模块**:改动横跨哪几个模块/crate/组件 - **现有的模块关系**:它们目前如何交互(调用、事件、共享状态、消息传递) - **想改什么**:计划中的边界或接口变化 - **驱动原因**:解耦、功能扩展、性能、可维护性 如果问题描述不够清晰,**先问清楚再分析**。 --- ## 第三步:架构分析框架 核心视角始终是**模块边界与模块间关系**,而非单个模块的内部实现。 ### 3a. 评估一个变更方案 逐一检视有实质内容的维度: | 维度 | 关注点 | | ---------------- | ---------------------------------------------------------------- | | **依赖方向** | 变更后依赖是否保持单向?是否引入循环依赖? | | **接口稳定性** | 跨模块的契约(trait/API/消息格式)是否被破坏?调用方需要改多少? | | **职责归属** | 每个模块的边界是否清晰?有没有职责被错误地放到了边界另一侧? | | **数据流清晰度** | 数据/事件在模块间的流动路径是否可追踪、可推理? | | **模块耦合度** | 改后模块间的耦合是增加还是减少?是紧耦合还是通过抽象层解耦? | | **迁移成本** | 需要同步修改哪些调用方?能否分阶段落地而不一次性破坏所有接口? | ### 3b. 诊断一个架构问题 先描述**症状**(难以扩展、边界模糊、牵一发动全身、职责重叠),再追溯**根因**(哪两个模块的关系出了问题、为什么),最后给出**最小有效改动**。 ### 3c. 比较多个方案 用结构化表格从模块关系角度对比,最后给出**明确推荐**和**推荐理由**。不要给出"都可以,看你喜好"——那不是架构建议,那是回避。 --- ## 第四步:输出结构 根据问题复杂度选择格式: **简单问题(单一决策点)**:直接给结论 + 核心理由,不超过 200 字。 **中等复杂度(涉及 2-3 个模块的关系)**: ``` ## 当前模块关系 <描述涉及模块之间现有的依赖/交互方式> ## 问题所在 <哪个边界有问题,或哪两个模块的关系不对> ## 建议调整 <推荐的模块关系,说明为什么这样划分更合理> ## 注意事项 <迁移时需要同步调整的接口、潜在的破坏性变更> ``` **大型变更(跨多个 crate / 重新划定模块边界)**: ``` ## TL;DR <一句话结论> ## 当前架构关系图(文字描述) ## 变更后架构关系图(文字描述) ## 方案对比 ## 推
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Skill File Structure Sample (Reference)
skill-sample/
├─ SKILL.md ⭐ Required: skill entry doc (purpose / usage / examples / deps)
├─ manifest.sample.json ⭐ Recommended: machine-readable metadata (index / validation / autofill)
├─ LICENSE.sample ⭐ Recommended: license & scope (open source / restriction / commercial)
├─ scripts/
│ └─ example-run.py ✅ Runnable example script for quick verification
├─ assets/
│ ├─ example-formatting-guide.md 🧩 Output conventions: layout / structure / style
│ └─ example-template.tex 🧩 Templates: quickly generate standardized output
└─ references/ 🧩 Knowledge base: methods / guides / best practices
├─ example-ref-structure.md 🧩 Structure reference
├─ example-ref-analysis.md 🧩 Analysis reference
└─ example-ref-visuals.md 🧩 Visual reference
More Agent Skills specs
Anthropic docs: https://agentskills.io/home
SKILL.md Requirements
├─ ⭐ Required: YAML Frontmatter (must be at top)
│ ├─ ⭐ name : unique skill name, follow naming convention
│ └─ ⭐ description : include trigger keywords for matching
│
├─ ✅ Optional: Frontmatter extension fields
│ ├─ ✅ license : license identifier
│ ├─ ✅ compatibility : runtime constraints when needed
│ ├─ ✅ metadata : key-value fields (author/version/source_url...)
│ └─ 🧩 allowed-tools : tool whitelist (experimental)
│
└─ ✅ Recommended: Markdown body (progressive disclosure)
├─ ✅ Overview / Purpose
├─ ✅ When to use
├─ ✅ Step-by-step
├─ ✅ Inputs / Outputs
├─ ✅ Examples
├─ 🧩 Files & References
├─ 🧩 Edge cases
├─ 🧩 Troubleshooting
└─ 🧩 Safety notes
Why SkillWink?
Skill files are scattered across GitHub and communities, difficult to search, and hard to evaluate. SkillWink organizes open-source skills into a searchable, filterable library you can directly download and use.
We provide keyword search, version updates, multi-metric ranking (downloads / likes / comments / updates), and open SKILL.md standards. You can also discuss usage and improvements on skill detail pages.
Keyword Search
Version Updates
Multi-Metric Ranking
Open Standard
Discussion
Quick Start:
Import/download skills (.zip/.skill), then place locally:
~/.claude/skills/ (Claude Code)
~/.codex/skills/ (Codex CLI)
One SKILL.md can be reused across tools.
FAQ
Everything you need to know: what skills are, how they work, how to find/import them, and how to contribute.
1. What are Agent Skills?
A skill is a reusable capability package, usually including SKILL.md (purpose/IO/how-to) and optional scripts/templates/examples.
Think of it as a plugin playbook + resource bundle for AI assistants/toolchains.
2. How do Skills work?
Skills use progressive disclosure: load brief metadata first, load full docs only when needed, then execute by guidance.
This keeps agents lightweight while preserving enough context for complex tasks.
3. How can I quickly find the right skill?
Use these three together:
Semantic search: describe your goal in natural language.
Multi-filtering: category/tag/author/language/license.
Sort by downloads/likes/comments/updated to find higher-quality skills.
4. Which import methods are supported?
Upload archive: .zip / .skill (recommended)
Upload skills folder
Import from GitHub repository
Note: file size for all methods should be within 10MB.
5. How to use in Claude / Codex?
Typical paths (may vary by local setup):
Claude Code:~/.claude/skills/
Codex CLI:~/.codex/skills/
One SKILL.md can usually be reused across tools.
6. Can one skill be shared across tools?
Yes. Most skills are standardized docs + assets, so they can be reused where format is supported.
Example: retrieval + writing + automation scripts as one workflow.
7. Are these skills safe to use?
Some skills come from public GitHub repositories and some are uploaded by SkillWink creators. Always review code before installing and own your security decisions.
8. Why does it not work after import?
Most common reasons:
Wrong folder path or nested one level too deep
Invalid/incomplete SKILL.md fields or format
Dependencies missing (Python/Node/CLI)
Tool has not reloaded skills yet
9. Does SkillWink include duplicates/low-quality skills?
We try to avoid that. Use ranking + comments to surface better skills:
Duplicate skills: compare differences (speed/stability/focus)
Low quality skills: regularly cleaned up