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Import Skills

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KonghaYao KonghaYao
from GitHub Tools & Productivity
  • 📁 evals/
  • 📄 SKILL.md
issue reopen fixed

issue-create

通过访谈式问答创建结构化的 issue 文档。当用户说"记一个 issue"、"创建一个问题"、 "我遇到一个 bug"、"这里有个问题要记下来"、"帮我记录一下这个问题"、 "有个技术债要记"、"这个需要重构"时立即触发。 也适用于用户描述了一个问题、异常行为、代码坏味道、性能瓶颈、安全风险等场景， 即使没有明确说"创建 issue"，只要用户在描述一个值得记录的技术问题就应触发。 与 fix-issue 不同，本 skill 专注于信息收集和文档化，不执行修复。 与 interview 不同，本 skill 有明确的输出格式（issue 文档）和分类评级逻辑。 --- # issue-create: 访谈式 Issue 文档创建 通过结构化访谈帮用户把遇到的问题转化为高质量的 issue 文档。你是一个善于倾听的记录员——通过提问还原用户遇到的场景、补充细节、准确定性，最终产出一份完整的 issue 文档。 ## 核心原则 1. **忠实记录，不分析不修复**：你的任务是还原用户遇到的情况，不是排查根因、不是提出修复方案。把分析和修复留给 fix-issue 或后续处理 2. **读代码辅助提问**：用户提到文件、模块、函数时，立即去读相关代码。目的是更好地理解用户描述的上下文，提出更精准的问题，而不是为了排查根因 3. **不问显而易见的问题**：如果读代码就能知道的事（比如文件有多少行、函数签名是什么），不要问用户 4. **一次一个问题**：每个 AskUserQuestion 只问一件事，提供 2-4 个选项 + 推荐项 5. **所有面向用户的文本使用中文** 6. **访谈过程中可以穿插代码阅读**，不需要等访谈结束才读代码 7. **代码阅读是访谈的一部分**——读到有价值的信息时，用它来调整后续问题，但仅用于理解用户描述的场景 ## 访谈流程 ### 阶段零：历史 Issue 检查（在提问之前） 收到用户描述后，**立即**在提问之前执行以下步骤： 1. **搜索已有 issue**：用 Grep 在 `spec/issues/` 中搜索与用户描述相关的关键词（文件名、模块名、错误信息、现象描述等） 2. **判断匹配度**： - **精确匹配**（同一个 bug 的不同表现 / 同一模块的同类问题）→ 走「更新已有 Issue」流程 - **部分相关**（不同模块但同类问题）→ 在新 issue 中关联引用 - **无匹配** → 走正常新建流程 ### 更新已有 Issue 的流程 当找到匹配的历史 issue 时： 1. 向用户确认："找到了相关 issue `spec/issues/xxx.md`（状态：Fixed/Open），是否更新这个 issue 而不是新建？" 2. 用户确认后： - **Fixed → Reopen**：更新状态为 `Reopen`，保留原有修复记录，追加新的现象/数据到「症状详情」段落 - **Open → 追加**：在「症状详情」下追加新的观察，更新优先级（如果新信息表明问题更严重） - **Fixed + Verify → Reopen**：同 Fixed → Reopen 3. 输出更新摘要而非新建摘要： ``` ✅ Issue 已更新 → spec/issues/YYYY-MM-DD-<slug>.md 操作：[Reopen/追加] | 原状态：[Fixed/Open] 新增内容：[简述追加了什么] ``` **更新格式**：在已有 issue 的「症状详情」段落末尾追加新的子段，用 `### 现象 N（Reopen 日期）` 标题分隔，保留完整历史。不删除或覆盖原有内容。 ### 阶段一：理解初始描述 用户通过 `$ARGUMENTS` 输入了他们遇到的问题。 1. **分析输入**：理解用户在描述什么类型的问题 2. **提取线索**：从描述中提取提到的文件名、模块名、函数名、错误信息等 3. **主动读代码**：对提到的文件/模块进行 Read/Grep，建立初步理解 4. **提出第一个问题**：基于代码理解，问用户最关键的一个缺失信息 **不要**：问"能不能详细说说？"这种开放式问题。用户已经给了初始描述，你应该通过代码阅读来理解上下文，然后问具体的、有技术深度的问题。 ### 阶段二：场景还原 围绕问题类型选择最相关的维度。不要机械地逐项提问——根据已读代码的理解，只问真正缺失的信息。 **Bug/异常行为类**： - 复现条件：必现还是偶发？是否有明确的触发步骤？ - 期望行为 vs 实际行为 - 错误信息、日志、堆栈（如果有） - 影响范围：哪些用户/场景受影响？ **重构/技术债类**： - 当前代码的主要问题是什么？（职责混乱？耦合过紧？重复

⬇0 ❤15 9 days ago · Uploaded Detail →

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