feat(agents): 统一的 agent 配置管理方案。 (#1670)

* feat(agents/skills): 为 agents 添加 skill-creator 技能

* feat(agents): 实现初版 Gvisor bug 修复 Skill

* docs(agents):添加 `.agent` 文件夹的文档

* chore(agents):使用软链接将 skills 文件夹链接到不同agent

* refactor: 调整 README 文档

* feat: 添加对 copilot 的 skills 引用支持

* feat(agents): 更新 “gvisor 分析”的 SKILL.md 文档并将示例拆分为单独文档

* feat: v0.2.0 gvisor 分析报告 skills

- 合并单测试用例分析和多测试用例分析的工作流

* docs(agents/gvisor-anly): 补充步骤七完整内容并更新示例

- 补充 SKILL.md 步骤七的详细内容(根因分析表格和修复方案的生成规则)
- 更新 EXAMPLES.md 中的处理流程,使其符合新的 7 步工作流
- 区分单个测试(跳过概览步骤)和多个测试(完整 7 步)的处理路径

Signed-off-by: mingjiangyu1 <mingjiangyu1@qq.com>
This commit is contained in:
Yuming Jiang
2026-02-11 11:24:30 +08:00
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.agents 目录说明
=================
本目录用于集中存放 Agent 工具的通用资源与说明,避免分散在多个配置目录中造成维护成本增加与同步困难的问题。
## 作用
- 统一维护:集中存放各类 Agent 工具共用的配置方便管理与更新。
- 可复用:配合软链接将本目录挂载到其他 Agent 工具配置中,实现一次修改、多处同步。
## 与其他目录的关系
本目录可被其他 Agent 工具的配置目录通过软链接引用,以达到共享资源的目的。
例如将 `.agents/skills` 链接到外部 Agent 工具的技能目录中(示例命令,按实际路径调整):
```
ln -s /path/to/DragonOS/.agents/skills /path/to/other-agent/skills
```
## 目录结构示例
```
.agents/
├── README.md # 本说明文件
└── skills/ # 存放各类 Agent Skills
├── dragonos-gvisor-test-analysis/ # DragonOS gVisor 测试失败分析 Skill
│ ├── SKILL.md # Skill 说明文件
│ └── references/ # 存放参考文档与格式说明
│ └── FORMAT.md # 分析报告格式说明
└── ... # 其他 Skills
```
@@ -0,0 +1,148 @@
---
name: dragonos-gvisor-test-analysis
description: 通过对比 Linux/gvisor 参考实现来分析 DragonOS gVisor 测试失败。输出结构化的修复文档,包含对于所有失败用例的表格格式分析文档,针对每个具体的失败用例的详细格式修复文档,并提供代码片段。当用户提及 gVisor 测试失败、特定测试用例或询问 bug 分析/修复方案时使用。
version: 0.2.0
allowed-tools: Read, Grep, Glob, Bash
---
# DragonOS gVisor 测试失败分析器
## 目的
通过参考 Linux 内核和 gVisor 实现来分析 DragonOS 在 gVisor 测试套件中的失败。输出识别根本原因并提供可执行修复计划的文档。
## 参考路径
```
gVisor 测试: ../gvisor/test/syscalls/linux/
Linux 内核: ../linux/kernel/
DragonOS: kernel/src/
```
## 工作流程
### 步骤 1: 解析测试失败
从用户输入中提取:
- 所有失败的测试名称(格式:`TestSuite.TestCase`
- GTEST 输出消息,例如:
```
[ RUN ] WaitTest.Wait4Rusage
[ FAILED ] WaitTest.Wait4Rusage (0 ms)
```
- 错误模式或 panic 消息
- 堆栈跟踪(如果存在)
### 步骤 2: 定位测试代码
查找 gVisor 测试实现:
```
使用 Glob 查找: ../gvisor/test/syscalls/linux/*<syscall>*.cc
使用 Grep 查找: TEST.*<test_name>
```
### 步骤 3: 追踪系统调用路径
映射调用链:
```
测试 → 系统调用 → DragonOS 实现 → Bug
```
查找 DragonOS 实现:
```
使用 Grep 查找: fn sys_<syscall_name> 或 syscall!(<syscall_name>)
```
### 步骤 4: 对比 Linux 参考
查找 Linux 参考实现:
```
在 ../linux 中使用 Grep: SYSCALL_DEFINE.*<syscall_name>
```
### 步骤 5: 生成概览修复文档的“测试范围理解”和“内核子系统现状”部分
遵循 `references/FORMAT.md` 中的"概览格式"部分,生成其前两部分:
- 测试范围理解
- 内核子系统现状
### 步骤六: 循环生成详细单个测试修复文档
对于每个失败的测试,遵循 `references/FORMAT.md` 中的"单个测试格式"部分,生成详细的修复文档,知道没有更多失败测试需要处理为止。
### 步骤七:生成概览文档的"根因分析"和"修复建议"部分
结合 Overview 和 Detailed 文档,生成概览文档的最后两部分:
#### 7.1 生成第三部分:根因分析表格
汇总所有详细文档中的根因,提炼共性偏差:
```markdown
## 三、根因分析
| 测试点 | Linux 期望 | DragonOS 实际 | 差距 |
|-------|-----------|---------------|------|
| `[接口/字段]` | [Linux 行为] | [DragonOS 行为] | [偏差说明] |
| `[接口/字段]` | [Linux 行为] | [DragonOS 行为] | [偏差说明] |
```
**提炼规则**
- 每行对应一个"接口/字段"级别的偏差
- 如果多个测试共享同一根因,在"差距"列注明 `N 个测试)`
- 优先描述数据结构/状态层面的差异,而非行为表现
- 引用具体文件和行号作为证据
#### 7.2 生成第四部分:修复方案
##### 7.2.1 生成关键改动表格
```markdown
## 四、修复方案
### 4.1 关键改动
| 文件 | 改动 | 原因 |
|-----|------|------|
| `kernel/src/xxx.rs` | [具体修改] | [修改原因] |
| `kernel/src/yyy.rs` | [具体修改] | [修改原因] |
```
**生成规则**
- 从所有 Detailed 文档的"修复方案"部分汇总
- 去重合并:同一文件的多个修改合并为一条
- 按依赖关系排序(基础改动在前)
- 原因列引用对应的根因("差距"列)
##### 7.2.2 生成实现细节
```markdown
### 4.2 实现细节
[补充关键实现注意事项、依赖关系、风险点等]
```
**内容规则**
- 说明跨文件修改的依赖顺序
- 标注可能影响的其他子系统(向后兼容性检查,防止回归)
- 列出需要同步修改的测试/文档
- 注明未完全实现的边缘情况(如果存在)
## 示例
完整的输入输出示例和详细使用场景,请参见 [EXAMPLES.md](references/EXAMPLES.md)。
该文件包含:
- 单个测试失败分析示例
- 多个测试失败批量分析示例
- 测试失败输出模式识别
- 系统调用路径追踪示例
- 根本原因分组示例
## 注意事项
- 始终引用 `file:line` 作为代码参考
- 代码片段应最小化(最多 5-10 行)
- 级联失败:注明哪个测试是根本原因
- 提出修复方案时考虑 DragonOS 架构约束
@@ -0,0 +1,146 @@
# 示例
本文件包含 dragonos-gvisor-test-analysis skill 的使用示例。
## 单个测试失败分析
**输入**
```
分析一下 WaitTest.Wait4Rusage 为什么失败
```
**处理流程**(符合 7 步工作流):
1. **步骤 1** - 解析测试失败:提取 `WaitTest.Wait4Rusage`、错误消息、堆栈跟踪
2. **步骤 2** - 定位测试代码:`Glob` 查找 `../gvisor/test/syscalls/linux/*wait*.cc``Grep` 查找 `TEST.*Wait4Rusage`
3. **步骤 3** - 追踪系统调用路径:映射 `wait4` → DragonOS 实现 `kernel/src/process/exit.rs`
4. **步骤 4** - 对比 Linux 参考:在 `../linux``Grep` 查找 `SYSCALL_DEFINE.*wait4`
5. *(跳过)* - 单个测试无需生成概览文档的第一、二部分
6. **步骤 6** - 生成详细格式修复文档:遵循 FORMAT.md"单个测试格式",包含代码片段和逐行对比
7. *(跳过)* - 单个测试无需生成概览文档的第三、四部分
**输出格式**:详细格式(单个测试格式)
- 包含来自 `exit.c:wait4``process/exit.rs` 的代码片段
- 逐行对比分析
- 详细的修复步骤
详见 [FORMAT.md](FORMAT.md) 中的"单个测试格式"部分。
---
## 多个测试失败批量分析
**输入**
```
wait_test 失败了20个测试用例,包括 Wait4Rusage, WaitidRusage, WaitAnyChildTest.*,
请对比 Linux 和 gvisor 的实现,分析失败原因并给出修复方案
```
**处理流程**(完整 7 步工作流):
1. **步骤 1** - 解析测试失败:提取出 20 个测试用例的名称、错误消息、堆栈跟踪
2. **步骤 2** - 定位测试代码:`Glob` 查找 `../gvisor/test/syscalls/linux/*wait*.cc``Grep` 查找各测试用例
3. **步骤 3** - 追踪系统调用路径:映射 `wait4/waitid` → DragonOS 实现
4. **步骤 4** - 对比 Linux 参考:在 `../linux` 中查找 `SYSCALL_DEFINE` 定义
5. **步骤 5** - 生成概览文档第一、二部分:遵循 FORMAT.md"概览格式",生成"测试范围理解"和"内核子系统现状"
6. **步骤 6** - 循环生成详细文档:对每个测试生成"单个测试格式"文档,直到没有更多失败测试
7. **步骤 7** - 生成概览文档第三、四部分:
- 7.1 汇总所有详细文档的根因,提炼共性偏差,生成"根因分析"表格
- 7.2 汇总所有修复方案,去重合并,生成"修复方案"部分(关键改动表格 + 实现细节)
**输出格式**:概览格式(表格格式) + 详细格式(单个测试格式)
- 概览文档:包含测试范围、内核现状、根因分析表格、修复方案表格
- 详细文档:每个测试一个文档,包含代码片段和逐行对比
详见 [FORMAT.md](FORMAT.md) 中的"概览格式"和"单个测试格式"部分。
---
## 测试失败输出模式识别
**输入(GTEST 输出)**
```
[ RUN ] WaitTest.Wait4Rusage
[ FAILED ] WaitTest.Wait4Rusage (0 ms)
```
**识别内容**
- 测试套件:`WaitTest`
- 测试用例:`Wait4Rusage`
- 完整名称:`WaitTest.Wait4Rusage`
- 失败状态:`FAILED`
**输入(panic 消息)**
```
panicked at 'assertion failed: `(left == right)`
left: `12`,
right: `0`', kernel/src/process/exit.rs:42:13
```
**识别内容**
- Panic 位置:`kernel/src/process/exit.rs:42:13`
- 断言失败:期望值 0,实际值 12
- 可能根因:`rusage` 结构体字段未正确初始化
---
## 系统调用路径追踪示例
**目标**:追踪 `wait4` 系统调用
**步骤**
1. **查找 gVisor 测试**
```
Glob: ../gvisor/test/syscalls/linux/*wait*.cc
Grep: TEST.*Wait4Rusage
```
2. **查找 DragonOS 实现**
```
Grep: fn sys_wait4
Grep: syscall!(wait4)
```
3. **查找 Linux 参考**
```
Grep (in ../linux): SYSCALL_DEFINE.*wait4
```
4. **映射调用链**
```
WaitTest.Wait4Rusage (测试)
→ gVisor test/cc (测试代码)
→ wait4 syscall (系统调用)
→ DragonOS kernel/src/process/exit.rs (DragonOS 实现)
→ Bug: rusage 未初始化
```
---
## 根本原因分组示例
当有多个测试失败时,按根本原因分组而非按测试套件分组:
**错误的分组**(按测试套件):
```
WaitTest: 5 个失败
WaitidTest: 3 个失败
SignalTest: 4 个失败
```
**正确的分组**(按根本原因):
```
根因 1: rusage 结构体未正确初始化
- WaitTest.Wait4Rusage
- WaitTest.WaitidRusage
- SignalTest.WaitidRusage
根因 2: 进程状态转换错误
- WaitTest.WaitAnyChildTest.Pid
- WaitTest.WaitAnyChildTest.Pgid
根因 3: 信号处理不完整
- SignalTest.SignalDelivery
- SignalTest.SignalMask
...
```
这样可以一次性解决所有相关问题,而不是逐个修复。
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# DragonOS Bug Fix 文档格式规范
本文档定义了两种标准的修复文档格式:概览格式(用于总览多个测试分析和修复方案)和单个测试格式(用于深度分析)。
---
## 格式一:概览格式(Overview Format
用于分析 3+ 个测试失败时,提供结构化的四部分分析文档。
### 模板
```markdown
# 修复 <test_suite_or_syscall> 测试
## 一、测试范围理解
### 1.1 测试目标
[简述测试要验证的系统调用或功能模块]
### 1.2 关键测试用例
| 用例名称 | 验证行为 | 状态 |
|---------|---------|------|
| `TestSuite.TestCase1` | [测试目的] | ❌ FAIL |
| `TestSuite.TestCase2` | [测试目的] | ❌ FAIL |
| `TestSuite.TestCase3` | [测试目的] | ❌ FAIL |
---
## 二、内核子系统现状
### 2.1 相关子系统
- [子系统1][职责说明]
- [子系统2][职责说明]
### 2.2 当前实现的问题
- [问题点1]
- [问题点2]
---
## 三、根因分析
| 测试点 | Linux 期望 | DragonOS 实际 | 差距 |
|-------|-----------|---------------|------|
| `[接口/字段]` | [Linux 行为] | [DragonOS 行为] | [偏差说明] |
| `[接口/字段]` | [Linux 行为] | [DragonOS 行为] | [偏差说明] |
---
## 四、修复方案
### 4.1 关键改动
| 文件 | 改动 | 原因 |
|-----|------|------|
| `kernel/src/xxx.rs` | [具体修改] | [修改原因] |
| `kernel/src/yyy.rs` | [具体修改] | [修改原因] |
### 4.2 实现细节
[补充关键实现注意事项、依赖关系、风险点等]
```
### 实际示例
<!-- TODO: 添加实际示例 -->
---
## 格式二:单个测试格式(Single Test Format
用于 1-2 个具体测试失败的深度分析,包含代码片段和行号引用。
### 模板
```
# Bug Fix: <test_suite>.<test_case>
## 根因分析
[详细描述问题的本质,为什么会产生这个错误]
## 测试行为
**gVisor 测试**: `../gvisor/test/syscalls/linux/<file>.cc:<line>`
测试逻辑:
- [步骤1]
- [步骤2]
- ...
- [步骤x]
- [预期结果]
```c
// ../gvisor/test/syscalls/linux/<file>.cc:<line>
TEST(<Test_name>, <Test_case>) {
[足够说明测试逻辑的代码片段,行数不被全局约束所限制]
}
```
**实际错误**: [错误信息或现象]
## 参考实现(Linux
**文件**: `../linux/<path>.c`
```c
// <line_number>
[ 5-10 ]
```
关键语义:
- [语义点1]
- [语义点2]
## DragonOS 当前实现
**文件**: `kernel/src/<path>.rs`
```rust
// <line_number>
[]
```
问题:
- [缺失/错误的逻辑]
- [与 Linux 的差异]
## 修复方案
1. [具体修改1 - 在某文件添加某逻辑]
2. [具体修改2 - 修改某函数的某行为]
## 变更范围
- **文件**: `kernel/src/xxx.rs`, `kernel/src/yyy.rs`
- **风险**: [描述可能的副作用或兼容性问题]
- **依赖**: [如果涉及多个修改,说明依赖顺序]
## 预期结果
- [测试通过条件]
- [副作用检查]
```
### 实际示例
<!-- TODO: 添加实际示例 -->
---
## 通用规则
### 引用规范
- Linux 参考: `../linux/<path>.c:<line>` 或 `function_name`
- gVisor 测试: `../gvisor/test/syscalls/linux/<file>.cc:<line>`
- DragonOS: `kernel/src/<path>.rs:<line>`
### 代码片段
- 最多 20 行,只包含关键逻辑
- 始终标注文件路径和行号
- 使用实际代码,非伪代码
### 表格单元格
- 最多 20 词
- 使用技术术语,避免冗长解释
- 多个测试共享同一原因/修复时,注明 "(N 个测试)"
### 根因描述
- 先说数据结构/状态问题,后说行为表现
- 引用 Linux/gvisor 的具体语义
- 说明 DragonOS 当前实现的偏差点
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+356
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---
name: skill-creator
description: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
license: Complete terms in LICENSE.txt
---
# Skill Creator
This skill provides guidance for creating effective skills.
## About Skills
Skills are modular, self-contained packages that extend Claude's capabilities by providing
specialized knowledge, workflows, and tools. Think of them as "onboarding guides" for specific
domains or tasks—they transform Claude from a general-purpose agent into a specialized agent
equipped with procedural knowledge that no model can fully possess.
### What Skills Provide
1. Specialized workflows - Multi-step procedures for specific domains
2. Tool integrations - Instructions for working with specific file formats or APIs
3. Domain expertise - Company-specific knowledge, schemas, business logic
4. Bundled resources - Scripts, references, and assets for complex and repetitive tasks
## Core Principles
### Concise is Key
The context window is a public good. Skills share the context window with everything else Claude needs: system prompt, conversation history, other Skills' metadata, and the actual user request.
**Default assumption: Claude is already very smart.** Only add context Claude doesn't already have. Challenge each piece of information: "Does Claude really need this explanation?" and "Does this paragraph justify its token cost?"
Prefer concise examples over verbose explanations.
### Set Appropriate Degrees of Freedom
Match the level of specificity to the task's fragility and variability:
**High freedom (text-based instructions)**: Use when multiple approaches are valid, decisions depend on context, or heuristics guide the approach.
**Medium freedom (pseudocode or scripts with parameters)**: Use when a preferred pattern exists, some variation is acceptable, or configuration affects behavior.
**Low freedom (specific scripts, few parameters)**: Use when operations are fragile and error-prone, consistency is critical, or a specific sequence must be followed.
Think of Claude as exploring a path: a narrow bridge with cliffs needs specific guardrails (low freedom), while an open field allows many routes (high freedom).
### Anatomy of a Skill
Every skill consists of a required SKILL.md file and optional bundled resources:
```
skill-name/
├── SKILL.md (required)
│ ├── YAML frontmatter metadata (required)
│ │ ├── name: (required)
│ │ └── description: (required)
│ └── Markdown instructions (required)
└── Bundled Resources (optional)
├── scripts/ - Executable code (Python/Bash/etc.)
├── references/ - Documentation intended to be loaded into context as needed
└── assets/ - Files used in output (templates, icons, fonts, etc.)
```
#### SKILL.md (required)
Every SKILL.md consists of:
- **Frontmatter** (YAML): Contains `name` and `description` fields. These are the only fields that Claude reads to determine when the skill gets used, thus it is very important to be clear and comprehensive in describing what the skill is, and when it should be used.
- **Body** (Markdown): Instructions and guidance for using the skill. Only loaded AFTER the skill triggers (if at all).
#### Bundled Resources (optional)
##### Scripts (`scripts/`)
Executable code (Python/Bash/etc.) for tasks that require deterministic reliability or are repeatedly rewritten.
- **When to include**: When the same code is being rewritten repeatedly or deterministic reliability is needed
- **Example**: `scripts/rotate_pdf.py` for PDF rotation tasks
- **Benefits**: Token efficient, deterministic, may be executed without loading into context
- **Note**: Scripts may still need to be read by Claude for patching or environment-specific adjustments
##### References (`references/`)
Documentation and reference material intended to be loaded as needed into context to inform Claude's process and thinking.
- **When to include**: For documentation that Claude should reference while working
- **Examples**: `references/finance.md` for financial schemas, `references/mnda.md` for company NDA template, `references/policies.md` for company policies, `references/api_docs.md` for API specifications
- **Use cases**: Database schemas, API documentation, domain knowledge, company policies, detailed workflow guides
- **Benefits**: Keeps SKILL.md lean, loaded only when Claude determines it's needed
- **Best practice**: If files are large (>10k words), include grep search patterns in SKILL.md
- **Avoid duplication**: Information should live in either SKILL.md or references files, not both. Prefer references files for detailed information unless it's truly core to the skill—this keeps SKILL.md lean while making information discoverable without hogging the context window. Keep only essential procedural instructions and workflow guidance in SKILL.md; move detailed reference material, schemas, and examples to references files.
##### Assets (`assets/`)
Files not intended to be loaded into context, but rather used within the output Claude produces.
- **When to include**: When the skill needs files that will be used in the final output
- **Examples**: `assets/logo.png` for brand assets, `assets/slides.pptx` for PowerPoint templates, `assets/frontend-template/` for HTML/React boilerplate, `assets/font.ttf` for typography
- **Use cases**: Templates, images, icons, boilerplate code, fonts, sample documents that get copied or modified
- **Benefits**: Separates output resources from documentation, enables Claude to use files without loading them into context
#### What to Not Include in a Skill
A skill should only contain essential files that directly support its functionality. Do NOT create extraneous documentation or auxiliary files, including:
- README.md
- INSTALLATION_GUIDE.md
- QUICK_REFERENCE.md
- CHANGELOG.md
- etc.
The skill should only contain the information needed for an AI agent to do the job at hand. It should not contain auxilary context about the process that went into creating it, setup and testing procedures, user-facing documentation, etc. Creating additional documentation files just adds clutter and confusion.
### Progressive Disclosure Design Principle
Skills use a three-level loading system to manage context efficiently:
1. **Metadata (name + description)** - Always in context (~100 words)
2. **SKILL.md body** - When skill triggers (<5k words)
3. **Bundled resources** - As needed by Claude (Unlimited because scripts can be executed without reading into context window)
#### Progressive Disclosure Patterns
Keep SKILL.md body to the essentials and under 500 lines to minimize context bloat. Split content into separate files when approaching this limit. When splitting out content into other files, it is very important to reference them from SKILL.md and describe clearly when to read them, to ensure the reader of the skill knows they exist and when to use them.
**Key principle:** When a skill supports multiple variations, frameworks, or options, keep only the core workflow and selection guidance in SKILL.md. Move variant-specific details (patterns, examples, configuration) into separate reference files.
**Pattern 1: High-level guide with references**
```markdown
# PDF Processing
## Quick start
Extract text with pdfplumber:
[code example]
## Advanced features
- **Form filling**: See [FORMS.md](FORMS.md) for complete guide
- **API reference**: See [REFERENCE.md](REFERENCE.md) for all methods
- **Examples**: See [EXAMPLES.md](EXAMPLES.md) for common patterns
```
Claude loads FORMS.md, REFERENCE.md, or EXAMPLES.md only when needed.
**Pattern 2: Domain-specific organization**
For Skills with multiple domains, organize content by domain to avoid loading irrelevant context:
```
bigquery-skill/
├── SKILL.md (overview and navigation)
└── reference/
├── finance.md (revenue, billing metrics)
├── sales.md (opportunities, pipeline)
├── product.md (API usage, features)
└── marketing.md (campaigns, attribution)
```
When a user asks about sales metrics, Claude only reads sales.md.
Similarly, for skills supporting multiple frameworks or variants, organize by variant:
```
cloud-deploy/
├── SKILL.md (workflow + provider selection)
└── references/
├── aws.md (AWS deployment patterns)
├── gcp.md (GCP deployment patterns)
└── azure.md (Azure deployment patterns)
```
When the user chooses AWS, Claude only reads aws.md.
**Pattern 3: Conditional details**
Show basic content, link to advanced content:
```markdown
# DOCX Processing
## Creating documents
Use docx-js for new documents. See [DOCX-JS.md](DOCX-JS.md).
## Editing documents
For simple edits, modify the XML directly.
**For tracked changes**: See [REDLINING.md](REDLINING.md)
**For OOXML details**: See [OOXML.md](OOXML.md)
```
Claude reads REDLINING.md or OOXML.md only when the user needs those features.
**Important guidelines:**
- **Avoid deeply nested references** - Keep references one level deep from SKILL.md. All reference files should link directly from SKILL.md.
- **Structure longer reference files** - For files longer than 100 lines, include a table of contents at the top so Claude can see the full scope when previewing.
## Skill Creation Process
Skill creation involves these steps:
1. Understand the skill with concrete examples
2. Plan reusable skill contents (scripts, references, assets)
3. Initialize the skill (run init_skill.py)
4. Edit the skill (implement resources and write SKILL.md)
5. Package the skill (run package_skill.py)
6. Iterate based on real usage
Follow these steps in order, skipping only if there is a clear reason why they are not applicable.
### Step 1: Understanding the Skill with Concrete Examples
Skip this step only when the skill's usage patterns are already clearly understood. It remains valuable even when working with an existing skill.
To create an effective skill, clearly understand concrete examples of how the skill will be used. This understanding can come from either direct user examples or generated examples that are validated with user feedback.
For example, when building an image-editor skill, relevant questions include:
- "What functionality should the image-editor skill support? Editing, rotating, anything else?"
- "Can you give some examples of how this skill would be used?"
- "I can imagine users asking for things like 'Remove the red-eye from this image' or 'Rotate this image'. Are there other ways you imagine this skill being used?"
- "What would a user say that should trigger this skill?"
To avoid overwhelming users, avoid asking too many questions in a single message. Start with the most important questions and follow up as needed for better effectiveness.
Conclude this step when there is a clear sense of the functionality the skill should support.
### Step 2: Planning the Reusable Skill Contents
To turn concrete examples into an effective skill, analyze each example by:
1. Considering how to execute on the example from scratch
2. Identifying what scripts, references, and assets would be helpful when executing these workflows repeatedly
Example: When building a `pdf-editor` skill to handle queries like "Help me rotate this PDF," the analysis shows:
1. Rotating a PDF requires re-writing the same code each time
2. A `scripts/rotate_pdf.py` script would be helpful to store in the skill
Example: When designing a `frontend-webapp-builder` skill for queries like "Build me a todo app" or "Build me a dashboard to track my steps," the analysis shows:
1. Writing a frontend webapp requires the same boilerplate HTML/React each time
2. An `assets/hello-world/` template containing the boilerplate HTML/React project files would be helpful to store in the skill
Example: When building a `big-query` skill to handle queries like "How many users have logged in today?" the analysis shows:
1. Querying BigQuery requires re-discovering the table schemas and relationships each time
2. A `references/schema.md` file documenting the table schemas would be helpful to store in the skill
To establish the skill's contents, analyze each concrete example to create a list of the reusable resources to include: scripts, references, and assets.
### Step 3: Initializing the Skill
At this point, it is time to actually create the skill.
Skip this step only if the skill being developed already exists, and iteration or packaging is needed. In this case, continue to the next step.
When creating a new skill from scratch, always run the `init_skill.py` script. The script conveniently generates a new template skill directory that automatically includes everything a skill requires, making the skill creation process much more efficient and reliable.
Usage:
```bash
scripts/init_skill.py <skill-name> --path <output-directory>
```
The script:
- Creates the skill directory at the specified path
- Generates a SKILL.md template with proper frontmatter and TODO placeholders
- Creates example resource directories: `scripts/`, `references/`, and `assets/`
- Adds example files in each directory that can be customized or deleted
After initialization, customize or remove the generated SKILL.md and example files as needed.
### Step 4: Edit the Skill
When editing the (newly-generated or existing) skill, remember that the skill is being created for another instance of Claude to use. Include information that would be beneficial and non-obvious to Claude. Consider what procedural knowledge, domain-specific details, or reusable assets would help another Claude instance execute these tasks more effectively.
#### Learn Proven Design Patterns
Consult these helpful guides based on your skill's needs:
- **Multi-step processes**: See references/workflows.md for sequential workflows and conditional logic
- **Specific output formats or quality standards**: See references/output-patterns.md for template and example patterns
These files contain established best practices for effective skill design.
#### Start with Reusable Skill Contents
To begin implementation, start with the reusable resources identified above: `scripts/`, `references/`, and `assets/` files. Note that this step may require user input. For example, when implementing a `brand-guidelines` skill, the user may need to provide brand assets or templates to store in `assets/`, or documentation to store in `references/`.
Added scripts must be tested by actually running them to ensure there are no bugs and that the output matches what is expected. If there are many similar scripts, only a representative sample needs to be tested to ensure confidence that they all work while balancing time to completion.
Any example files and directories not needed for the skill should be deleted. The initialization script creates example files in `scripts/`, `references/`, and `assets/` to demonstrate structure, but most skills won't need all of them.
#### Update SKILL.md
**Writing Guidelines:** Always use imperative/infinitive form.
##### Frontmatter
Write the YAML frontmatter with `name` and `description`:
- `name`: The skill name
- `description`: This is the primary triggering mechanism for your skill, and helps Claude understand when to use the skill.
- Include both what the Skill does and specific triggers/contexts for when to use it.
- Include all "when to use" information here - Not in the body. The body is only loaded after triggering, so "When to Use This Skill" sections in the body are not helpful to Claude.
- Example description for a `docx` skill: "Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. Use when Claude needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks"
Do not include any other fields in YAML frontmatter.
##### Body
Write instructions for using the skill and its bundled resources.
### Step 5: Packaging a Skill
Once development of the skill is complete, it must be packaged into a distributable .skill file that gets shared with the user. The packaging process automatically validates the skill first to ensure it meets all requirements:
```bash
scripts/package_skill.py <path/to/skill-folder>
```
Optional output directory specification:
```bash
scripts/package_skill.py <path/to/skill-folder> ./dist
```
The packaging script will:
1. **Validate** the skill automatically, checking:
- YAML frontmatter format and required fields
- Skill naming conventions and directory structure
- Description completeness and quality
- File organization and resource references
2. **Package** the skill if validation passes, creating a .skill file named after the skill (e.g., `my-skill.skill`) that includes all files and maintains the proper directory structure for distribution. The .skill file is a zip file with a .skill extension.
If validation fails, the script will report the errors and exit without creating a package. Fix any validation errors and run the packaging command again.
### Step 6: Iterate
After testing the skill, users may request improvements. Often this happens right after using the skill, with fresh context of how the skill performed.
**Iteration workflow:**
1. Use the skill on real tasks
2. Notice struggles or inefficiencies
3. Identify how SKILL.md or bundled resources should be updated
4. Implement changes and test again
@@ -0,0 +1,82 @@
# Output Patterns
Use these patterns when skills need to produce consistent, high-quality output.
## Template Pattern
Provide templates for output format. Match the level of strictness to your needs.
**For strict requirements (like API responses or data formats):**
```markdown
## Report structure
ALWAYS use this exact template structure:
# [Analysis Title]
## Executive summary
[One-paragraph overview of key findings]
## Key findings
- Finding 1 with supporting data
- Finding 2 with supporting data
- Finding 3 with supporting data
## Recommendations
1. Specific actionable recommendation
2. Specific actionable recommendation
```
**For flexible guidance (when adaptation is useful):**
```markdown
## Report structure
Here is a sensible default format, but use your best judgment:
# [Analysis Title]
## Executive summary
[Overview]
## Key findings
[Adapt sections based on what you discover]
## Recommendations
[Tailor to the specific context]
Adjust sections as needed for the specific analysis type.
```
## Examples Pattern
For skills where output quality depends on seeing examples, provide input/output pairs:
```markdown
## Commit message format
Generate commit messages following these examples:
**Example 1:**
Input: Added user authentication with JWT tokens
Output:
```
feat(auth): implement JWT-based authentication
Add login endpoint and token validation middleware
```
**Example 2:**
Input: Fixed bug where dates displayed incorrectly in reports
Output:
```
fix(reports): correct date formatting in timezone conversion
Use UTC timestamps consistently across report generation
```
Follow this style: type(scope): brief description, then detailed explanation.
```
Examples help Claude understand the desired style and level of detail more clearly than descriptions alone.
@@ -0,0 +1,28 @@
# Workflow Patterns
## Sequential Workflows
For complex tasks, break operations into clear, sequential steps. It is often helpful to give Claude an overview of the process towards the beginning of SKILL.md:
```markdown
Filling a PDF form involves these steps:
1. Analyze the form (run analyze_form.py)
2. Create field mapping (edit fields.json)
3. Validate mapping (run validate_fields.py)
4. Fill the form (run fill_form.py)
5. Verify output (run verify_output.py)
```
## Conditional Workflows
For tasks with branching logic, guide Claude through decision points:
```markdown
1. Determine the modification type:
**Creating new content?** → Follow "Creation workflow" below
**Editing existing content?** → Follow "Editing workflow" below
2. Creation workflow: [steps]
3. Editing workflow: [steps]
```
+303
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@@ -0,0 +1,303 @@
#!/usr/bin/env python3
"""
Skill Initializer - Creates a new skill from template
Usage:
init_skill.py <skill-name> --path <path>
Examples:
init_skill.py my-new-skill --path skills/public
init_skill.py my-api-helper --path skills/private
init_skill.py custom-skill --path /custom/location
"""
import sys
from pathlib import Path
SKILL_TEMPLATE = """---
name: {skill_name}
description: [TODO: Complete and informative explanation of what the skill does and when to use it. Include WHEN to use this skill - specific scenarios, file types, or tasks that trigger it.]
---
# {skill_title}
## Overview
[TODO: 1-2 sentences explaining what this skill enables]
## Structuring This Skill
[TODO: Choose the structure that best fits this skill's purpose. Common patterns:
**1. Workflow-Based** (best for sequential processes)
- Works well when there are clear step-by-step procedures
- Example: DOCX skill with "Workflow Decision Tree""Reading""Creating""Editing"
- Structure: ## Overview → ## Workflow Decision Tree → ## Step 1 → ## Step 2...
**2. Task-Based** (best for tool collections)
- Works well when the skill offers different operations/capabilities
- Example: PDF skill with "Quick Start""Merge PDFs""Split PDFs""Extract Text"
- Structure: ## Overview → ## Quick Start → ## Task Category 1 → ## Task Category 2...
**3. Reference/Guidelines** (best for standards or specifications)
- Works well for brand guidelines, coding standards, or requirements
- Example: Brand styling with "Brand Guidelines""Colors""Typography""Features"
- Structure: ## Overview → ## Guidelines → ## Specifications → ## Usage...
**4. Capabilities-Based** (best for integrated systems)
- Works well when the skill provides multiple interrelated features
- Example: Product Management with "Core Capabilities" → numbered capability list
- Structure: ## Overview → ## Core Capabilities → ### 1. Feature → ### 2. Feature...
Patterns can be mixed and matched as needed. Most skills combine patterns (e.g., start with task-based, add workflow for complex operations).
Delete this entire "Structuring This Skill" section when done - it's just guidance.]
## [TODO: Replace with the first main section based on chosen structure]
[TODO: Add content here. See examples in existing skills:
- Code samples for technical skills
- Decision trees for complex workflows
- Concrete examples with realistic user requests
- References to scripts/templates/references as needed]
## Resources
This skill includes example resource directories that demonstrate how to organize different types of bundled resources:
### scripts/
Executable code (Python/Bash/etc.) that can be run directly to perform specific operations.
**Examples from other skills:**
- PDF skill: `fill_fillable_fields.py`, `extract_form_field_info.py` - utilities for PDF manipulation
- DOCX skill: `document.py`, `utilities.py` - Python modules for document processing
**Appropriate for:** Python scripts, shell scripts, or any executable code that performs automation, data processing, or specific operations.
**Note:** Scripts may be executed without loading into context, but can still be read by Claude for patching or environment adjustments.
### references/
Documentation and reference material intended to be loaded into context to inform Claude's process and thinking.
**Examples from other skills:**
- Product management: `communication.md`, `context_building.md` - detailed workflow guides
- BigQuery: API reference documentation and query examples
- Finance: Schema documentation, company policies
**Appropriate for:** In-depth documentation, API references, database schemas, comprehensive guides, or any detailed information that Claude should reference while working.
### assets/
Files not intended to be loaded into context, but rather used within the output Claude produces.
**Examples from other skills:**
- Brand styling: PowerPoint template files (.pptx), logo files
- Frontend builder: HTML/React boilerplate project directories
- Typography: Font files (.ttf, .woff2)
**Appropriate for:** Templates, boilerplate code, document templates, images, icons, fonts, or any files meant to be copied or used in the final output.
---
**Any unneeded directories can be deleted.** Not every skill requires all three types of resources.
"""
EXAMPLE_SCRIPT = '''#!/usr/bin/env python3
"""
Example helper script for {skill_name}
This is a placeholder script that can be executed directly.
Replace with actual implementation or delete if not needed.
Example real scripts from other skills:
- pdf/scripts/fill_fillable_fields.py - Fills PDF form fields
- pdf/scripts/convert_pdf_to_images.py - Converts PDF pages to images
"""
def main():
print("This is an example script for {skill_name}")
# TODO: Add actual script logic here
# This could be data processing, file conversion, API calls, etc.
if __name__ == "__main__":
main()
'''
EXAMPLE_REFERENCE = """# Reference Documentation for {skill_title}
This is a placeholder for detailed reference documentation.
Replace with actual reference content or delete if not needed.
Example real reference docs from other skills:
- product-management/references/communication.md - Comprehensive guide for status updates
- product-management/references/context_building.md - Deep-dive on gathering context
- bigquery/references/ - API references and query examples
## When Reference Docs Are Useful
Reference docs are ideal for:
- Comprehensive API documentation
- Detailed workflow guides
- Complex multi-step processes
- Information too lengthy for main SKILL.md
- Content that's only needed for specific use cases
## Structure Suggestions
### API Reference Example
- Overview
- Authentication
- Endpoints with examples
- Error codes
- Rate limits
### Workflow Guide Example
- Prerequisites
- Step-by-step instructions
- Common patterns
- Troubleshooting
- Best practices
"""
EXAMPLE_ASSET = """# Example Asset File
This placeholder represents where asset files would be stored.
Replace with actual asset files (templates, images, fonts, etc.) or delete if not needed.
Asset files are NOT intended to be loaded into context, but rather used within
the output Claude produces.
Example asset files from other skills:
- Brand guidelines: logo.png, slides_template.pptx
- Frontend builder: hello-world/ directory with HTML/React boilerplate
- Typography: custom-font.ttf, font-family.woff2
- Data: sample_data.csv, test_dataset.json
## Common Asset Types
- Templates: .pptx, .docx, boilerplate directories
- Images: .png, .jpg, .svg, .gif
- Fonts: .ttf, .otf, .woff, .woff2
- Boilerplate code: Project directories, starter files
- Icons: .ico, .svg
- Data files: .csv, .json, .xml, .yaml
Note: This is a text placeholder. Actual assets can be any file type.
"""
def title_case_skill_name(skill_name):
"""Convert hyphenated skill name to Title Case for display."""
return ' '.join(word.capitalize() for word in skill_name.split('-'))
def init_skill(skill_name, path):
"""
Initialize a new skill directory with template SKILL.md.
Args:
skill_name: Name of the skill
path: Path where the skill directory should be created
Returns:
Path to created skill directory, or None if error
"""
# Determine skill directory path
skill_dir = Path(path).resolve() / skill_name
# Check if directory already exists
if skill_dir.exists():
print(f"❌ Error: Skill directory already exists: {skill_dir}")
return None
# Create skill directory
try:
skill_dir.mkdir(parents=True, exist_ok=False)
print(f"✅ Created skill directory: {skill_dir}")
except Exception as e:
print(f"❌ Error creating directory: {e}")
return None
# Create SKILL.md from template
skill_title = title_case_skill_name(skill_name)
skill_content = SKILL_TEMPLATE.format(
skill_name=skill_name,
skill_title=skill_title
)
skill_md_path = skill_dir / 'SKILL.md'
try:
skill_md_path.write_text(skill_content)
print("✅ Created SKILL.md")
except Exception as e:
print(f"❌ Error creating SKILL.md: {e}")
return None
# Create resource directories with example files
try:
# Create scripts/ directory with example script
scripts_dir = skill_dir / 'scripts'
scripts_dir.mkdir(exist_ok=True)
example_script = scripts_dir / 'example.py'
example_script.write_text(EXAMPLE_SCRIPT.format(skill_name=skill_name))
example_script.chmod(0o755)
print("✅ Created scripts/example.py")
# Create references/ directory with example reference doc
references_dir = skill_dir / 'references'
references_dir.mkdir(exist_ok=True)
example_reference = references_dir / 'api_reference.md'
example_reference.write_text(EXAMPLE_REFERENCE.format(skill_title=skill_title))
print("✅ Created references/api_reference.md")
# Create assets/ directory with example asset placeholder
assets_dir = skill_dir / 'assets'
assets_dir.mkdir(exist_ok=True)
example_asset = assets_dir / 'example_asset.txt'
example_asset.write_text(EXAMPLE_ASSET)
print("✅ Created assets/example_asset.txt")
except Exception as e:
print(f"❌ Error creating resource directories: {e}")
return None
# Print next steps
print(f"\n✅ Skill '{skill_name}' initialized successfully at {skill_dir}")
print("\nNext steps:")
print("1. Edit SKILL.md to complete the TODO items and update the description")
print("2. Customize or delete the example files in scripts/, references/, and assets/")
print("3. Run the validator when ready to check the skill structure")
return skill_dir
def main():
if len(sys.argv) < 4 or sys.argv[2] != '--path':
print("Usage: init_skill.py <skill-name> --path <path>")
print("\nSkill name requirements:")
print(" - Hyphen-case identifier (e.g., 'data-analyzer')")
print(" - Lowercase letters, digits, and hyphens only")
print(" - Max 40 characters")
print(" - Must match directory name exactly")
print("\nExamples:")
print(" init_skill.py my-new-skill --path skills/public")
print(" init_skill.py my-api-helper --path skills/private")
print(" init_skill.py custom-skill --path /custom/location")
sys.exit(1)
skill_name = sys.argv[1]
path = sys.argv[3]
print(f"🚀 Initializing skill: {skill_name}")
print(f" Location: {path}")
print()
result = init_skill(skill_name, path)
if result:
sys.exit(0)
else:
sys.exit(1)
if __name__ == "__main__":
main()
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#!/usr/bin/env python3
"""
Skill Packager - Creates a distributable .skill file of a skill folder
Usage:
python utils/package_skill.py <path/to/skill-folder> [output-directory]
Example:
python utils/package_skill.py skills/public/my-skill
python utils/package_skill.py skills/public/my-skill ./dist
"""
import sys
import zipfile
from pathlib import Path
from quick_validate import validate_skill
def package_skill(skill_path, output_dir=None):
"""
Package a skill folder into a .skill file.
Args:
skill_path: Path to the skill folder
output_dir: Optional output directory for the .skill file (defaults to current directory)
Returns:
Path to the created .skill file, or None if error
"""
skill_path = Path(skill_path).resolve()
# Validate skill folder exists
if not skill_path.exists():
print(f"❌ Error: Skill folder not found: {skill_path}")
return None
if not skill_path.is_dir():
print(f"❌ Error: Path is not a directory: {skill_path}")
return None
# Validate SKILL.md exists
skill_md = skill_path / "SKILL.md"
if not skill_md.exists():
print(f"❌ Error: SKILL.md not found in {skill_path}")
return None
# Run validation before packaging
print("🔍 Validating skill...")
valid, message = validate_skill(skill_path)
if not valid:
print(f"❌ Validation failed: {message}")
print(" Please fix the validation errors before packaging.")
return None
print(f"{message}\n")
# Determine output location
skill_name = skill_path.name
if output_dir:
output_path = Path(output_dir).resolve()
output_path.mkdir(parents=True, exist_ok=True)
else:
output_path = Path.cwd()
skill_filename = output_path / f"{skill_name}.skill"
# Create the .skill file (zip format)
try:
with zipfile.ZipFile(skill_filename, 'w', zipfile.ZIP_DEFLATED) as zipf:
# Walk through the skill directory
for file_path in skill_path.rglob('*'):
if file_path.is_file():
# Calculate the relative path within the zip
arcname = file_path.relative_to(skill_path.parent)
zipf.write(file_path, arcname)
print(f" Added: {arcname}")
print(f"\n✅ Successfully packaged skill to: {skill_filename}")
return skill_filename
except Exception as e:
print(f"❌ Error creating .skill file: {e}")
return None
def main():
if len(sys.argv) < 2:
print("Usage: python utils/package_skill.py <path/to/skill-folder> [output-directory]")
print("\nExample:")
print(" python utils/package_skill.py skills/public/my-skill")
print(" python utils/package_skill.py skills/public/my-skill ./dist")
sys.exit(1)
skill_path = sys.argv[1]
output_dir = sys.argv[2] if len(sys.argv) > 2 else None
print(f"📦 Packaging skill: {skill_path}")
if output_dir:
print(f" Output directory: {output_dir}")
print()
result = package_skill(skill_path, output_dir)
if result:
sys.exit(0)
else:
sys.exit(1)
if __name__ == "__main__":
main()
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#!/usr/bin/env python3
"""
Quick validation script for skills - minimal version
"""
import sys
import os
import re
import yaml
from pathlib import Path
def validate_skill(skill_path):
"""Basic validation of a skill"""
skill_path = Path(skill_path)
# Check SKILL.md exists
skill_md = skill_path / 'SKILL.md'
if not skill_md.exists():
return False, "SKILL.md not found"
# Read and validate frontmatter
content = skill_md.read_text()
if not content.startswith('---'):
return False, "No YAML frontmatter found"
# Extract frontmatter
match = re.match(r'^---\n(.*?)\n---', content, re.DOTALL)
if not match:
return False, "Invalid frontmatter format"
frontmatter_text = match.group(1)
# Parse YAML frontmatter
try:
frontmatter = yaml.safe_load(frontmatter_text)
if not isinstance(frontmatter, dict):
return False, "Frontmatter must be a YAML dictionary"
except yaml.YAMLError as e:
return False, f"Invalid YAML in frontmatter: {e}"
# Define allowed properties
ALLOWED_PROPERTIES = {'name', 'description', 'license', 'allowed-tools', 'metadata'}
# Check for unexpected properties (excluding nested keys under metadata)
unexpected_keys = set(frontmatter.keys()) - ALLOWED_PROPERTIES
if unexpected_keys:
return False, (
f"Unexpected key(s) in SKILL.md frontmatter: {', '.join(sorted(unexpected_keys))}. "
f"Allowed properties are: {', '.join(sorted(ALLOWED_PROPERTIES))}"
)
# Check required fields
if 'name' not in frontmatter:
return False, "Missing 'name' in frontmatter"
if 'description' not in frontmatter:
return False, "Missing 'description' in frontmatter"
# Extract name for validation
name = frontmatter.get('name', '')
if not isinstance(name, str):
return False, f"Name must be a string, got {type(name).__name__}"
name = name.strip()
if name:
# Check naming convention (hyphen-case: lowercase with hyphens)
if not re.match(r'^[a-z0-9-]+$', name):
return False, f"Name '{name}' should be hyphen-case (lowercase letters, digits, and hyphens only)"
if name.startswith('-') or name.endswith('-') or '--' in name:
return False, f"Name '{name}' cannot start/end with hyphen or contain consecutive hyphens"
# Check name length (max 64 characters per spec)
if len(name) > 64:
return False, f"Name is too long ({len(name)} characters). Maximum is 64 characters."
# Extract and validate description
description = frontmatter.get('description', '')
if not isinstance(description, str):
return False, f"Description must be a string, got {type(description).__name__}"
description = description.strip()
if description:
# Check for angle brackets
if '<' in description or '>' in description:
return False, "Description cannot contain angle brackets (< or >)"
# Check description length (max 1024 characters per spec)
if len(description) > 1024:
return False, f"Description is too long ({len(description)} characters). Maximum is 1024 characters."
return True, "Skill is valid!"
if __name__ == "__main__":
if len(sys.argv) != 2:
print("Usage: python quick_validate.py <skill_directory>")
sys.exit(1)
valid, message = validate_skill(sys.argv[1])
print(message)
sys.exit(0 if valid else 1)
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../.agents/skills
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../.agents/skills
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../.agents/skills