skill-creator by 0xdarkmatter/claude-mods
npx skills add https://github.com/0xdarkmatter/claude-mods --skill skill-creator本技能提供创建高效技能的指导。
技能是模块化、自包含的包,通过提供专业知识、工作流程和工具来扩展 Claude 的能力。可以将它们视为针对特定领域或任务的“入职指南”——它们将 Claude 从一个通用代理转变为配备有模型无法完全掌握的流程知识的专业代理。
官方 Anthropic 资源:
上下文窗口是公共资源。技能与 Claude 所需的其他一切共享上下文窗口:系统提示、对话历史、其他技能的元数据以及实际的用户请求。
默认假设:Claude 已经非常聪明。 只添加 Claude 尚不具备的上下文。挑战每一条信息:“Claude 真的需要这个解释吗?”以及“这段文字是否值得其 token 成本?”
优先使用简洁的示例,而非冗长的解释。
根据任务的脆弱性和可变性匹配具体程度:
高自由度(基于文本的说明):当存在多种有效方法、决策取决于上下文或启发式方法指导操作时使用。
中等自由度(带参数的伪代码或脚本):当存在首选模式、允许一些变化或配置影响行为时使用。
:当操作脆弱且容易出错、一致性至关重要或必须遵循特定顺序时使用。
This skill provides guidance for creating effective 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.
Official Anthropic Resources:
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.
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将 Claude 想象为探索一条路径:两侧是悬崖的狭窄桥梁需要特定的护栏(低自由度),而开阔的田野则允许多条路线(高自由度)。
每个技能都包含一个必需的 SKILL.md 文件和可选的捆绑资源:
skill-name/
├── SKILL.md (必需)
│ ├── YAML 前置元数据 (必需)
│ │ ├── name: (必需)
│ │ └── description: (必需)
│ └── Markdown 说明 (必需)
└── 捆绑资源 (可选)
├── scripts/ - 可执行代码 (Python/Bash/等)
├── references/ - 旨在根据需要加载到上下文中的文档
└── assets/ - 输出中使用的文件 (模板、图标、字体等)
每个 SKILL.md 包含:
name 和 description 字段。这些是 Claude 用来确定何时使用技能的唯一字段,因此在描述技能是什么以及何时应该使用时,清晰和全面非常重要。scripts/)用于需要确定性可靠性或需要重复重写的任务的可执行代码(Python/Bash/等)。
scripts/rotate_pdf.pyreferences/)旨在根据需要加载到上下文中以告知 Claude 流程和思考的文档和参考资料。
references/finance.md,用于公司 NDA 模板的 references/mnda.md,用于公司政策的 references/policies.md,用于 API 规范的 references/api_docs.mdassets/)不打算加载到上下文中,而是在 Claude 生成的输出中使用的文件。
assets/logo.png,用于 PowerPoint 模板的 assets/slides.pptx,用于 HTML/React 样板代码的 assets/frontend-template/,用于字体的 assets/font.ttf技能应仅包含直接支持其功能的基本文件。请勿创建无关的文档或辅助文件,包括:
技能应仅包含 AI 代理完成手头工作所需的信息。它不应包含关于创建它的过程、设置和测试程序、面向用户的文档等的辅助上下文。创建额外的文档文件只会增加混乱和困惑。
技能使用三级加载系统来高效管理上下文:
将 SKILL.md 正文保持在基本内容,并控制在 500 行以内,以最小化上下文膨胀。在接近此限制时,将内容拆分为单独的文件。将内容拆分到其他文件中时,从 SKILL.md 引用它们并清楚地描述何时读取它们非常重要,以确保技能的读者知道它们的存在以及何时使用它们。
关键原则: 当技能支持多种变体、框架或选项时,在 SKILL.md 中只保留核心工作流程和选择指导。将特定变体的详细信息(模式、示例、配置)移动到单独的参考资料文件中。
模式 1:带参考资料的高级指南
# PDF 处理
## 快速开始
使用 pdfplumber 提取文本:
[代码示例]
## 高级功能
- **表单填写**:完整指南请参阅 [FORMS.md](FORMS.md)
- **API 参考**:所有方法请参阅 [REFERENCE.md](REFERENCE.md)
- **示例**:常见模式请参阅 [EXAMPLES.md](EXAMPLES.md)
Claude 仅在需要时加载 FORMS.md、REFERENCE.md 或 EXAMPLES.md。
模式 2:领域特定组织
对于具有多个领域的技能,按领域组织内容以避免加载不相关的上下文:
bigquery-skill/
├── SKILL.md (概述和导航)
└── reference/
├── finance.md (收入、计费指标)
├── sales.md (机会、销售管道)
├── product.md (API 使用、功能)
└── marketing.md (活动、归因)
当用户询问销售指标时,Claude 只读取 sales.md。
类似地,对于支持多个框架或变体的技能,按变体组织:
cloud-deploy/
├── SKILL.md (工作流程 + 提供商选择)
└── references/
├── aws.md (AWS 部署模式)
├── gcp.md (GCP 部署模式)
└── azure.md (Azure 部署模式)
当用户选择 AWS 时,Claude 只读取 aws.md。
模式 3:条件性细节
显示基本内容,链接到高级内容:
# DOCX 处理
## 创建文档
使用 docx-js 创建新文档。请参阅 [DOCX-JS.md](DOCX-JS.md)。
## 编辑文档
对于简单的编辑,直接修改 XML。
**对于修订跟踪**:请参阅 [REDLINING.md](REDLINING.md)
**对于 OOXML 详细信息**:请参阅 [OOXML.md](OOXML.md)
Claude 仅在用户需要这些功能时读取 REDLINING.md 或 OOXML.md。
重要指南:
技能创建涉及以下步骤:
按顺序执行这些步骤,只有在有明确理由不适用时才跳过。
仅当技能的使用模式已经清晰理解时才跳过此步骤。即使在使用现有技能时,它仍然有价值。
要创建有效的技能,请清楚地了解技能将如何使用的具体示例。这种理解可以来自直接的用户示例,也可以来自经过用户反馈验证的生成示例。
例如,在构建图像编辑器技能时,相关的问题包括:
为了避免让用户不知所措,避免在单个消息中提出太多问题。从最重要的问题开始,并根据需要跟进以获得更好的效果。
当对技能应支持的功能有清晰的认识时,结束此步骤。
为了将具体示例转化为有效的技能,通过以下方式分析每个示例:
示例:当构建一个 pdf-editor 技能来处理诸如“帮我旋转这个 PDF”之类的查询时,分析显示:
scripts/rotate_pdf.py 脚本会很有帮助示例:当设计一个 frontend-webapp-builder 技能来处理诸如“为我构建一个待办事项应用”或“构建一个仪表板来跟踪我的步数”之类的查询时,分析显示:
assets/hello-world/ 模板存储在技能中会很有帮助示例:当构建一个 big-query 技能来处理诸如“今天有多少用户登录?”之类的查询时,分析显示:
references/schema.md 文件存储在技能中会很有帮助为了确定技能的内容,分析每个具体示例,创建一个要包含的可重用资源列表:脚本、参考资料和资产。
此时,是时候实际创建技能了。
仅当正在开发的技能已经存在,并且需要迭代或打包时才跳过此步骤。在这种情况下,请继续下一步。
从头开始创建新技能时,始终运行 init_skill.py 脚本。该脚本方便地生成一个新的模板技能目录,自动包含技能所需的一切,使技能创建过程更加高效和可靠。
用法:
scripts/init_skill.py <skill-name> --path <output-directory>
该脚本:
scripts/、references/ 和 assets/初始化后,根据需要自定义或删除生成的 SKILL.md 和示例文件。
编辑(新生成的或现有的)技能时,请记住,技能是为另一个 Claude 实例使用而创建的。包含对 Claude 有益且非显而易见的信息。考虑哪些流程知识、领域特定细节或可重用资产将帮助另一个 Claude 实例更有效地执行这些任务。
根据技能的需求,参考这些有用的指南:
这些文件包含有效技能设计的既定最佳实践。
复杂任务的专业提示:
开始实施时,从上面识别的可重用资源开始:scripts/、references/ 和 assets/ 文件。请注意,此步骤可能需要用户输入。例如,在实现 brand-guidelines 技能时,用户可能需要提供品牌资产或模板存储在 assets/ 中,或提供文档存储在 references/ 中。
添加的脚本必须通过实际运行来测试,以确保没有错误,并且输出符合预期。如果有很多类似的脚本,只需要测试一个代表性样本,以确保它们都能正常工作,同时平衡完成时间。
技能不需要的任何示例文件和目录都应删除。初始化脚本在 scripts/、references/ 和 assets/ 中创建示例文件以演示结构,但大多数技能不需要所有这些文件。
写作指南: 始终使用祈使句/不定式形式。
使用 name 和 description 编写 YAML 前置元数据:
name:技能名称description:这是技能的主要触发机制,帮助 Claude 理解何时使用该技能。
docx 技能的描述示例:“全面的文档创建、编辑和分析,支持修订跟踪、评论、格式保留和文本提取。当 Claude 需要使用专业文档 (.docx 文件) 进行以下操作时使用:(1) 创建新文档,(2) 修改或编辑内容,(3) 处理修订跟踪,(4) 添加评论,或任何其他文档任务”不要在 YAML 前置元数据中包含任何其他字段。
编写使用技能及其捆绑资源的说明。
技能开发完成后,必须将其打包成可分发的 .skill 文件,与用户共享。技能遵循 Agent Skills 开放标准,以实现跨 AI 平台的可移植性。
打包过程首先自动验证技能,以确保其满足所有要求:
scripts/package_skill.py <path/to/skill-folder>
可选的输出目录指定:
scripts/package_skill.py <path/to/skill-folder> ./dist
打包脚本将:
验证 技能,自动检查:
打包 技能(如果验证通过),创建一个以技能命名的 .skill 文件(例如,my-skill.skill),该文件包含所有文件并保持正确的目录结构以便分发。.skill 文件是一个带有 .skill 扩展名的 zip 文件。
如果验证失败,脚本将报告错误并退出,不创建包。修复任何验证错误并再次运行打包命令。
测试技能后,用户可能会请求改进。这通常发生在使用技能后不久,用户对技能的表现有新鲜的记忆。
迭代工作流程:
每周安装
5
仓库
GitHub Stars
8
首次出现
2026年2月5日
安全审计
安装于
opencode5
gemini-cli5
claude-code5
replit4
codex4
cursor4
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.
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).
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.)
Every SKILL.md consists of:
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.scripts/)Executable code (Python/Bash/etc.) for tasks that require deterministic reliability or are repeatedly rewritten.
scripts/rotate_pdf.py for PDF rotation tasksreferences/)Documentation and reference material intended to be loaded as needed into context to inform Claude's process and thinking.
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 specificationsassets/)Files not intended to be loaded into context, but rather used within the output Claude produces.
assets/logo.png for brand assets, assets/slides.pptx for PowerPoint templates, assets/frontend-template/ for HTML/React boilerplate, assets/font.ttf for typographyA skill should only contain essential files that directly support its functionality. Do NOT create extraneous documentation or auxiliary files, including:
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.
Skills use a three-level loading system to manage context efficiently:
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
# 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:
# 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:
Skill creation involves these steps:
Follow these steps in order, skipping only if there is a clear reason why they are not applicable.
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:
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.
To turn concrete examples into an effective skill, analyze each example by:
Example: When building a pdf-editor skill to handle queries like "Help me rotate this PDF," the analysis shows:
scripts/rotate_pdf.py script would be helpful to store in the skillExample: 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:
assets/hello-world/ template containing the boilerplate HTML/React project files would be helpful to store in the skillExample: When building a big-query skill to handle queries like "How many users have logged in today?" the analysis shows:
references/schema.md file documenting the table schemas would be helpful to store in the skillTo establish the skill's contents, analyze each concrete example to create a list of the reusable resources to include: scripts, references, and assets.
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:
scripts/init_skill.py <skill-name> --path <output-directory>
The script:
scripts/, references/, and assets/After initialization, customize or remove the generated SKILL.md and example files as needed.
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.
Consult these helpful guides based on your skill's needs:
These files contain established best practices for effective skill design.
Pro tips for complex tasks:
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.
Writing Guidelines: Always use imperative/infinitive form.
Write the YAML frontmatter with name and description:
name: The skill namedescription: This is the primary triggering mechanism for your skill, and helps Claude understand when to use the skill.
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.
Write instructions for using the skill and its bundled resources.
Once development of the skill is complete, it must be packaged into a distributable .skill file that gets shared with the user. Skills follow the Agent Skills open standard for portability across AI platforms.
The packaging process automatically validates the skill first to ensure it meets all requirements:
scripts/package_skill.py <path/to/skill-folder>
Optional output directory specification:
scripts/package_skill.py <path/to/skill-folder> ./dist
The packaging script will:
Validate the skill automatically, checking:
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.
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:
Weekly Installs
5
Repository
GitHub Stars
8
First Seen
Feb 5, 2026
Security Audits
Installed on
opencode5
gemini-cli5
claude-code5
replit4
codex4
cursor4
AI新闻播客制作技能:实时新闻转对话式播客脚本与音频生成
1,200 周安装