Openclaw 技能模板:AI 能力标准化框架 - Openclaw Skills
作者:互联网
2026-04-07
什么是 Openclaw 技能模板?
Openclaw 技能模板是开发人员扩展 AI 智能体效用的基础蓝图。它提供了一套结构化方法,用于定义智能体应如何处理特定的文件类型、复杂的工作流或专业工具集。通过采用此模板,用户可以确保其 Openclaw 技能具有模块化、易于被大语言模型(LLM)解释以及在不同开发环境中易于维护的特性。
该框架强调关注点分离,区分了可执行逻辑、上下文引用和静态资产。这使得创建复杂的 Openclaw 技能成为可能,其范围涵盖从简单的 CLI 封装器到用于文档处理和系统自动化的复杂多步决策树。
下载入口:https://github.com/openclaw/skills/tree/main/skills/enchantedmotorcycle/my-new-skill
安装与下载
1. ClawHub CLI
从源直接安装技能的最快方式。
npx clawhub@latest install my-new-skill
2. 手动安装
将技能文件夹复制到以下位置之一
全局模式~/.openclaw/skills/
工作区
/skills/
优先级:工作区 > 本地 > 内置
3. 提示词安装
将此提示词复制到 OpenClaw 即可自动安装。
请帮我使用 Clawhub 安装 my-new-skill。如果尚未安装 Clawhub,请先安装(npm i -g clawhub)。
Openclaw 技能模板 应用场景
- 为团队范围内的 Openclaw 技能开发建立一致的结构。
- 为复杂的多步 AI 任务构建顺序工作流决策树。
- 为特定的文件操作(如 PDF 或 DOCX 处理)创建基于任务的工具集。
- 封装领域特定知识和 API 文档以增强 AI 上下文。
- 为前端或后端开发项目标准化样板生成。
- 选择最能代表技能目的的结构模式(工作流、任务、参考或能力)。
- 配置 SKILL.md 的 frontmatter,包含唯一名称以及智能体何时应触发该技能的详细描述。
- 在 scripts 目录中实现可执行逻辑以执行自动化数据处理。
- 在 references 目录中提供文档,为 AI 智能体提供关于规则和规范的深度上下文。
- 在 assets 目录中存储非上下文模板和样板文件,供智能体在最终输出中使用。
Openclaw 技能模板 配置指南
要开始使用 Openclaw 技能模板进行构建,请遵循以下步骤:
# 进入本地技能仓库
cd openclaw-skills
# 为您的自定义技能创建一个新目录
mkdir -p skills/your-unique-skill
# 使用模板初始化技能
cp templates/SKILL.md skills/your-unique-skill/SKILL.md
Openclaw 技能模板 数据架构与分类体系
模板将数据组织成清晰的分类,以优化智能体与不同文件类型的交互方式:
| 组件 | 位置 | 描述 |
|---|---|---|
| 逻辑 | /scripts |
用于直接操作的可执行 Python 或 Bash 脚本。 |
| 上下文 | /references |
加载到智能体上下文中的 Markdown 文件和文档。 |
| 模板 | /assets |
用于输出生成的文件,如 .pptx 或 .html 样板。 |
name: my-new-skill
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.]
My New Skill
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 (optional)
Create only the resource directories this skill actually needs. Delete this section if no resources are required.
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 Codex for patching or environment adjustments.
references/
Documentation and reference material intended to be loaded into context to inform Codex'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 Codex should reference while working.
assets/
Files not intended to be loaded into context, but rather used within the output Codex 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.
Not every skill requires all three types of resources.
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