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agentifyagentify 分析

Agent Skill

agentify 用于处理浏览器自动化、网页检查和页面信息提取,适合在 OpenClaw 中需要让 Agent 打开页面、读取网页或验证前端流程时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

5,471

周安装

235

GitHub Stars

1

下载量

1,918
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:agentify(agentify 分析)
来源仓库:https://github.com/chartgen-ai/agentify
安装命令:
openclaw skills install agentify
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install agentify

简介

agentify 用于处理浏览器自动化、网页检查和页面信息提取,适合在 OpenClaw 中需要让 Agent 打开页面、读取网页或验证前端流程时使用。

  • 适用于分析、重写和生成设计规范,使AI Agent、网络抓取工具和自动化工具更容易使用网页和网站的场景。
  • 通过 clawhub 安装,命令为 openclaw skills install agentify。
  • 安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。
  • agentify 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
agentify
description
Analyze, rewrite, and generate design specs to make web pages and websites more easily usable by AI agents, web scrapers, and automation tools. Use when (1) evaluating how agent-friendly, accessible (a11y), or machine-readable a web page or HTML/JSX/Vue/Svelte code is, (2) rewriting web templates to add semantic markup, ARIA, structured data (schema.org / JSON-LD), and stable selectors (data-testid) for tools like Playwright, Puppeteer, Cypress, or Selenium, (3) generating agent-friendly design specification documents for development teams covering SEO, accessibility, and GEO (Generative Engine Optimization). Triggers on phrases like "agent-friendly", "make this page work with agents", "analyze for automation", "agentify", "improve SEO", "add structured data", "add data-testid", "web scraping friendly", "machine-readable", "a11y audit", "crawler-friendly".

Agentify

Make web pages and websites more easily navigable, parseable, and operable by AI agents, web scrapers, and automation tools.

Core Capabilities

1. Analyze

Evaluate web pages or code for agent-friendliness. Produce a scored report (0-100) with actionable improvements.

When to use: The user wants to audit a page, URL, or codebase for agent accessibility.

Workflow:

  1. Acquire the content:

- URL → fetch and retrieve HTML - File path → read the file - Glob pattern → find matching files, analyze each - IDE selection → analyze selected code

  1. Read the scoring reference: references/scoring.md
  2. Read the full checklist: references/checklist.md
  3. Evaluate across 9 categories (100 points total):
#CategoryPtsFocus
1Semantic HTML15Heading hierarchy, landmarks, semantic tags vs div soup
2ARIA & Accessibility15Roles, labels, live regions, keyboard attributes
3Structured Data15JSON-LD / schema.org presence, completeness
4Form Readability10Label association, autocomplete, fieldset grouping
5Navigation Clarity10Consistent nav, breadcrumbs, skip links, sitemap
6Automation Attributes10data-testid coverage, data-* for key elements
7CSS Selector Stability5Meaningful class names vs generated hashes
8API Discoverability10Canonical URLs, link relations, OpenAPI
9Meta & Machine Signals10robots meta, description, OG tags, sitemap
  1. Output report in this format:

- Score: X/100 (Grade A-F) - Per-category score breakdown table - Top 5 priority improvements with before/after code - Detailed findings per category - Quick wins section (changes under 5 minutes, 5+ point gain)

2. Rewrite

Transform web templates to be agent-friendly while preserving all existing functionality.

When to use: The user wants to improve existing code for agent consumption.

Workflow:

  1. Detect framework from file extension (.html, .jsx, .tsx, .vue, .svelte)
  2. Read the patterns reference: references/patterns.md
  3. Read framework-specific guidance: references/frameworks.md
  4. Read and understand the entire file before modifying
  5. Apply transformations in order:

- Replace non-semantic elements with semantic equivalents (only when intent is unambiguous) - Add ARIA attributes to interactive elements - Add data-testid to buttons, links, inputs, content containers (kebab-case naming) - Improve form labels, autocomplete, fieldset grouping - Insert JSON-LD structured data where content type is identifiable - Add meta tags for full HTML pages - Add skip links and nav labels - Fix heading hierarchy

Safety rules (non-negotiable):

  • Never remove existing code, event handlers, or component logic
  • Never change class names, IDs, or visual appearance
  • Never break framework-specific syntax
  • Only add attributes, never replace unless strictly better
  • Match existing formatting style
  1. After modification, summarize: number of changes per category, changes considered but skipped, and follow-up suggestions needing human judgment

3. Design Spec

Generate a comprehensive agent-friendly design specification document for development teams.

When to use: The user wants to establish standards for agent-friendly web development.

Workflow:

  1. Parse arguments for project name and focus area (e-commerce, dashboard, docs, SaaS, marketing)
  2. Scan the project if in a code directory:

- Detect framework (package.json, config files) - Detect test framework - Grep for existing data-testid, aria-*, schema.org patterns - Read 2-3 representative components to understand code style

  1. Read the spec template: references/spec-template.md
  2. Read the example spec: references/spec-example.md
  3. Generate a markdown spec to agent-friendly-spec.md covering:

- Executive summary - Semantic HTML guidelines - ARIA & accessibility patterns - Naming conventions (data-testid, CSS classes, components) - Structured data (JSON-LD) per page type - Form design patterns - Navigation patterns - API & discoverability - Meta tags & machine signals - Component-level checklists - Testing for agent-friendliness - Migration guide (quick wins → medium → large effort)

Each section must include: priority level (P0/P1/P2), code examples for the detected framework, anti-patterns, and verification methods.

Shared Knowledge Base

For the canonical reference on all agent-friendly web patterns (semantic HTML, ARIA, structured data, data attributes, forms, navigation, APIs, meta tags, CSS stability, interaction patterns), read: references/knowledge-base.md

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

77.7%
按下载量换算1,490

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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