web-reader

answerzhao/agent-skills · updated Apr 8, 2026

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$npx skills add https://github.com/answerzhao/agent-skills --skill web-reader
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summary

Web page content extraction with automatic title, HTML, and metadata retrieval.

  • Fetches and parses web pages via the page_reader function, returning structured data including title, HTML content, plain text, and publication time
  • Supports both CLI usage for quick tasks and SDK integration for programmatic access in backend code only
  • Includes caching, rate limiting, parallel processing, and error handling patterns for production applications
  • Handles multiple URLs, content aggregatio
skill.md

Web Reader Skill

This skill guides the implementation of web page reading and content extraction functionality using the z-ai-web-dev-sdk package, enabling applications to fetch and process web page content programmatically.

Skills Path

Skill Location: {project_path}/skills/web-reader

This skill is located at the above path in your project.

Reference Scripts: Example test scripts are available in the {Skill Location}/scripts/ directory for quick testing and reference. See {Skill Location}/scripts/web-reader.ts for a working example.

Overview

Web Reader allows you to build applications that can extract content from web pages, retrieve article metadata, and process HTML content. The API automatically handles content extraction, providing clean, structured data from any web URL.

IMPORTANT: z-ai-web-dev-sdk MUST be used in backend code only. Never use it in client-side code.

Prerequisites

The z-ai-web-dev-sdk package is already installed. Import it as shown in the examples below.

CLI Usage (For Simple Tasks)

For simple web page content extraction, you can use the z-ai CLI instead of writing code. This is ideal for quick content scraping, testing URLs, or simple automation tasks.

Basic Page Reading

# Extract content from a web page
z-ai function --name "page_reader" --args '{"url": "https://example.com"}'

# Using short options
z-ai function -n page_reader -a '{"url": "https://www.example.com/article"}'

Save Page Content

# Save extracted content to JSON file
z-ai function \
  -n page_reader \
  -a '{"url": "https://news.example.com/article"}' \
  -o page_content.json

# Extract and save blog post
z-ai function \
  -n page_reader \
  -a '{"url": "https://blog.example.com/post/123"}' \
  -o blog_post.json

Common Use Cases

# Extract news article
z-ai function \
  -n page_reader \
  -a '{"url": "https://news.site.com/breaking-news"}' \
  -o news.json

# Read documentation page
z-ai function \
  -n page_reader \
  -a '{"url": "https://docs.example.com/getting-started"}' \
  -o docs.json

# Scrape blog content
z-ai function \
  -n page_reader \
  -a '{"url": "https://techblog.com/ai-trends-2024"}' \
  -o blog.json

# Extract research article
z-ai function \
  -n page_reader \
  -a '{"url": "https://research.org/papers/quantum-computing"}' \
  -o research.json

CLI Parameters

  • --name, -n: Required - Function name (use "page_reader")
  • --args, -a: Required - JSON arguments object with:
    • url (string, required): The URL of the web page to read
  • --output, -o <path>: Optional - Output file path (JSON format)

Response Structure

The CLI returns a JSON object containing:

  • title: Page title
  • html: Main content HTML
  • text: Plain text content
  • publish_time: Publication timestamp (if available)
  • url: Original URL
  • metadata: Additional page metadata

Example Response

{
  "title": "Introduction to Machine Learning",
  "html": "<article><h1>Introduction to Machine Learning</h1><p>Machine learning is...</p></article>",
  "text": "Introduction to Machine Learning\n\nMachine learning is...",
  "publish_time": "2024-01-15T10:30:00Z",
  "url": "https://example.com/ml-intro",
  "metadata": {
    "author": "John Doe",
    "description": "A comprehensive guide to ML"
  }
}

Processing Multiple URLs

# Create a simple script to process multiple URLs
for url in \
  "https://site1.com/article1" \
  "https://site2.com/article2" \
  "https://site3.com/article3"
do
  filename=$(echo $url | md5sum | cut -d' ' -f1)
  z-ai function -n page_reader -a "{\"url\": \"$url\"}" -o "${filename}.json"
done

When to Use CLI vs SDK

Use CLI for:

  • Quick content extraction
  • Testing URL accessibility
  • Simple web scraping tasks
  • One-off content retrieval

Use SDK for:

  • Batch URL processing with custom logic
  • Integration with web applications
  • Complex content processing pipelines
  • Production applications with error handling

How It Works

The Web Reader uses the page_reader function to:

  1. Fetch the web page content
  2. Extract main article content and metadata
  3. Parse and clean the HTML
  4. Return structured data including title, content, and publication time

Basic Web Reading Implementation

Simple Page Reading

import ZAI from 'z-ai-web-dev-sdk';

async function readWebPage(url) {
  try {
    const zai = await ZAI.create();

    const result = await zai.functions.invoke('page_reader', {
      url: url
    });

    console.log('Title:', result.data.title);
    console.log('URL:', result.data.url);
    console.log('Published:', result.data.publishedTime);
    console.log('HTML Content:', result.data.html);
    console.log('Tokens Used:', result.data.usage.tokens);

    return result.data;
  } catch (error) {
    console.error('Page reading failed:', error.message);
    throw error;
  }
}

// Usage
const pageData = await readWebPage('https://example.com/article');
console.log('Page title:', pageData.title);

Extract Article Text Only

import ZAI from 'z-ai-web-dev-sdk';

async function extractArticleText(url) {
  const zai = await ZAI.create();

  const result = await zai.functions.invoke('page_reader', {
    url: url
  });

  // Convert HTML to plain text (basic approach)
  const plainText = result.data.html
    .replace(/<[^>]*>/g, ' ')
    .replace(/\s+/g, ' ')
    .trim();

  
how to use web-reader

How to use web-reader on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add web-reader
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/answerzhao/agent-skills --skill web-reader

The skills CLI fetches web-reader from GitHub repository answerzhao/agent-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/web-reader

Reload or restart Cursor to activate web-reader. Access the skill through slash commands (e.g., /web-reader) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.564 reviews
  • Maya Liu· Dec 24, 2024

    web-reader fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Kiara Torres· Dec 12, 2024

    I recommend web-reader for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Valentina Park· Dec 8, 2024

    Useful defaults in web-reader — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Shikha Mishra· Dec 4, 2024

    web-reader reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Valentina Thomas· Dec 4, 2024

    web-reader reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Olivia Ndlovu· Nov 27, 2024

    Registry listing for web-reader matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Yash Thakker· Nov 23, 2024

    I recommend web-reader for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Naina Verma· Nov 23, 2024

    I recommend web-reader for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Soo Sharma· Nov 23, 2024

    Solid pick for teams standardizing on skills: web-reader is focused, and the summary matches what you get after install.

  • Mateo Okafor· Nov 19, 2024

    web-reader has been reliable in day-to-day use. Documentation quality is above average for community skills.

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