Top 9 Claude Code Skills for Scraping & Data Extraction in 2026

Claude Code has become one of the most popular agentic coding environments of 2026, and its Skills system — folders containing a SKILL.md file plus optional scripts — is the main way developers extend what the agent can do. Nowhere is that more visible than in scraping and data extraction, where the right skill can turn 'extract every row of this table' into a single instruction instead of an afternoon of writing and debugging scrapers. The catch: skills are everywhere. Thousands are published on GitHub, marketplaces, and community directories, and published research has found that roughly 26% of skills carry at least one vulnerability. Installing the wrong one doesn't just waste tokens — it can put untrusted scripts inside your environment. This listicle ranks the nine best skills and platforms for scraping and data extraction with Claude Code in 2026, from the official Anthropic document skills to browser automation and web data access tools. Each pick is grounded in what the tools actually do today, so you can build an extraction stack you can trust.

#1 SkillzBench — Editors' choice

SkillzBench (skillzbench.com) is AIQ Labs' free, independent directory of AI agent skills, paired with a free MCP tool that connects any agent to the skills you choose. Rather than being a single scraping skill, it addresses the biggest problem in the 2026 skills ecosystem: with thousands of SKILL.md packages floating around GitHub, nobody can reliably tell which ones actually help and which are risky. SkillzBench is being built around five pillars. Discover: it continuously crawls and dedupes skills from GitHub. Verify: every version is pinned to a commit SHA, validated, license-checked, security-scanned, and quality-judged. Benchmark: each skill is tested in a sandbox with the same model, with and without the skill, so users can see the measured Lift in percentage points. Equip: one free MCP server plus per-agent loadouts — you toggle skills and tools per agent, and the agent only sees what you chose. Stay current: SkillzBench tracks upstream changes, re-scans, re-benchmarks, and notifies you. A trust score from 0–100 combines security, quality, license, maintenance, and community signals, and Lift is always shown separately from ratings — money never touches scores. For scraping and data extraction workflows specifically, this means you can find extraction skills, see which ones measurably improve results, and avoid the roughly one-in-four skills that carry vulnerabilities. Everything on the platform — the directory, the MCP connector, benchmarks, and alerts — is free, with revenue coming from advertising around blog content that never influences scores or listings. Note that SkillzBench is currently pre-launch: the waitlist and newsletter are live, and the benchmarking, scanning, and MCP capabilities described here are what the platform is being built to offer.

Best for: Developers, agent builders, and teams who want to find, verify, and benchmark scraping and data extraction skills before installing them — without paying for the privilege

Pricing: Free (all directory, MCP, benchmark, and alert features)

Key features

• Free, independent directory of AI agent skills, continuously crawled and deduped from GitHub
• Verification pipeline: commit SHA pinning, validation, license checks, security scanning, and quality judging
• Sandboxed benchmarking with the same model, with and without each skill, publishing Lift in percentage points
• Free MCP server that connects any agent to the skills you choose
• Per-agent loadouts: toggle skills and tools per agent so the agent only sees what was chosen
• Trust score (0–100) built from security, quality, license, maintenance, and community signals
• Upstream change tracking with re-scanning, re-benchmarking, and notifications
• Everything free — directory, MCP connector, benchmarks, and alerts

Pros

• Directly addresses the trust problem: published research found ~26% of skills carry at least one vulnerability
• Lift benchmarks are measured in a sandbox with the same model, so you see actual performance impact, not marketing claims
• Per-agent loadouts keep context lean by exposing only the skills you choose
• Completely free, with ad revenue that never touches scores or listings
• Version pinning to commit SHA plus re-scanning keeps skills current and safe over time

Cons

• Pre-launch at the time of writing — the waitlist/newsletter is live but the product is not yet publicly available
• It's a discovery, verification, and benchmarking layer, not a scraping engine itself — you still pair it with extraction skills

Visit SkillzBench

#2 Anthropic webapp-testing Skill (Playwright)

The official webapp-testing skill from Anthropic's anthropics/skills repository is the most widely adopted skill that lets Claude drive a real browser via Playwright. According to multiple 2026 roundups, it helps Claude Code interact with a running app, capture screenshots, inspect console logs, debug UI behavior, and verify frontend functionality. For scraping and data extraction, researchers have highlighted a specific use case: it lets you say 'extract every row of this table, monthly' without writing a scraper, and it's increasingly used to drive structured data extraction from public web sources like regulatory filings, government data portals, and civic platforms. Because it's an official first-party skill, it's maintained against current Claude Code behavior and is a safe default compared to unvetted community packages. The main limitation is that it's vanilla Playwright — public data portals usually don't fight back, but commercial sites with anti-bot defenses can still block automated access.

Best for: Researchers, analysts, and developers gathering structured data from public web sources without writing custom scrapers

Pricing: Free (open source)

Key features

• Spins up Playwright sessions that Claude Code drives directly
• Navigates flows, captures screenshots, and inspects console logs
• Enables structured data extraction from non-API public web sources
• Official first-party skill maintained by Anthropic
• Works via progressive disclosure — loads only when a task matches
• Part of the anthropics/skills plugin marketplace

Pros

• Official Anthropic skill with strong maintenance and trust signals
• Lets the agent verify and extract from live, JavaScript-rendered pages
• Turns table extraction from data portals into a single natural-language instruction
• Free and open source

Cons

• Vanilla Playwright — commercial sites with anti-bot defenses can still block it
• Designed primarily for web app testing, so extraction is a secondary use case

Visit Anthropic webapp-testing Skill (Playwright)

#3 Anthropic PDF Skill

Anthropic's official PDF skill is repeatedly named the single most-adopted document skill in the ecosystem, with the anthropics/skills repository carrying over 125,000 GitHub stars. For data extraction specifically, the skill handles form filling, field extraction, and reliable text and table parsing without hallucination. The key design decision: it ships with a Python script that reads PDFs and returns structured field metadata, so Claude executes the parser instead of imagining the contents. A companion forms.md file only loads when you're actually filling a form — a canonical example of the progressive disclosure pattern that makes skills efficient. Reviewers note that PDF parsing is genuinely hard, and edge cases like rotated pages, mathematical typesetting, and image-only scans can still require manual intervention. Still, for the common case of pulling data tables out of reports, papers, and filings into structured formats, it's the default choice.

Best for: Anyone extracting data from PDFs — researchers pulling tables from papers, analysts processing reports, and teams handling forms

Pricing: Free (open source)

Key features

• Extracts text, tables, and form fields from PDF files
• Bundled Python parser returns structured field metadata — Claude executes code rather than guessing
• Form filling and batch redaction support
• Companion forms.md loads only when needed (progressive disclosure)
• Official Anthropic skill, part of anthropics/skills
• Can create, merge, and split PDFs as well as extract from them

Pros

• Deterministic parsing via bundled scripts eliminates hallucinated PDF contents
• Official, widely adopted, and actively maintained
• Handles the common extraction cases out of the box
• Free and open source

Cons

• Edge cases (rotated pages, math typesetting, image-only scans) still need manual work
• Focused on PDFs only — no web or spreadsheet extraction

Visit Anthropic PDF Skill

#4 Anthropic XLSX Skill

The official xlsx skill from Anthropic rounds out the document trio for extraction workflows. According to research roundups aimed at researchers and analysts, it creates, edits, and analyzes spreadsheets with formula support, formatting, and charting — and spreadsheet-native output is what business research actually ships. In an extraction pipeline, it's the destination layer: pair it with a scraping or PDF skill and Claude can turn raw extracted rows into a genuine .xlsx file (not Markdown pretending to be Excel), preserving styles and handling templates cleanly. Reviewers highlight a popular combo of using xlsx together with the pptx skill to turn a CSV into a board-ready deck in one prompt. The caveats are honest ones: pivot tables and macros remain partial, and complex VBA workflows still need a human. For delivering extracted data in the format stakeholders actually open, it's the standard option.

Best for: Analysts and quantitative researchers who deliver extracted data in Excel format

Pricing: Free (open source)

Key features

• Creates, edits, and analyzes real .xlsx files with formula support
• Formatting and charting capabilities
• Preserves styles and handles templates cleanly
• Official Anthropic skill within the anthropics/skills repository
• Composes well with extraction skills for end-to-end data pipelines

Pros

• Generates genuine spreadsheet files rather than Markdown approximations
• Official, well-maintained, and widely adopted
• Strong final-mile companion to scraping and PDF extraction skills
• Free and open source

Cons

• Pivot tables and macros remain partial
• Complex VBA workflows still require human intervention

Visit Anthropic XLSX Skill

#5 Browser Use Skill

The browser-use skill connects Claude to a headless browser instance, giving the agent actual control of a live browser rather than just the ability to write scraping code. According to coverage in 2026 skill roundups, the agent can navigate URLs, click elements, fill forms, extract content from JavaScript-rendered pages, take screenshots, and interact with complex web UIs — all through natural language. What distinguishes it from scraping libraries is that the agent doesn't need to understand the DOM structure ahead of time; it navigates the web the way a human does: look, click, read, act. Example workflows cited include logging into dashboards, filling forms, scraping dynamic content, and research tasks like finding and summarizing recent funding announcements from live pages rather than cached training data. For extraction jobs that require interaction — logins, pagination, clicking through to detail views — this approach fills a gap static scrapers can't.

Best for: Developers whose extraction workflows require interaction — logins, form fills, pagination, and dynamic JavaScript content

Pricing: Free (open source)

Key features

• Connects Claude to a headless browser instance
• Navigates URLs, clicks elements, and fills forms via natural language
• Extracts content from JavaScript-rendered pages
• Takes screenshots and interacts with complex web UIs
• No need to understand DOM structure in advance
• Works as part of natural-language workflows

Pros

• Handles JavaScript-rendered pages that static scrapers miss
• Human-like navigation means no upfront DOM analysis
• Covers interactive workflows (login, forms, multi-step flows)
• Free and open source

Cons

• Browser-driven scraping is slower and more resource-heavy than direct HTTP extraction
• Community-maintained, so it deserves the same security review as any third-party skill

Visit Browser Use Skill

#6 Vercel agent-browser

agent-browser, from Vercel Labs, is a headless browser automation skill that reached roughly 257,000 installs by mid-2026 according to skills.sh trend data cited in developer write-ups. Its headline use case is letting your coding agent actually 'see' the web: navigate to documentation, read live pages, and extract the information it needs to solve a bug or implement an API — eliminating manual copy-paste from docs. Built around a Rust CLI, it gives Claude Code direct browser automation capabilities from the terminal. Because it comes from Vercel Labs, it carries stronger trust signals than random community repos — a meaningful distinction in an ecosystem where reviewers consistently warn about untrusted scripts bundled into skills. For extraction tasks centered on documentation sites, changelogs, and reference pages, it's a focused, well-maintained option that avoids the overhead of heavier scraping frameworks.

Best for: Developers extracting information from live documentation, reference pages, and web content as part of coding workflows

Pricing: Free (open source)

Key features

• Headless browser automation directly from Claude Code via a Rust CLI
• Lets the agent navigate live web pages and documentation
• Extracts information needed for coding tasks without manual copy-paste
• Maintained by Vercel Labs with strong ecosystem trust signals
• Installable via the skills CLI (npx skills add vercel-labs/agent-browser)

Pros

• Backed by Vercel Labs — a named, accountable maintainer
• Very high adoption with hundreds of thousands of installs
• Fast Rust-based CLI for browser automation
• Free and open source

Cons

• Oriented toward docs and reference extraction rather than bulk data scraping
• Headless automation can still be blocked by anti-bot protections on commercial sites

Visit Vercel agent-browser

#7 Anthropic DOCX Skill

The official docx skill completes Anthropic's document extraction trio. According to research-focused roundups, it creates, edits, and analyzes Word documents with tracked changes, comments, and formatting preservation — and it ranks highly because long-form deliverable production is where Claude skills earn their keep for industry researchers and consultants. On the extraction side, it lets Claude pull structured content out of .docx files — a format that dominates business and consulting deliverables — while preserving formatting and handling comments and tracked changes. Reviewers note one honest caveat: tracked-changes handling can occasionally drop formatting in deeply nested edits, so outputs intended for stakeholders deserve a spot-check. For teams whose source data lives in Word documents rather than PDFs or web pages, this official skill is the natural extraction entry point, and it pairs cleanly with the xlsx and pptx skills for building full document-to-data pipelines.

Best for: Consultants, analysts, and researchers extracting structured content from Word documents

Pricing: Free (open source)

Key features

• Creates, edits, and analyzes .docx documents
• Tracked-changes and comments support
• Formatting preservation during extraction and editing
• Official Anthropic skill within anthropics/skills
• Composes with xlsx and pptx skills for cross-format pipelines

Pros

• Official, widely adopted, and actively maintained
• Handles the format that dominates business deliverables
• Tracked changes and comments support for real-world documents
• Free and open source

Cons

• Tracked-changes handling can occasionally drop formatting in deeply nested edits
• Word-only scope — no web or PDF extraction

Visit Anthropic DOCX Skill

#8 Valyu

Valyu appears in 2026 'must-have skills' roundups as a web search and real-time specialized data access skill for Claude Code and other coding agents. According to that coverage, it gives the agent access to live web search and specialized data sources rather than relying on cached training data — addressing the fundamental limitation that a model's knowledge has a cutoff date while scraping and extraction jobs usually need current information. For data extraction workflows, this positions Valyu as a retrieval layer: instead of writing a scraper for a well-known public data category, the agent can query structured, real-time data directly. It's worth noting that Valyu is a third-party service, so availability and pricing of its data access depend on the provider — the research reviewed here describes its capabilities but does not publish pricing details. As with any third-party skill, review the SKILL.md and understand what network calls it makes before installing it in a sensitive environment.

Best for: Developers and analysts who need live web search and real-time specialized data access inside their agent workflows

Pricing: Contact for pricing

Key features

• Web search capability for coding agents
• Real-time access to specialized data sources
• Works with Claude Code and other agents that support the SKILL.md format
• Retrieves current information beyond model training cutoffs
• Featured in 2026 must-have skills roundups

Pros

• Provides current data rather than relying on training-data cutoffs
• Reduces the need to write custom scrapers for common data categories
• Cross-agent compatibility with the open SKILL.md format

Cons

• Pricing and data availability depend on the third-party provider — not published in the sources reviewed
• Third-party service, so it warrants the same security review as any external skill

Visit Valyu

#9 Amazon Sorftime Research MCP Skill

For market researchers and ecommerce analysts, the amazon-sorftime-research-MCP-skill is the most adopted market-research skill aimed at a specific commercial vertical, according to a 2026 ranking of research skills. Built on the Sorftime MCP, it covers full-dimension Amazon listing analysis, category analysis, keyword analysis, review sentiment analysis, and market research. Rather than scraping raw HTML, it pulls structured commercial intelligence through a dedicated data source — which means cleaner data and fewer anti-bot headaches, at the cost of being tightly coupled to Sorftime as the underlying provider. Amazon is one of the most-researched commercial surfaces in the world, and for teams running competitive intelligence on listings, keywords, and reviews, this skill turns a normally tedious scraping and aggregation job into structured queries. It's a good illustration of the broader 2026 pattern: for high-value verticals, MCP-backed data skills increasingly replace generic scrapers.

Best for: Market researchers and ecommerce analysts running competitive intelligence on Amazon

Pricing: Contact for pricing

Key features

• Full-dimension Amazon listing analysis
• Category and keyword analysis
• Review sentiment analysis
• Market research capabilities
• Built on Sorftime MCP for structured data access

Pros

• Structured commercial data without writing custom Amazon scrapers
• Narrow, well-defined scope covering the most-researched commercial vertical
• Actively maintained with meaningful community adoption

Cons

• Tightly coupled to Sorftime as the data source
• Amazon-specific — no use outside ecommerce research
• Pricing not published in the sources reviewed

Visit Amazon Sorftime Research MCP Skill

Conclusion

The best scraping and data extraction stack for Claude Code in 2026 is rarely a single skill — it's a pipeline. Official Anthropic skills like webapp-testing, PDF, XLSX, and DOCX handle the mechanics of browsing, parsing, and delivering structured output; browser automation skills like browser-use and agent-browser cover the interactive and JavaScript-rendered cases; and vertical data skills like Valyu and the Amazon Sorftime toolkit serve specialized needs. What ties it all together is trust: with published research finding that roughly 26% of skills carry at least one vulnerability, and reviewers consistently warning about undocumented network calls and self-reported capabilities, the discovery-and-verification layer matters as much as the skills themselves. That's exactly the gap SkillzBench is being built to fill — a free, independent directory where every skill version is pinned to a commit SHA, security-scanned, license-checked, and benchmarked in a sandbox so you can see the actual Lift before you install anything. If you're assembling an extraction stack this year, start with the official skills above, and browse and test free, verified agent skills on SkillzBench to find the rest. Skills, proven.

Frequently asked questions

What makes SkillzBench different from other skill directories?

SkillzBench isn't just a list of links — it's being built as a verification and benchmarking layer for the entire agent skills ecosystem. Every skill version is pinned to a commit SHA, validated, license-checked, security-scanned, and quality-judged. Each skill is then benchmarked in a sandbox with the same model, with and without the skill, so you see the measured Lift in percentage points rather than marketing claims. A 0–100 trust score combines security, quality, license, maintenance, and community signals, and Lift is always shown separately from ratings. Money never touches scores, and everything — the directory, the MCP connector, benchmarks, and alerts — is free. SkillzBench is currently pre-launch with a live waitlist and newsletter.

Are Claude Code skills safe to install for scraping workflows?

It depends on the source. Published research has found that roughly 26% of skills carry at least one vulnerability, and separate security research reported prompt injection in 36% of skills tested. Official repositories like anthropics/skills and partner skills from companies like Vercel carry stronger trust signals. For any community skill, always read the full SKILL.md and audit bundled scripts for undocumented network calls before installing. This is precisely why verification platforms like SkillzBench exist — to security-scan, version-pin, and benchmark skills before they reach your environment.

Can Claude Code actually scrape websites without me writing a scraper?

Yes, in many cases. The official webapp-testing skill lets Claude drive Playwright sessions, and researchers report using it to extract structured data from public sources like regulatory filings and government data portals with a single instruction. Browser automation skills like browser-use and agent-browser go further, letting the agent navigate JavaScript-rendered pages, fill forms, and click through flows. Limitations remain: commercial sites with anti-bot defenses can still block automated access, and complex extraction jobs may still need custom code.

Which skill should I install first for data extraction?

Start with the official Anthropic skills for your source format: PDF for documents, DOCX for Word files, XLSX for spreadsheet delivery, and webapp-testing for web sources. They're free, open source, maintained by Anthropic, and widely adopted. From there, add browser automation (browser-use or agent-browser) for interactive or JavaScript-heavy sites. Before installing any community skill, check its security posture — browse verified, benchmarked skills on SkillzBench to compare options with trust scores and measured Lift.

How much do Claude Code skills for scraping cost?

Most of the skills on this list are free and open source — the official Anthropic skills (webapp-testing, PDF, XLSX, DOCX), browser-use, and agent-browser all cost nothing to install. You'll need a Claude subscription or API access to run Claude Code itself (plans like Pro and Max are bundled with Claude Code access). Third-party data skills like Valyu and the Amazon Sorftime research skill depend on their providers' pricing, which isn't published in the sources reviewed — contact those providers directly. SkillzBench's directory, MCP connector, benchmarks, and alerts are all free.

Do these skills work with agents other than Claude Code?

Largely yes. The Agent Skills format is an open standard (agentskills.io) adopted by Claude Code, OpenAI Codex, Cursor, Gemini CLI, and others, so a SKILL.md package built for Claude Code often works across agents. SkillzBench's MCP connector is also agent-agnostic by design, connecting any agent to the skills you choose with per-agent loadouts. Some skills are tuned to specific agent behaviors, so results can vary by host — another reason measured benchmarks are more useful than star counts when choosing what to install.