The 9 Best Agent Skills for Scraping & Data Extraction in 2026

Web scraping and data extraction have quietly become one of the most valuable jobs you can hand to an AI agent in 2026. Traditional scrapers built on fixed selectors still break every time a site changes its layout, while data teams spend roughly 45% of their time on data preparation, according to Anaconda's State of Data Science survey. That's why agent skills — portable SKILL.md instruction packages that teach Claude Code, Codex, Cursor, and Gemini CLI how to navigate websites, fill forms, and pull structured data — have exploded across registries like skills.sh, which now hosts over a million skills. The catch: not all of them are safe or effective. Published research found that roughly a quarter of skills carry at least one vulnerability, and with hundreds of thousands of options, it's hard to know which scraping skills actually lift your agent's performance. This guide ranks the nine best options for scraping and data extraction in 2026 — from browser-automation skills and AI-native scraping APIs to no-code platforms — and shows you how to verify, benchmark, and safely equip any of them with SkillzBench's free tooling.

#1 SkillzBench — Editors' choice

SkillzBench is AIQ Labs' free, independent directory of AI agent skills plus a free MCP tool that connects any agent to the skills you choose — and it takes the top spot because it solves the problem every other entry on this list creates: how do you know a scraping skill is safe and actually works before you wire it into your agent? Agent skills for scraping and data extraction are everywhere in 2026, but published research found that roughly 26% of skills carry at least one vulnerability, and nobody can tell which ones genuinely help and which are risky. SkillzBench is being built to fix exactly that. Its Discover pillar continuously crawls and dedupes skills from GitHub, so scraping skills from every corner of the ecosystem land in one searchable place. Its Verify pillar pins every skill version to a commit SHA, validates the package, checks licenses, runs security scans, and applies quality judgments — critical when a malicious scraping skill could exfiltrate credentials or data. Its Benchmark pillar is the real differentiator: SkillzBench tests every skill in a sandbox with the same model, with and without the skill, and publishes the Lift in percentage points, so you can see how much a browser-automation or extraction skill actually improves your agent rather than trusting marketing claims. The Equip pillar delivers one free MCP server plus per-agent loadouts — you toggle skills and tools per agent, and the agent only sees what you chose. And because upstream skills change constantly, SkillzBench tracks changes, re-scans, re-benchmarks, and notifies you. A 0–100 trust score draws on security, quality, license, maintenance, and community signals, and Lift is always shown separately — money never touches scores. Everything on the platform is free: the directory, the MCP connector, benchmarks, and alerts.

Best for: Anyone equipping agents with scraping or data-extraction skills — developers, agent builders, prompt engineers, and business teams — who want verified, benchmarked, security-scanned skills instead of blind installs

Pricing: Free (all features; revenue comes from blog advertising, never from users)

Key features

• Free, independent directory of AI agent skills, continuously crawled and deduped from GitHub
• Every skill version pinned to a commit SHA with validation, license checks, and security scans
• Sandbox benchmarking that publishes Lift (percentage-point improvement) with and without each skill, using the same model
• Free MCP server plus per-agent loadouts — toggle skills and tools per agent, and the agent only sees what you selected
• 0–100 trust score built from security, quality, license, maintenance, and community signals
• Upstream change tracking with re-scans, re-benchmarks, and notifications
• Lift always reported separately from ratings; money never influences scores or listings
• Everything free — directory, MCP connector, benchmarks, and alerts

Pros

• Independent and free — ad-supported, so money never touches scores or listings
• Security-first: every skill version is pinned, scanned, and license-checked before you trust it
• Published Lift benchmarks show actual performance gains, not popularity
• Works with Claude Code, Codex, Cursor, Gemini CLI, and chat-app agents via one free MCP server

Cons

• Pre-launch — the waitlist/newsletter is live, but the full product is not yet public
• Focuses on evaluating and equipping skills rather than providing scraping infrastructure itself

Visit SkillzBench

#2 Agent Browser (Vercel Labs)

Agent Browser is one of the most-installed skills in the entire agent ecosystem — over 1.1 million installs on the skills.sh leaderboard as of October 2026 — and it's the go-to skill when your agent needs to actually interact with the web rather than just write scraper code. According to its documentation and ecosystem listings, it's a full browser-automation CLI built in Rust, integrating directly with the Chrome DevTools Protocol rather than wrapping Playwright or Puppeteer. That architecture gives agents fast, persistent browser automation with session continuity across commands. The skill supports three browser modes — headless Chromium, real Chrome with profile support, and cloud-hosted remote browsers — and offers more than 15 command categories covering navigation, page inspection, interactions, data extraction, and JavaScript execution. For scraping workflows specifically, that means your agent can open pages, click through pagination, fill forms behind logins, extract content from JavaScript-rendered sites, and take screenshots, all driven by natural language. Cloud session management and parallel subagent execution enable scalable workflows, and built-in Python integration lets agents set variables and execute scripts inside the browser context. Accessibility-tree snapshots provide reliable element targeting, and the skill can even record video of sessions. For data professionals collecting information from web dashboards or automating downloads, it's become an indispensable capability — though as a raw skill, you're trusting the publisher's code without independent verification unless you check it through a service like SkillzBench.

Best for: Developers and agent builders who want their coding agent to navigate, click, log in, and extract data from live, JavaScript-heavy websites

Pricing: Free and open source

Key features

• Rust-based browser-automation CLI with direct Chrome DevTools Protocol integration
• Three browser modes: headless Chromium, real Chrome with profiles, and cloud-hosted remote browsers
• 15+ command categories for navigation, inspection, interaction, data extraction, and JavaScript execution
• Session continuity across commands and cloud session management
• Parallel subagent execution for scalable workflows
• Accessibility-tree snapshots for reliable element targeting
• Screenshot capture and session video recording
• Built-in Python integration for scripts within the browser context

Pros

• Massively adopted — over 1.1M installs on skills.sh, one of the top skills overall
• Maintained by Vercel Labs, a well-known publisher with a strong reputation
• Session continuity makes multi-step scraping and form workflows practical
• Free and open source

Cons

• No built-in benchmark data showing how much it lifts your specific agent's performance
• Requires comfort with CLI-driven workflows; not a no-code option
• You're responsible for handling anti-bot protections and proxies

Visit Agent Browser (Vercel Labs)

#3 Firecrawl

Firecrawl is the unified extraction API for the modern AI stack, and according to its own 2026 materials it's the only tool covering both web and document extraction in a single API with the same output shape. On the web side, /scrape handles JavaScript-heavy sites and returns clean markdown or schema-defined JSON; /crawl recursively pulls entire sites or docs sections with depth and path filters; /search and /agent let you search the web and hydrate results in one call, or hand a natural-language extraction task to an agent that navigates and extracts on its own. The document side handles PDFs, DOCX, XLSX, PPTX, EPUB, and other formats without an external OCR service, powered by two open-source Rust libraries. Firecrawl has become a favorite for agent workflows because it's keyless — every developer gets 1,000 free credits a month with no signup, live across the MCP server, CLI, and API, so you can point Claude Code, Cursor, or any MCP-compatible agent at it in one command. It's also engineered to be token-efficient: the markdown and structured JSON returned are aggressively cleaned of nav, chrome, and boilerplate before hitting your LLM, which the company says cuts input tokens by 30–40% per page — meaningful at RAG or agent scale. Adoption backs the claims: Firecrawl is now one of the top 50 most-starred repositories on GitHub out of over 400 million public repos. The trade-off is that it's API-first, so non-technical teammates need a wrapper, and per third-party reviews it doesn't provide autonomous self-healing when layouts change.

Best for: Developers building AI applications and agent pipelines who need clean, LLM-ready data from both websites and documents

Pricing: Free credits (1,000/month, keyless); paid plans start at $0.001 per page, pay-as-you-go

Key features

• /scrape for single URLs as markdown, JSON, or structured schema output with JavaScript rendering
• /crawl for recursive site extraction with depth and path filters
• /parse for PDFs, DOCX, XLSX, PPTX, EPUB, and more without external OCR
• /search and /agent for web search hydration and natural-language extraction tasks
• /interact and /monitor for dynamic pages with clicks, form fills, logins, and change alerts
• Keyless access: 1,000 free credits monthly, no signup, across MCP server, CLI, and API
• Token-efficient output cleaned of boilerplate, reportedly cutting tokens 30–40% per page
• Top-50 most-starred repository on GitHub

Pros

• One API covers web and document extraction with consistent output
• MCP server makes it trivially easy to connect to Claude Code, Cursor, and other agents
• Token-efficient, LLM-ready output reduces downstream costs
• Generous keyless free tier

Cons

• API-first — non-technical users need a wrapper or developer help
• No autonomous maintenance or self-healing when target sites change layouts
• Credit-based pricing can scale up quickly for high-volume crawling

Visit Firecrawl

#4 Browser Use

Browser Use is the skill that turns a coding agent from a code-generation tool into an end-to-end research analyst and automation operator, and it's repeatedly named among the must-have agent skills of 2026 in guides from Medium, AGNT, and others. According to its documentation, the skill connects an agent like Claude to a headless browser instance, letting it navigate URLs, click elements, fill forms, extract content from JavaScript-rendered pages, take screenshots, and interact with complex web UIs as part of a natural-language workflow. 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. That makes it well suited to scraping tasks where pages require interaction, logins, or dynamic content, and to research workflows like finding recent funding announcements and summarizing amounts and investors directly from the live web rather than cached training data. A Playwright-based variant supports full browser automation for testing deployed apps. The skill works across Claude Code, Cursor, Gemini CLI, Codex CLI, and other SKILL.md-compatible agents via the universal format. For teams whose extraction needs involve dynamic, interactive sites rather than static pages, Browser Use remains one of the most capable free options — though like any community skill, its quality and safety depend on the version you install, which is exactly the problem SkillzBench's verification and benchmarking layer is designed to address.

Best for: Agents that need to scrape interactive, login-gated, or JavaScript-heavy sites and do live-web research

Pricing: Free and open source

Key features

• Connects agents to a headless browser for navigation, clicking, form filling, and screenshots
• Extracts content from JavaScript-rendered pages without predefined DOM structure
• Human-like navigation: look, click, read, act
• Handles logins, dynamic content, and complex web UIs in natural-language workflows
• Playwright-based variant for full browser automation and end-to-end testing
• Works across Claude Code, Cursor, Gemini CLI, Codex CLI, and other SKILL.md agents
• Free and open source

Pros

• Handles interactive and dynamic sites that defeat traditional scrapers
• No need to pre-map DOM structure — the agent navigates like a human
• Broad agent compatibility through the SKILL.md format
• Free and open source

Cons

• Slower than deterministic scrapers since the agent reasons through each page
• No built-in proxy rotation or anti-bot infrastructure
• Community-maintained, so quality varies by version and requires vetting

Visit Browser Use

#5 Kadoa

Kadoa takes a fundamentally different approach to scraping: instead of writing scripts for you, it builds AI agents that continuously maintain and self-heal the extractors — which is why independent 2026 reviews rank it as the best fully autonomous AI scraper. According to its website, when you build a workflow you define what the data is (e.g., 'the product price'), not where it is in the HTML. Kadoa's models view the rendered page like a human user using multimodal analysis (vision plus text), so if a site moves a price from a sidebar to the center column, Kadoa identifies it by context and extracts it anyway. A validation layer compares previous run data with current data, and if the layout shifts, the agents adapt automatically — directly attacking the 'maintenance hell' cycle where scripts break at 2 a.m. after a CSS change. Crucially, Kadoa compiles agent findings into efficient, deterministic code rather than re-prompting a model on every scrape, so production runs are fast and cheap. It scales to millions of pages with intelligent batching and anti-bot bypass, and offers enterprise workflow automation with scheduling, monitoring, and alerting. For teams running ongoing extraction — competitor pricing, alternative data, market monitoring — that zero-maintenance promise is the core value. The trade-off is cost and opacity: paid plans start at $99/month with usage-based credits, and like any hosted platform, you depend on Kadoa's models rather than your own agent stack.

Best for: Enterprises and teams that need production-grade, autonomous scraping at scale with zero script maintenance

Pricing: Free tier available; paid plans start at $99/month with usage-based credits

Key features

• Zero-maintenance AI agents that continuously monitor and self-heal extractors
• Multimodal analysis (vision + text) for semantic, context-based data extraction
• Deterministic execution — compiles agent findings into efficient production code
• Validation layer that detects layout changes and adapts automatically
• Scales to millions of pages with intelligent batching and anti-bot bypass
• Enterprise workflow automation with scheduling, monitoring, and alerting
• Free tier available

Pros

• Genuine self-healing — extractors adapt when target sites change
• Deterministic compiled code keeps production runs fast and cost-efficient
• Strong enterprise readiness: scheduling, monitoring, alerting
• Handles anti-bot protections at scale

Cons

• Paid plans start at $99/month — pricier than open-source alternatives
• Hosted platform dependency rather than running within your own agent stack
• Not a SKILL.md skill, so it doesn't extend coding agents directly

Visit Kadoa

#6 Apify

Apify is the managed data platform of choice when you don't want to build scrapers from scratch, and it has leaned hard into the agent era in 2026. According to its website and 2026 roundups, Apify offers 6,000+ pre-built Actors — reusable scraper programs for popular sites spanning e-commerce, social media, and local listings — so teams can start extracting data without touching selectors or proxies. Beyond the marketplace, Apify supports natural-language AI browser automation for agents, custom Actor development, and a marketplace where developers publish and monetize their own scrapers. The platform handles the operational heavy lifting: proxy management, scheduling, and API integrations, with cloud execution that runs your extractions on a schedule and delivers results via API, webhooks, or exports. Pricing is transparent and tiered: a free plan, then Starter at $39/month, Scale at $199/month, and Business at $999/month, with usage-based consumption on top. For agent builders, Apify's Actors can be invoked from agent workflows, effectively giving your AI agent a library of battle-tested extraction tools it can call on demand — a practical complement to browser-automation skills that handle the interactive parts. The main limitations are that pre-built Actors vary in quality and maintenance across publishers, and heavy usage on higher tiers adds up. Still, for teams that want managed infrastructure plus a huge catalog of ready-made extractors, Apify remains one of the most complete platforms in 2026.

Best for: Developers and analysts automating large-scale data collection across e-commerce, social media, and directory sites

Pricing: Free plan; Starter $39/month, Scale $199/month, Business $999/month (usage-based)

Key features

• 6,000+ pre-built Actors for popular websites and data sources
• Natural-language AI browser automation for agents
• Custom Actor development and a public marketplace
• Proxy management, scheduling, and API integrations
• Cloud-based execution with webhook and export delivery
• Transparent tiered pricing from free to enterprise

Pros

• Huge catalog of ready-made scrapers means fast time to first data
• Managed proxies, scheduling, and infrastructure — no browser farm to run
• Actors integrate into agent workflows for on-demand extraction
• Clear, published pricing tiers

Cons

• Third-party Actor quality and maintenance vary by publisher
• Costs escalate with heavy usage on paid tiers
• Less flexible than writing your own extraction logic for unusual sites

Visit Apify

#7 Browse AI

Browse AI pioneered the visual 'robot training' approach to scraping, and according to independent 2026 reviews it remains the best no-code visual scraper for teams without developers. The concept is simple: you point and click on the elements you want to extract on a live page, and Browse AI generates a robot that repeats the extraction on a schedule in the cloud. The platform ships pre-built templates for common sites — LinkedIn, Amazon, and others — so many common extraction jobs start from a proven recipe rather than a blank canvas. Robots run in the cloud with built-in scheduling and basic monitoring and change detection, so you can watch competitor prices, listings, or lead sources continuously without keeping a machine running. For business users adopting AI at work, this is one of the lowest-friction paths to automated data extraction: no code, no infrastructure, and results delivered to sheets or via API. The honest limitation, which reviewers note, is that Browse AI relies heavily on traditional selectors under the hood — when target sites change their layouts, you often need to retrain the robot manually, and it lacks the autonomous selector generation of AI-native platforms like Kadoa. Pricing is friendly to small teams, with a free tier of limited robots and paid plans starting at $49/month. For non-technical users who need reliable extraction from relatively stable sites and don't mind occasional retraining, it's a strong, approachable choice.

Best for: Small teams and non-technical users who need a simple visual scraper and can tolerate occasional manual retraining

Pricing: Free tier with limited robots; paid plans start at $49/month

Key features

• Point-and-click visual interface for training extraction robots
• Pre-built templates for common sites including LinkedIn and Amazon
• Cloud-based execution with scheduling
• Basic monitoring and change detection
• No-code setup requiring no developer involvement
• Free tier with limited robots

Pros

• Extremely intuitive — train a robot in minutes with no code
• Templates cover many popular extraction targets
• Affordable entry pricing with a free tier
• Cloud scheduling means continuous monitoring without infrastructure

Cons

• Selector-based under the hood — site changes often require manual retraining
• No autonomous selector generation or self-healing
• Limited enterprise readiness compared with AI-native platforms

Visit Browse AI

#8 just-scrape (ScrapeGraphAI)

just-scrape is a purpose-built agent skill from ScrapeGraphAI that deserves a spot on any 2026 scraping list because it's designed specifically for the SKILL.md agent ecosystem. According to its listing on the MCP servers agent-skills library, the skill lets an agent search, scrape, crawl, extract structured data, and monitor web pages via the ScrapeGraph AI CLI. Its trigger description covers the full extraction workflow: searching the web, scraping a webpage, grabbing content from a URL, extracting JSON from a site, crawling documentation or site sections, monitoring a page for changes, inspecting request history, checking ScrapeGraph credits, and validating API setup. That breadth makes it a single install that covers most day-to-day extraction needs for a coding agent — from quick single-page pulls to ongoing monitoring jobs. Because it's tagged for web scraping, data analysis, and research, it slots naturally into agent loadouts alongside browser-automation skills: just-scrape handles the structured extraction and crawling, while a browser skill handles interactive, login-gated pages. It's categorized as a featured skill in the ecosystem's scraping section, reflecting solid community visibility. As with any third-party skill, the usual caveats apply: you're trusting the publisher's CLI and instructions, quality depends on the underlying ScrapeGraphAI service, and you should verify what you install — which is precisely the gap SkillzBench's security scanning, license checks, and Lift benchmarking are being built to close.

Best for: Agent builders who want one skill covering search, scraping, crawling, JSON extraction, and page monitoring inside their coding agent

Pricing: Contact for pricing (ScrapeGraphAI service usage applies)

Key features

• Search, scrape, crawl, and extract structured data via the ScrapeGraph AI CLI
• Extract JSON from sites for structured, downstream-ready output
• Crawl documentation or site sections recursively
• Monitor pages for changes over time
• Inspect request history and check ScrapeGraph credits from within the agent
• Native SKILL.md skill for Claude Code, Codex, Cursor, and compatible agents

Pros

• Purpose-built for the agent skill ecosystem — installs like any SKILL.md package
• Covers the full extraction workflow in a single skill
• Structured JSON output suited to downstream analysis and RAG
• Includes monitoring for change-detection workflows

Cons

• Depends on the underlying ScrapeGraphAI CLI and service
• Pricing not publicly listed in research; usage costs may apply
• Third-party skill — requires independent security vetting before production use

Visit just-scrape (ScrapeGraphAI)

#9 Octoparse

Octoparse rounds out the list as the best hybrid option, blending traditional scraping control with AI assistance — a combination that independent 2026 reviews highlight for power users who want both. According to its website and third-party comparisons, Octoparse offers desktop and cloud-based scraping with a drag-and-drop workflow builder, AI-assisted template generation, and intelligent pagination detection that reduces manual setup for common sites. For complex targets, it doesn't hide the machinery: an advanced workflow editor supports XPath and regex, giving experienced users precise control over extraction logic. On the operations side, Octoparse includes IP rotation, CAPTCHA solving, and proxy support — the anti-bot essentials that DIY scripts usually lack — plus pre-set templates for top websites and scheduling for recurring runs. The AI features are genuinely helpful but, as reviewers note, not autonomous: you still need to configure selectors manually for complex sites, and there's a steeper learning curve than pure no-code tools like Browse AI. Pricing is reasonable, with a free tier and paid plans starting at $75/month. For marketing and pricing analysts who need structured web data but want the option to drop into XPath-level control when a site gets difficult, Octoparse occupies a useful middle ground between visual no-code tools and developer-first APIs — just don't expect it to self-heal when layouts change.

Best for: Power users and analysts who want AI assistance plus manual control via XPath/regex for difficult sites

Pricing: Free tier available; paid plans start at $75/month

Key features

• Desktop and cloud-based scraping options
• Drag-and-drop workflow builder with AI-assisted template generation
• Advanced workflow editor with XPath and regex support
• Intelligent pagination detection
• IP rotation, CAPTCHA solving, and proxy support
• Pre-set templates for top websites and scheduled runs
• Free tier available

Pros

• Hybrid approach: AI help for speed, manual control for precision
• Built-in anti-bot essentials (IP rotation, CAPTCHA solving, proxies)
• Both desktop and cloud execution with scheduling
• Reasonable pricing with a free tier

Cons

• AI features are assistive, not autonomous — no self-healing extractors
• Steeper learning curve than pure no-code alternatives
• Not agent-native; integrating into SKILL.md-based agent workflows requires extra glue

Visit Octoparse

Conclusion

Scraping and data extraction in 2026 is no longer a choice between brittle scripts and expensive enterprise platforms — agent skills and AI-native tools have collapsed that spectrum. If you're equipping a coding agent, skills like Agent Browser, Browser Use, and just-scrape give your agent hands on the live web, while platforms like Firecrawl, Kadoa, Apify, Browse AI, and Octoparse cover managed, autonomous, and no-code needs. But whichever route you take, the same rule applies: verify before you install. With research showing roughly a quarter of published skills carry at least one vulnerability, blindly adding scraping skills to your agent is a real security risk. That's exactly why SkillzBench exists — a free, independent directory that security-scans every skill, pins versions to commit SHAs, and benchmarks each one in a sandbox to publish its actual Lift in percentage points, with a free MCP server to equip only the skills you choose. Skills, proven. Join the SkillzBench waitlist today to get notified at launch, browse the free skills directory, and start building agent loadouts you can actually trust — because the best scraping skill is one that's been verified, benchmarked, and scanned before it ever touches your data.

Frequently asked questions

What makes SkillzBench different from other skill directories?

SkillzBench is independent and free, supported by blog advertising rather than user fees, so money never influences scores or listings. It verifies every skill by pinning versions to commit SHAs, validating packages, checking licenses, and running security scans, then benchmarks each skill in a sandbox with the same model — with and without the skill — and publishes the Lift in percentage points. A 0–100 trust score combines security, quality, license, maintenance, and community signals, with Lift always shown separately. It also provides a free MCP server with per-agent loadouts, and tracks upstream skill changes with re-scans, re-benchmarks, and notifications.

What is an agent skill for scraping?

An agent skill is a folder containing a SKILL.md file — a portable instruction package that teaches an AI agent like Claude Code, Codex, Cursor, or Gemini CLI how to perform a specific task. A scraping skill gives the agent a playbook for navigating websites, filling forms, extracting content from JavaScript-rendered pages, and returning structured data, using progressive disclosure so the instructions load only when the task calls for them.

Are agent skills safe to install?

Not automatically. Published research found that approximately 26% of agent skills carry at least one vulnerability, and other security-focused directories report similar figures, scanning for prompt injection, credential theft, and data exfiltration. Because skills can bundle scripts and instructions that agents execute, a malicious skill is a genuine supply-chain risk. Verify skills before installing — SkillzBench's security scanning, license checks, and version pinning are built for exactly this.

Do I need coding experience to use these scraping tools?

It depends on the tool. Browse AI and Octoparse offer visual, no-code interfaces suitable for non-technical users, while Firecrawl, Agent Browser, Browser Use, and just-scrape are developer-first and assume comfort with APIs, CLIs, or agent configuration. Kadoa sits in between with workflow automation that non-developers can define in plain language.

How much do these scraping skills and tools cost?

The skills themselves — Agent Browser, Browser Use, and just-scrape — are free to install, though just-scrape relies on the ScrapeGraphAI service, whose pricing isn't publicly listed. Platforms vary: Firecrawl offers 1,000 keyless free credits monthly with paid usage from $0.001 per page; Browse AI starts at $49/month; Octoparse at $75/month; Kadoa at $99/month; and Apify from a free plan up to $999/month. SkillzBench is entirely free, funded by blog advertising.

Can these tools handle JavaScript-heavy and bot-protected websites?

Yes, with varying approaches. Agent Browser and Browser Use drive real browser instances, so they handle JavaScript-rendered content naturally. Firecrawl includes JavaScript rendering and anti-bot bypass in its API. Kadoa, Apify, and Octoparse include proxy rotation and CAPTCHA-solving infrastructure. For heavily protected targets, managed platforms with dedicated anti-bot networks generally perform better than raw open-source skills.

How do I choose the right scraping solution for my team?

Match the tool to your constraints: if you have developers and agent workflows, start with skills like Agent Browser or Browser Use plus Firecrawl's API, verified through SkillzBench. If you need zero maintenance at scale, Kadoa's self-healing extractors fit best. If you want ready-made scrapers, Apify's Actor marketplace is the fastest start. If you're non-technical, Browse AI or Octoparse offer the shortest path. Whatever you pick, benchmark and security-scan before production use.