'scraping' 검색 결과

Extract a YouTube video’s full transcript and metadata, meaning details such as its title, channel, and like count, through the BrowserAct API. Use the results as source material for summaries, content research, or knowledge bases.

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• Collecting transcripts as source material for video summaries
• Gathering video text for content research
• Adding video transcripts to an internal knowledge base

Search YouTube by keyword and collect linked video and comment datasets through the BrowserAct API. Gather titles, views, comment text, likes, and reply counts to support audience feedback research and topic monitoring.

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• Gathering viewer feedback for a specific topic
• Researching audience discussions around competitor videos
• Collecting comments about trending search terms

Collect comments from a specific Instagram post, including text, usernames, timestamps, like counts, and reply counts. Follow successive result pages and combine the available comments into a list for reviewing the discussion.

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• Collecting comments on a specific post
• Reviewing commenter names and posting times
• Checking comment likes and reply counts

Collect product listings from Etsy category and subcategory pages, including prices, ratings, shop names, images, and advertising or shipping labels. Follow pagination to gather products for competitor comparisons, category research, or potential supplier discovery.

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• Compare competing products in an Etsy category
• Research seasonal product listings
• Find potential suppliers by category

Extract product names, prices, shipping details, and seller ratings from eBay search or category pages. Collect listings across multiple pages and regional eBay sites to prepare data for price comparisons and listing research.

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• Comparing prices for products listed on eBay
• Researching competing sellers and their listings
• Collecting listings across multiple category pages

Collect product listings from Walmart category pages, including prices, ratings, availability, and seller details. Use filtered category URLs and browse multiple pages to gather structured data for product comparisons and category research.

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• Collecting products from a filtered category
• Comparing prices and ratings within a category
• Checking availability and seller information

Gather Product Hunt launches from daily, weekly, monthly, or yearly leaderboards. Collect rankings, descriptions, votes, and product links, with optional maker profiles and visible website email addresses for product discovery and competitor research.

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• Finding new products for a selected period
• Collecting rankings and votes for competitor research
• Researching makers and their profile links

Collect product names, prices, images, ratings, and links from e-commerce listings or keyword searches. Apply filters such as price range and brand, and gather structured product records across multiple pages.

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• Compare products within a price range
• Collect products from a category
• Find products by brand and rating

Collect Amazon product reviews by supplying an ASIN, Amazon's product identifier. BrowserAct returns ratings, review text, publication dates, reviewer details, and verified purchase status without an Amazon login, providing data for feedback research and competitor comparisons.

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• Gathering reviews of competing products
• Collecting feedback to identify product improvements
• Preparing comparisons by verified purchase status

Collect customer reviews from e-commerce product and review pages, including review text, ratings, dates, verified purchase status, and helpful votes. Gather multiple pages of feedback to prepare data for customer opinion research and sentiment analysis.

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• Gathering customer feedback for product research
• Preparing review text for sentiment analysis
• Collecting recent or helpful Amazon reviews

Extract wholesale product details from 1688.com, including quantity-based prices, product variants with dimensions and weight, seller information, shop scores, promotions, and review summaries. Organize these details to compare sourcing options and supplier metrics.

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• Compare wholesale prices by order quantity
• Check dimensions and weight for product variants
• Compare supplier scores and repeat purchase rates

Find and run over 2,000 AI models and API tools through one MCP connection, a shared interface for agents. Inspect inputs and pricing before generating media, searching the web, or retrieving structured and social data.

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• Finding and running image or video generation models
• Retrieving social media posts
• Searching the web and extracting page content

Automate browser tasks such as clicking, typing, navigation, data extraction, testing, and screenshots. It controls Chrome through CDP, a browser control protocol, and supports work requiring logged-in sessions or pages rendered with JavaScript.

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• Automating repeated clicks and form entry
• Collecting information from JavaScript-rendered pages
• Testing website interactions and taking screenshots

Use DeepAPI to search the web, collect website and social platform data, and produce sourced research. It also routes tasks to services for public website actions, email, image generation, and persistent agent memory.

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• Collecting information from websites and social platforms
• Researching a question with multiple cited sources
• Navigating and interacting with public websites

Retrieve HTML or JSON from URLs through Browserbase without starting a browser session. Inspect HTTP status codes and response headers, control redirects, and enable proxies for static page retrieval and simple content collection.

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• Retrieve HTML or JSON from static pages
• Inspect HTTP status codes and response headers
• Check redirect destinations

Use when the user asks to "codify how our founder sounds", "build a founder voice dossier", or "set our content pillars"; runs an 80%-extraction interview over the user's OWN posts, emails, and decks (never competitor scraping, never an invented persona) and produces the versioned voice record — a per-platform register map (incl. 小红书/微信公众号), banned phrases, per-context disclosure lines (the ECHO C2 upstream), a few-shot bank built exclusively from own posts, and 3-5 content pillars with Estimated %-allocations — submitted via memory/events/channels.ndjson for channel-registry to store as voice-dossier.md, the record every Craft-phase skill reads first. Not for the brand-level voice canon — use brand-language-codifier; not for audience/persona research — use audience-mapper. 声音档案/品牌语气/创始人语气/内容支柱/披露声明

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Production-ready patterns for Apify SDK and apify-client in TypeScript. Use when building Actors with Crawlee, managing datasets/KV stores, or implementing robust client wrappers with retry and validation. Trigger with "apify SDK patterns", "apify best practices", "apify client wrapper", "crawlee patterns", "idiomatic apify".

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Upgrade Apify SDK, apify-client, and Crawlee versions safely. Use when migrating between SDK versions, handling breaking changes, or updating from Apify SDK v2 to v3 (Crawlee split). Trigger with "upgrade apify", "apify migration", "apify breaking changes", "update apify SDK", "crawlee upgrade", "apify v2 to v3".

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Collect Apify debug evidence for support tickets and troubleshooting. Use when an Actor run has failed, is stuck, or produced empty output and you need to gather run metadata, logs, dataset samples, and environment info before opening a support ticket. Trigger with "apify debug", "apify support bundle", "collect apify logs", "apify diagnostic", "apify run failed why".

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Production readiness checklist for Apify Actor deployments. Use when deploying an Actor to production, preparing for launch, or validating Actor configuration, scheduling, monitoring, and rollback before going live. Trigger with "apify production", "deploy actor to prod", "apify go-live", "apify launch checklist", "actor production ready".

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Optimize Apify platform costs through memory tuning, compute unit management, and proxy budgeting. Use when analyzing Apify billing, reducing Actor run costs, or implementing usage monitoring and budget alerts. Trigger with "apify cost", "apify billing", "reduce apify costs", "apify pricing", "apify expensive", "apify budget", "compute units".

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Handle Apify API rate limits with proper backoff and request queuing. Use when hitting 429 errors, optimizing API request throughput, or implementing rate-aware client wrappers. Trigger with "apify rate limit", "apify throttling", "apify 429", "apify retry", "apify backoff", "too many requests apify".

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Manage Apify datasets, key-value stores, and request queues programmatically, and orchestrate multi-Actor pipelines. Use when you need to read or write Apify datasets, export scraped data to CSV/JSON/XLSX, store config or binary artifacts in a key-value store, manage a resumable request queue, chain Actors into a scrape → transform → export pipeline, or monitor Actor run status and cost. Trigger with "apify dataset", "apify key-value store", "apify storage", "export apify data", "apify pipeline", "apify request queue".

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Optimize Apify Actor performance: crawl speed, memory usage, concurrency, and proxy rotation. Use when Actors are slow, consuming too much memory, or being blocked by target sites, or when a crawl is too expensive per run. Trigger with "apify performance", "optimize apify actor", "apify slow", "crawlee concurrency", "apify memory tuning", "scraper performance".

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