Best web scraping skills, page 13

Optimize Apify platform costs through memory tuning, compute unit management, and proxy budgeting.

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Collect Apify debug evidence for support tickets and troubleshooting.

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Deploy Apify Actors and integrate scraping into external applications.

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Run your first Apify Actor and retrieve results via apify-client.

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Install and configure Apify SDK, CLI, and API client authentication.

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Set up local Apify Actor development with the Apify CLI and Crawlee.

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Optimize Apify Actor performance: crawl speed, memory usage, concurrency, and proxy rotation.

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Production readiness checklist for Apify Actor deployments. An agent skill from jeremylongshore/tons-of-skills-marketplace.

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Handle Apify API rate limits with proper backoff and request queuing.

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Production-grade architecture patterns for Apify-powered applications.

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Production-ready patterns for Apify SDK and apify-client in TypeScript.

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Secure Apify API tokens, configure proxy access, and protect Actor data.

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Upgrade Apify SDK, apify-client, and Crawlee versions safely.

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Implement Apify webhooks for Actor run notifications and event-driven pipelines.

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Analyze and operate the Bright Data Web Scraper API async snapshot lifecycle with terminal-state and delivery controls.

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Design and review a bounded Bright Data worker deployment with separate proxy, Browser API, scraper, snapshot, and delivery responsibilities.

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Gate a Bright Data integration for production with authorization, reliability, cost, data, and rollback evidence.

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Wrap the official Bright Data Python SDK and REST contracts behind a typed, testable client boundary.

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Migrate Bright Data SDK, API, product, or response-header contracts with fixture evidence and a reversible canary.

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Isolate difficult Firecrawl v2 failures by separating caller, authentication, request, queue, rendering, origin, and result-processing evidence.

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Select a Firecrawl v2 architecture for interactive scrape, governed batch, scheduled crawl, search enrichment, or self-hosted processing.

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Build deterministic CI gates for a Firecrawl v2 integration using synthetic fixtures, pinned schemas, secret scanning, and an optional protected smoke test.

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Analyze and resolve current Firecrawl v2 validation, authentication, credit, policy, rate, concurrency, timeout, and server errors.

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Implement current Firecrawl v2 scrape and crawl flows with bounded discovery, pagination, content validation, and durable receipts.

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Combine Firecrawl v2 map, search, batch scrape, parse, and structured JSON extraction into a governed acquisition workflow.

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Measure and reduce Firecrawl credit consumption using explicit limits, endpoint selection, cache policy, format discipline, and spend controls.

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Validate, minimize, classify, deduplicate, retain, and dispose of Firecrawl documents and extracted JSON safely.

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Assemble a minimal, redacted Firecrawl diagnostic package for internal triage or vendor support.

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Deploy a Firecrawl v2 client integration or a reviewed self-hosted stack with secrets, canaries, health evidence, and rollback controls.

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Design and audit Firecrawl team roles, API-key ownership, endpoint and format restrictions, IP restrictions, SSO, and separation of duties.

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Create the smallest current Firecrawl v2 scrape and verify its provenance, origin status, and output without leaking credentials.

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Analyze and mitigate Firecrawl integration incidents involving outage, credits, throttling, policy denial, job failure, webhook loss, or unsafe content.

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Install the current Firecrawl Node or Python SDK, configure Cloud authentication, and verify package provenance and secret injection.

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Audit a Firecrawl integration for legacy v1 calls, unbounded crawls, incomplete pagination, unsafe retries, retention mistakes, and untrusted-content handling.

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Measure Firecrawl throughput under plan, team rate, browser concurrency, queue, timeout, target-policy, and credit constraints.

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Build a deterministic Firecrawl development loop with SDK fakes, recorded synthetic contracts, and an optional trusted-network self-hosted stack.

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Migrate a custom Puppeteer, Playwright, Cheerio, or third-party scraping workload to Firecrawl v2 with parity, policy, cost, and rollback evidence.

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Separate Firecrawl development, staging, and production identities, targets, budgets, policies, telemetry, and data stores.

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Instrument Firecrawl v2 requests, async jobs, queue pressure, credits, origin status, webhooks, output quality, and downstream delivery without logging content.

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Improve Firecrawl latency and throughput through measured scope, formats, cache freshness, async selection, pagination, and concurrency controls.

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Enforce domain authorization, robots and terms review, endpoint and format allowlists, scope, spend, retention, and unsafe-content controls around Firecrawl.

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Run a release gate for a Firecrawl v2 integration covering contracts, scope, identity, spend, retention, reliability, observability, and rollback.

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Implement bounded Firecrawl throttling and retry behavior using current team RPM, browser concurrency, queue status, timeouts, and Retry-After.

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Design a production Firecrawl v2 ingestion system with policy gateway, bounded acquisition, validation, provenance, storage, indexing, observability, and deletion.

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Implement bounded retries, durable async state, pagination, idempotency, reconciliation, circuit breaking, cancellation, and degraded modes for Firecrawl v2.

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Build a typed, testable Firecrawl v2 adapter for Node or Python with current methods, explicit options, errors, pagination, and dependency control.

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Secure Firecrawl identities, targets, request options, webhooks, untrusted content, retention, logs, and self-hosted exposure.

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Upgrade a Firecrawl client from legacy v0/v1 routes and methods to the current v2 SDK and API with contract, parity, and rollback evidence.

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