Run Apify actors and filter dataset results in code.
npx skills add https://github.com/larsboes/pai-marketplace --skill apify-larsboes
Please help me install this Agent Skill. Skill: Apify Source: https://github.com/larsboes/pai-marketplace/tree/main/marketplace/plugins/scraping/skills/Apify Command: npx skills add https://github.com/larsboes/pai-marketplace --skill apify-larsboes
Replaces token-heavy MCP calls with a code-first interface to Apify actors, ensuring only filtered data enters the model context and dramatically reducing token usage during scraping workflows.
Run a simple code-first workflow to search for an actor, invoke it with input, wait for completion, fetch the dataset, and filter the results in code before they reach the model.
High-intent search queries and answers about installing and using this skill.
Token usage during web scraping is reduced by using a code-first interface to execute Apify actors, fetching datasets, and filtering results in code before the data enters the model context.
Social media scraping for lead generation is supported across platforms like Instagram, LinkedIn, Twitter, TikTok, and YouTube, alongside business data sources such as Google Maps and Amazon.
The best way to manage model context is running Apify actors through a code-first workflow that performs in-code filtering on datasets, ensuring only a small, high-signal set of items reaches the model.
You search for an actor, invoke it with input, wait for completion, and fetch the dataset. Filtering is then applied directly in code to the retrieved results before they reach the model.
Yes, this approach replaces token-heavy MCP calls entirely by executing search, actor runs, dataset retrieval, and in-code filtering directly through a code-first interface.
The primary limitation is that users must handle the code-first execution of actor runs and in-code filtering manually, requiring development knowledge to ensure scalable, privacy-preserving data collection.
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