Apify

Search Apify actors, launch runs, and read datasets in code.

186|24|Updated Jan 1, 2026
One-click install
npx skills add https://github.com/Steffen025/pai-opencode --skill apify-steffen025
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: Apify
Source: https://github.com/Steffen025/pai-opencode/tree/main/.opencode/skills/Apify
Command: npx skills add https://github.com/Steffen025/pai-opencode --skill apify-steffen025

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a code-first interface to Apify actors, replacing token-heavy MCP calls with in-code data handling. It enables developers to orchestrate actor searches, executions, and dataset reads entirely within code, ensuring that only filtered results reach the model context.

Core Features & Use Cases

  • End-to-end control: search for actors, run them with input, wait for completion, and read the resulting dataset.
  • Token-efficient pipelines: filter and transform data in code before it reaches the model to dramatically reduce token usage.
  • Broad coverage: supports social media scraping, business data extraction, and e-commerce workflows via Apify actors.

Quick Start

Install and import the code-first Apify client, create an instance with your API token, search for actors, select an actor and call it with input, wait for the run to finish, and read results from the dataset. Then apply in-code filtering to keep only the relevant items before returning to the model context.

Frequently Asked Questions about Apify

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I reduce token usage when running Apify actors through an LLM?

A code-first Apify wrapper replaces token-heavy MCP calls by handling actor searches, executions, and dataset reads within code, allowing you to filter and transform data before returning it to the model context.

Can I search for and run Apify actors without loading the entire dataset into context?

Yes, a code-first Apify interface enables end-to-end control: searching actors, running them with input, waiting for completion, and reading datasets, all while keeping heavy data out of the model context.

What types of scraping workflows are supported by code-first Apify wrappers?

Code-first Apify wrappers support social media scraping, business data extraction, and e-commerce workflows by orchestrating actors with configurable run options like memory, timeout, and build versions.

How do I configure memory and timeout settings for an Apify actor run?

You can configure memory, timeout, and build options through the configurable run parameters provided by the code-first Apify client when launching an actor run and waiting for completion.

Why does my Apify MCP integration consume so many tokens?

MCP integrations consume many tokens because raw dataset payloads pass directly into the model context, whereas a code-first wrapper filters and transforms data in code before returning results to the model.