Apify Cli

Apify· v1.0.0

codingOfficial

Official Provider SkillView repo

Patterns for invoking the Apify CLI (`apify`) from agents. Covers authentication, creating/running/pushing Actors, calling Actors in the cloud, and reading results from datasets and key-value stores.

Files1 files

SKILL.md113 lines

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Install

Recommended

One command — your agent picks it up automatically.

Select AI agent

Select an AI agent above to see the install command.

Manual Install

More steps

Download the file and paste it into your agent's system prompt.

Skill details

Versionv1.0.0

AuthorApify

Categorycoding

Skill IDapify/apify-cli/skills/apify

Related skills

Apify Actor DevelopmentDevelop, debug, and deploy Apify Actors - serverless cloud programs for web scraping, automation, and data processing. Use when creating new Actors, modifying existing ones, or troubleshooting Actor code.Apify ActorizationConvert existing projects into Apify Actors - serverless cloud programs. Actorize JavaScript/TypeScript (SDK with Actor.init/exit), Python (async context manager), or any language (CLI wrapper). Use when migrating code to Apify, wrapping CLI tools as Actors, or adding Actor SDK to existing projects.Apify Generate Output SchemaGenerate output schemas (dataset_schema.json, output_schema.json, key_value_store_schema.json) for an Apify Actor by analyzing its source code. Use when creating or updating Actor output schemas.Apify Sdk IntegrationIntegrate Apify into an existing JavaScript/TypeScript or Python application using the apify-client package. Use when adding web scraping, automation, or data extraction capabilities to an existing app via the Apify API.Bug TriageTriage open GitHub bug issues for Apify MCP server. Fetches issues, analyzes root causes, drafts developer-to-developer responses, and posts after user approval. Use when handling user bug reports, responding to issues, or cleaning up stale bugs.DigExplore, analyze, plan, or spec features for the Apify MCP server. Adapts to what the user asks — from quick code exploration to full GitHub issue specs. Use when the user asks to explore code, understand behavior, plan a change, design a feature, or create an issue spec.