apify-hello-world
Run your first Apify Actor and retrieve results via apify-client. Use when starting a new Apify integration, testing connectivity, or learning the Actor call/dataset retrieval pattern. Trigger with "apify hello world", "apify example", "run an apify actor", "apify quick start", "first apify scrape".
Install / Use
npx skills add jeremylongshore/tons-of-skills-marketplace --skill apify-hello-worldInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
AutomationSupported Platforms
Our assessment of apify-hello-world
apify-hello-world scores 88/100 on our quality scale, 1278th of 3,055 Automation skills we index (top 42%).
Its SKILL.md is 5.2 KB long, well organised into 16 sections with 3 code examples: a solid amount of guidance for an agent.
With 2,785 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 8 days ago, so apify-hello-world is actively maintained.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.
Automated pattern scan on 2026-10-02. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
apify-hello-world compared with similar skills
All 4 of these similar skills score higher than apify-hello-world; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| apify-hello-world (this skill)by jeremylongshore | 88 | 2.8k | 8d ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 88.1k | 17d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 74.3k | today | CLAUDE.md |
| rufloby ruvnet | 100 | 73.7k | today | CLAUDE.md |
| Scraplingby D4Vinci | 100 | 85.2k | 1d ago | MCP Server |
Frequently asked questions
- How do I install apify-hello-world?
- Run
npx skills add jeremylongshore/tons-of-skills-marketplace --skill apify-hello-world. The install tabs above show the steps for each supported agent. - Which AI agents does apify-hello-world work with?
- It is written for Claude Code, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is apify-hello-world safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is apify-hello-world still maintained?
- The repository was last updated 8 days ago, so apify-hello-world is actively maintained.
Skill content
View source on GitHubname: apify-hello-world description: | Run your first Apify Actor and retrieve results via apify-client. Use when starting a new Apify integration, testing connectivity, or learning the Actor call/dataset retrieval pattern. Trigger with "apify hello world", "apify example", "run an apify actor", "apify quick start", "first apify scrape". allowed-tools: Read, Write, Edit, Bash(npm:), Bash(npx:), Bash(node:*) version: 1.5.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io tags:
- saas
- scraping
- automation
- apify compatibility: Designed for Claude Code
Apify Hello World
Overview
Run a public Actor from the Apify Store, wait for it to finish, and retrieve the scraped data. This demonstrates the fundamental call-wait-collect pattern used in every Apify integration.
Prerequisites
npm install apify-clientcompletedAPIFY_TOKENenvironment variable set- See
apify-install-authif not ready
Authentication
Every call authenticates with a personal API token passed to the client
constructor: new ApifyClient({ token: process.env.APIFY_TOKEN }). Keep the
token in the APIFY_TOKEN environment variable — never hard-code it in the
script. Full setup (where to generate the token, how to export it) lives in the
apify-install-auth skill.
Core Pattern: Call Actor, Get Data
import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
// 1. Run an Actor and wait for it to finish
const run = await client.actor('apify/website-content-crawler').call({
startUrls: [{ url: 'https://docs.apify.com/academy' }],
maxCrawlPages: 5,
});
// 2. Retrieve results from the default dataset
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`Crawled ${items.length} pages:`);
items.forEach(item => {
console.log(` - ${item.url}: ${item.text?.substring(0, 80)}...`);
});
This is the whole workflow at a high level: authenticate, .call() an Actor,
then read its default dataset. For sync-vs-async execution, pagination,
downloads, key-value store retrieval, run-configuration options, and a table of
popular starter Actors, see run & retrieval patterns.
Instructions
Step 1: Create the Script
Use Write (or Edit an existing file) to create hello-apify.ts (or .js) with
the Core Pattern code above. Use Read to confirm the file contents before running.
Step 2: Run It
# With tsx (recommended)
npx tsx hello-apify.ts
# Or with Node.js (plain JS)
node hello-apify.js
Step 3: Understand the Output
The Actor runs on Apify's cloud infrastructure. See the Output section below for the run-object fields returned when it finishes.
Output
A successful run returns a run object plus a populated dataset. The fields you read most:
| Field | Meaning |
|-------|---------|
| run.id | Unique run identifier |
| run.status | SUCCEEDED, FAILED, TIMED-OUT, or ABORTED |
| run.defaultDatasetId | ID of the dataset containing scrape results |
| run.defaultKeyValueStoreId | ID of the KV store with metadata/artifacts |
| run.statusMessage | Human-readable detail (essential when status is not SUCCEEDED) |
client.dataset(run.defaultDatasetId).listItems() returns { items }, where
each item is one scraped record (shape depends on the Actor). Always branch on
run.status before reading the dataset — a FAILED run can leave an empty or
partial dataset. See worked examples for the full
run-object breakdown.
Error Handling
| Error | Cause | Solution |
|-------|-------|----------|
| Actor not found | Wrong Actor ID | Check ID at apify.com/store |
| run.status === 'FAILED' | Actor crashed | Check run.statusMessage for details |
| run.status === 'TIMED-OUT' | Exceeded timeout | Increase timeout or reduce workload |
| Dataset is empty | Actor produced no output | Verify input parameters; check Actor logs |
| 402 Payment Required | Insufficient compute units — Apify returns HTTP 402 when your account is out of prepaid units | Top up at console.apify.com/billing |
Examples
Minimal happy-path collection — call an Actor and count the results:
const run = await client.actor('apify/website-content-crawler').call({
startUrls: [{ url: 'https://example.com' }],
maxCrawlPages: 10,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`Scraped ${items.length} pages`);
For the complete status-guarded "scrape and save to JSON" script and a full breakdown of the run object, see worked examples.
Resources
- Apify Store — Browse Actors
- Run Actor via API
- JS Client Examples
- Run & retrieval patterns — sync/async, pagination, run config, starter Actors
- Worked examples — full scrape-and-save script
Next Steps
Once your first Actor run succeeds, proceed to the apify-local-dev-loop skill
to build and iterate on your own Actor locally, then deploy it back to the Apify
platform. That skill covers the develop-run-debug cycle in depth.
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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
