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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: "apify hello world", "apify example", "run an apify actor", "apify quick start", "first apify scrape".
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/ComeOnOliver/skillshub --skill apify-hello-world命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
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| name | 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: "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 | 1.0.0 |
| license | MIT |
| author | Jeremy Longshore <jeremy@intentsolutions.io> |
| tags | ["saas","scraping","automation","apify"] |
| compatible-with | claude-code |
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.
npm install apify-client completedAPIFY_TOKEN environment variable setapify-install-auth if not readyimport { 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(, )}...`);
});
Create hello-apify.ts (or .js) with the code above.
# With tsx (recommended)
npx tsx hello-apify.ts
# Or with Node.js (plain JS)
node hello-apify.js
The Actor runs on Apify's cloud infrastructure. When it finishes:
run.id — unique run identifierrun.status — SUCCEEDED, FAILED, TIMED-OUT, or ABORTEDrun.defaultDatasetId — ID of the dataset containing resultsrun.defaultKeyValueStoreId — ID of the KV store with metadata| Actor ID | Purpose | Typical Input |
|---|---|---|
apify/website-content-crawler | Crawl and extract text | { startUrls, maxCrawlPages } |
apify/web-scraper | General-purpose scraper | { startUrls, pageFunction } |
apify/cheerio-scraper | Fast HTML scraper | { startUrls, pageFunction } |
apify/google-search-scraper | Google SERP results | { queries, maxPagesPerQuery } |
// SYNCHRONOUS — .call() waits for the Actor to finish (simple, blocking)
const run = await client.actor('apify/web-scraper').call(input);
// ASYNCHRONOUS — .start() returns immediately, poll later
const run = await client.actor('apify/web-scraper').start(input);
// ... do other work ...
const finishedRun = await client.run(run.id).waitForFinish();
// Get all items (paginated internally)
const { items } = await client.dataset(run.defaultDatasetId).listItems();
// Get items with pagination control
const page1 = await client.dataset(run.defaultDatasetId).listItems({
limit: 100,
offset: 0,
});
// Download entire dataset as CSV/JSON/etc.
const buffer = await client.dataset(run.defaultDatasetId).downloadItems('csv');
// Get a named output from the key-value store
const screenshot = await client
.keyValueStore(run.defaultKeyValueStoreId)
.getRecord('screenshot');
const run = await client.actor('apify/web-scraper').call(
input, // Actor-specific input object
{
memory: 1024, // Memory in MB (128–32768, powers of 2)
timeout: 300, // Timeout in seconds (default: Actor's setting)
build: 'latest', // Which build to use
waitSecs: 120, // Max wait for .call() (0 = don't wait)
}
);
| 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 | Top up at console.apify.com/billing |
import { ApifyClient } from 'apify-client';
import { writeFileSync } from 'fs';
const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
async function scrapeAndSave() {
console.log('Starting Actor run...');
const run = await client.actor('apify/website-content-crawler').call({
startUrls: [{ url: 'https://example.com' }],
maxCrawlPages: 10,
});
if (run.status !== 'SUCCEEDED') {
throw new Error(`Actor run failed: ${run.status} — ${run.statusMessage}`);
}
const { items } = await client.dataset(run.defaultDatasetId).listItems();
writeFileSync('results.json', JSON.stringify(items, null, 2));
console.log(`Saved ${items.length} items to results.json`);
}
scrapeAndSave().catch(console.error);
Proceed to apify-local-dev-loop for local Actor development.