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Agent skill

Apify Core Workflow B

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

Manage Apify datasets, key-value stores, and request queues programmatically, and orchestrate multi-Actor pipelines.

MITAuto-check passedData & Analytics

Install Apify Core Workflow B

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill apify-core-workflow-b -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace apify-core-workflow-b --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/apify-core-workflow-b .claude/skills/apify-core-workflow-b && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
apify-core-workflow-b
GitHub stars
2.8k
Token cost
~1.8k tokens
SKILL.md length
554 words
Files
3 (incl. references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Manage Apify datasets, key-value stores, and request queues programmatically, and orchestrate multi-Actor pipelines.

  • You need to read
  • SKILL.md covers Overview, Prerequisites, Authentication and Storage Types at a Glance, plus 6 more sections
  • Calls npm; needs APIFY_TOKEN
  • Write Apify datasets

What it does

Apify Core Workflow B is an agent skill from jeremylongshore/tons-of-skills-marketplace. Manage Apify datasets, key-value stores, and request queues programmatically, and orchestrate multi-Actor pipelines. Use when you need to read or write Apify datasets, export scraped data to CSV/JSON/XLSX, store config or binary artifacts in a key-value store, manage a resumable request queue, chain Actors into a scrape → transform → export pipeline, or monitor Actor run status and cost. Trigger with "apify dataset", "apify key-value store", "apify storage", "export apify data", "apify pipeline", "apify request…

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/pipelines.md` and `references/storage-operations.md`). Compatibility notes: Designed for Claude Code

It sits in Data & Analytics, covering Web scraping and NoSQL databases. It works with Apify and Microsoft Excel. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • You need to read
  • Write Apify datasets
  • Export scraped data to CSV/JSON/XLSX
  • Binary artifacts in a key-value store

Example prompts

  • “apify dataset”
  • “apify key-value store”
  • “apify storage”
  • “/apify-core-workflow-b”

Requirements

  • Node.js
  • A credential in APIFY_TOKEN
  • Compatibility (from SKILL.md): Designed for Claude Code
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Bash(npm:*), Bash(npx:*), Grep

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Bash(npm:*)
    • Bash(npx:*)
    • Grep

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • npm

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • docs.apify.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • APIFY_TOKEN

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Claude Code

    From compatibility in the SKILL.md frontmatter.

Context cost

Apify Core Workflow B loads about 1.8k tokens when it runs, and up to ~3.3k if it reads all its reference files. Until then it costs about 137 tokens; SKILL.md has 554 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~137
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 554 words, ~1,771 tokens.

Download SKILL.mdSave it as .claude/skills/apify-core-workflow-b/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
apify-core-workflow-b
description
Manage Apify datasets, key-value stores, and request queues programmatically, and orchestrate multi-Actor pipelines. Use when you need to read or write Apify datasets, export scraped data to CSV/JSON/XLSX, store config or binary artifacts in a key-value store, manage a resumable request queue, chain Actors into a scrape → transform → export pipeline, or monitor Actor run status and cost. Trigger with "apify dataset", "apify key-value store", "apify storage", "export apify data", "apify pipeline", "apify request queue".
allowed-tools
Read, Write, Edit, Bash(npm:*), Bash(npx:*), Grep
compatibility
Designed for Claude Code
version
1.5.0
license
MIT
author
Jeremy Longshore <jeremy@intentsolutions.io>
tags
saas, scraping, automation, apify

Apify Core Workflow B — Storage & Pipelines

Overview

Manage Apify's three storage types (datasets, key-value stores, request queues) and orchestrate multi-Actor pipelines using the apify-client JS SDK. Covers CRUD operations, data export, automatic pagination, and chaining Actors together (scrape → transform → export).

This SKILL.md gives you the high-level workflow plus the essential first example for each storage type. Drill into the reference files for the complete, copy-ready code:

Prerequisites

  • Node.js with apify-client installed (npm install apify-client).
  • An Apify account token exported as APIFY_TOKEN (see Authentication below).
  • Familiarity with apify-core-workflow-a (Actor invocation and run lifecycle), since pipelines chain Actor runs and read their default storages.

Authentication

All operations authenticate with an Apify API token. Never hard-code it — read it from the environment and construct the client once:

typescript
import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: process.env.APIFY_TOKEN });

Generate a token at Apify Console → Settings → Integrations, then export it (export APIFY_TOKEN=apify_api_...) or load it from your secrets manager.

Storage Types at a Glance

StorageBest ForAnalogyRetention
DatasetLists of similar items (products, pages)Append-only table7 days (unnamed)
Key-Value StoreConfig, screenshots, summaries, any fileS3 bucket7 days (unnamed)
Request QueueURLs to crawl (managed by Crawlee)Job queue7 days (unnamed)

Named storages persist indefinitely. Unnamed (default run) storages expire after 7 days.

Instructions

Pick the storage type you need, use the skeleton below to get started, then open the linked reference for the full operation set.

Datasets — append-only item lists

getOrCreate a named dataset, push items, and list them (pagination is manual):

typescript
const dataset = await client.datasets().getOrCreate('product-catalog');
const dsClient = client.dataset(dataset.id);
await dsClient.pushItems([{ sku: 'ABC123', name: 'Widget', price: 9.99 }]);
const { items, total } = await dsClient.listItems({ limit: 100, offset: 0 });

Full auto-pagination loop, CSV/JSON/XLSX export, and field filtering: storage-operations.md, Step 1.

Key-value stores — config, files, and Actor OUTPUT

Store JSON or binary records by key, then retrieve them:

typescript
const store = await client.keyValueStores().getOrCreate('scraper-config');
const kvClient = client.keyValueStore(store.id);
await kvClient.setRecord({ key: 'settings', value: { maxRetries: 3 }, contentType: 'application/json' });
const record = await kvClient.getRecord('settings');

Binary records, key listing, and reading a run's default OUTPUT: storage-operations.md, Step 2.

Request queues — resumable crawl URLs

Create a named queue and add requests (deduplicated by uniqueKey):

typescript
const queue = await client.requestQueues().getOrCreate('my-crawl-queue');
const rqClient = client.requestQueue(queue.id);
await rqClient.addRequest({ url: 'https://example.com/page1', uniqueKey: 'page1' });

Batch adds and queue stats: storage-operations.md, Step 3.

Show full SKILL.md (215 more words)Show less
Multi-Actor pipelines & monitoring

Chain Actors (scrape → transform → export) and monitor run status and cost. Full runPipeline() function and run-monitoring code: pipelines.md.

Output

  • Datasets return { items, total, count, offset, limit } from listItems(); downloadItems(format) returns a Buffer in csv / json / xlsx.
  • Key-value stores return { key, value, contentType } from getRecord() and { items } (each { key, size }) from listKeys().
  • Request queues return { pendingRequestCount, handledRequestCount, ... } from get().
  • Pipelines return the named export dataset id; run monitoring yields { status, statusMessage, stats, usage, usageTotalUsd } per run.

Error Handling

ErrorCauseSolution
Dataset not foundExpired (unnamed, >7 days)Use named datasets for persistence
Record too largeKV store 9MB record limitSplit into multiple records
Push failedDataset items >9MB batchPush in smaller batches
Request already existsDuplicate uniqueKeyExpected behavior, queue deduplicates

Examples

Export a named dataset to CSV — get the client, download the buffer, write it:

typescript
const csvBuffer = await client.dataset('product-catalog').downloadItems('csv');
require('fs').writeFileSync('products.csv', csvBuffer);

Read an Actor run's OUTPUT record — after a run completes:

typescript
const run = await client.actor('apify/web-scraper').call(input);
const output = await client.keyValueStore(run.defaultKeyValueStoreId).getRecord('OUTPUT');

Longer end-to-end examples — the full pagination loop, binary record storage, and the three-stage runPipeline() — live in the reference files: storage-operations.md and pipelines.md.

Resources

Next Steps

For common errors and their fixes across the Apify pack, see the apify-common-errors skill. For Actor invocation and run lifecycle basics that pipelines build on, see apify-core-workflow-a.

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in skills/.curated/apify-core-workflow-b of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • references/pipelines.md
  • references/storage-operations.md

Open the folder on GitHubat commit cfae287

Compare with similar skills

Apify Core Workflow B next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Apify Core Workflow B compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Apify Core Workflow B this skilljeremylongshore/tons-of-skills-marketplace2.8k—~1.8kAutomated safety check: PassMIT
Apify Generate Output Schemasickn33/agentic-awesome-skills47k1 repos~4.3kAutomated safety check: PassMIT
Yao Doubao Crawleryaojingang/yao-geo-skills871—~475Automated safety check: PassMIT
Data Cleaningericrisco/rsc-harness180—~3.6kAutomated safety check: PassMIT
Apify Jobs Dataapify/awesome-skills266—~5.5kAutomated safety check: PassApache-2.0
Reddit Post Findergooseworks-ai/goose-skills1.2k1 repos~1.2kAutomated safety check: PassMIT

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Works with

Categories

Questions about Apify Core Workflow B

What does Apify Core Workflow B do?

Manage Apify datasets, key-value stores, and request queues programmatically, and orchestrate multi-Actor pipelines. Apify Core Workflow B is an agent skill from jeremylongshore/tons-of-skills-marketplace. Manage Apify datasets, key-value stores, and request queues programmatically, and orchestrate multi-Actor pipelines.

When should I use Apify Core Workflow B?

Apify Core Workflow B fits situations like: you need to read; write Apify datasets; export scraped data to CSV/JSON/XLSX; binary artifacts in a key-value store.

How do I install Apify Core Workflow B in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill apify-core-workflow-b -a claude-code`. Or copy the skill folder (skills/.curated/apify-core-workflow-b in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/apify-core-workflow-b in your project. Claude Code loads it when a task matches its description.

How do I install Apify Core Workflow B in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill apify-core-workflow-b -a codex`. Or copy the skill folder (skills/.curated/apify-core-workflow-b in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/apify-core-workflow-b in your project. Codex loads it when a task matches its description.

Can I use Apify Core Workflow B in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill apify-core-workflow-b -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/apify-core-workflow-b, .gemini/skills/apify-core-workflow-b, .github/skills/apify-core-workflow-b and .opencode/skills/apify-core-workflow-b in your project.

What does Apify Core Workflow B need to run?

Going by SKILL.md and its folder, Apify Core Workflow B needs the command-line tools its instructions call (npm) and credentials named APIFY_TOKEN. Our summary lists: Node.js; A credential in APIFY_TOKEN. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash(npm:*), Bash(npx:*), Grep. Compatibility (from SKILL.md): Designed for Claude Code.

Does Apify Core Workflow B access the network?

SKILL.md names 1 domain. As links in the text: docs.apify.com. This is read from the text; nothing was executed.

Is Apify Core Workflow B safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Apify Core Workflow B use?

Apify Core Workflow B is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Apify Core Workflow B use?

About 1.8k tokens (SKILL.md is roughly 7.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.6k tokens, read only when the agent opens those files.

What are the alternatives to Apify Core Workflow B?

Skills that share tags, products or a category with Apify Core Workflow B: Apify Generate Output Schema (sickn33/agentic-awesome-skills, 47k stars), Yao Doubao Crawler (yaojingang/yao-geo-skills, 871 stars), Data Cleaning (ericrisco/rsc-harness, 180 stars) and Apify Jobs Data (apify/awesome-skills, 266 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Apify Core Workflow B?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.