A specialized data extraction tool that automates the collection of Instagram profile metrics and engagement data for marketing audits.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install instagram-collector
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install instagram-collector using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Instagram Collector Skill?
The Instagram Collector is an automated data gathering tool designed to bridge the gap between social media presence and actionable marketing insights. By integrating directly with the Apify Instagram Profile Scraper, this skill enables developers to programmatically retrieve follower counts, post statistics, and detailed engagement metrics. As a core component of the Openclaw Skills ecosystem, it ensures that your marketing audit pipelines are populated with fresh, accurate data without manual scraping or data entry.
This skill is particularly valuable for teams building automated reporting tools or competitive analysis dashboards. It handles the complexity of API interactions, polling logic, and data normalization, providing a clean, typed interface for your application. By using Openclaw Skills like this collector, you can focus on data analysis rather than the technical overhead of social media data extraction.
Instagram Collector Skill Use Cases
- Automating comprehensive social media audits for brands and competitors.
- Generating real-time engagement reports for digital marketing agencies.
- Tracking industry hashtag trends and posting frequencies for content strategy.
- Populating performance sections of marketing audit reports within Openclaw Skills pipelines.
How Instagram Collector Skill Works
- The collector receives a target Instagram handle (e.g., "gymshark") as an input parameter.
- It initiates a run on the Apify Instagram Profile Scraper actor using a secure API token.
- The skill polls the Apify service for completion, managing a 60-second timeout to ensure pipeline efficiency.
- Once the data is retrieved, it calculates the engagement rate by averaging likes and comments relative to the total follower count.
- It analyzes the timestamps of the last 30 posts to generate a human-readable posting frequency metric.
- A regex-based extraction process identifies the top 10 most frequently used hashtags from recent captions.
- The final structured object is returned to the pipeline for further processing by other Openclaw Skills.
Instagram Collector Skill Setup
To get started with the Instagram Collector, ensure your environment is configured with the necessary API credentials.
# Set your Apify API Token in your environment variables
export APIFY_API_TOKEN='your_apify_token_here'
The skill depends on the apifyService.ts module for communication. Ensure your project has the required dependencies installed to handle asynchronous actor runs and polling logic.
Instagram Collector Skill Data Schema & Taxonomy
The skill returns a strictly typed InstagramData object. Below is the structure used across Openclaw Skills for this collector:
| Property | Type | Description |
|---|---|---|
followers |
number | Total number of followers for the handle. |
posts |
number | Total number of posts published on the account. |
engagementRate |
number | The percentage of followers engaging with content. |
postingFrequency |
string | Human-readable frequency (e.g., "1.5 posts/day"). |
avgLikes |
number | Average number of likes across recent posts. |
topHashtags |
string[] | The top 10 most utilized hashtags in recent captions. |
error |
string? | Optional field containing error details if the collection fails. |
Instagram Collector Skill Advanced Features
- Intelligent engagement rate calculation with built-in protection against division by zero errors.
- Automated posting frequency analysis that converts post timestamps into readable intervals like "posts/week" or "posts/month".
- Regex-powered hashtag discovery to identify high-performing content trends.
- Robust error handling that returns a standardized empty object rather than throwing exceptions, ensuring your Openclaw Skills pipeline remains stable even if a profile is private or missing.
SKILL.md
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