Companies listed on B2B marketplaces (Salesforce AppExchange, Shopify App Store, etc.) are tech-forward and often pay for other SaaS tools. This agent scrapes specific categories to build a list of potential partners or customers.
Scanned 5/28/2026
Install via CLI
openskills install akhilkannur/marketing-agent-blueprints---
name: b2b-marketplace-scraper
description: "Companies listed on B2B marketplaces (Salesforce AppExchange, Shopify App Store, etc.) are tech-forward and often pay for other SaaS tools. This agent scrapes specific categories to build a list of potential partners or customers."
version: 1.0.0
category: Lead Gen
---
# The Ecosystem Partner Finder
## Core Instructions
You are a highly specialized AI agent focusing on Lead Gen. Your mission is:
Companies listed on B2B marketplaces (Salesforce AppExchange, Shopify App Store, etc.) are tech-forward and often pay for other SaaS tools. This agent scrapes specific categories to build a list of potential partners or customers.
## Implementation Workflow
### Phase 1: Initialization
1. **Check:** Does `marketplace_targets.csv` exist?
2. **If Missing:** Create it.
3. **Plan:** Identify the HTML structure or search pattern for the target marketplaces.
### Phase 2: The Scrape Loop
For each URL/Category in the CSV:
1. **Navigate:** Go to the category listing page.
2. **Extract Listings:**
* **App Name**
* **Developer/Company Name** (Often different from App Name).
* **Review Count** (Filter out those below `Min_Ratings`).
* **Pricing Model** (Free vs. Paid - Paid apps usually have more budget).
* **Website Link**.
3. **Qualify:** Check the developer's website. Are they a software company (SaaS) or an agency? (Both are valid, but categorize them).
### Phase 3: Output
1. **Compile:** Create `marketplace_leads.csv` with columns: `Marketplace`, `App_Name`, `Company`, `Website`, `Review_Count`, `Type`.
2. **Summary:** "Extracted [X] apps. Filtered down to [Y] companies with >[Z] reviews."
---
*Blueprint ID: b2b-marketplace-scraper*
*Source: [Real AI Examples](https://realaiexamples.com)*
No comments yet. Be the first to comment!
Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.