scrape-airdrops

name: scrape-airdrops description: This skill should be used when the user asks to "scrape airdrops", "get airdrop data", "find new airdrops", "track airdrops", "check airdrop updates", or mentions CryptoRank or DeFiLlama airdrops. Automates airdrop data collection using agent-browser CLI.

Scrape Airdrops

Automate airdrop data collection from CryptoRank and DeFiLlama using the agent-browser CLI.

Prerequisites

• agent-browser CLI installed and accessible
• Run agent-browser --help to verify installation

Core Workflow

Step 1: Initialize Browser

Open the target airdrop platform:

agent-browser open https://cryptorank.io/airdrops

Wait for page load, then take a snapshot:

agent-browser snapshot -i

Step 2: Navigate and Filter (CryptoRank)

The CryptoRank airdrops page shows ongoing and upcoming airdrops.

1. Take interactive snapshot to identify filter elements:

   agent-browser snapshot -i
   

2. Apply filters if needed (e.g., status = Active):

   • Look for filter buttons with refs like @e1, @e2
   • Click to apply: agent-browser click @e5

3. Wait for content update after filtering:

   agent-browser snapshot -i
   

Step 3: Extract Airdrop Data

For each airdrop entry visible, extract:

JavaScript extraction pattern:

agent-browser evaluate "document.querySelectorAll('.airdrop-card').forEach(card => { console.log(card.innerText) })"

Step 4: Scrape DeFiLlama Airdrops

Navigate to DeFiLlama:

agent-browser open https://defillama.com/airdrops

DeFiLlama provides a different data format focused on:

• Confirmed airdrops
• Potential airdrops (projects with no token yet)
• Historical airdrop data

Extract using similar snapshot and evaluate patterns.

Step 5: Compile Results

Merge data from both sources, deduplicating by project name.

Output format (JSON):

{
  "scraped_at": "2025-01-26T12:00:00Z",
  "sources": ["CryptoRank", "DeFiLlama"],
  "airdrops": [
    {
      "name": "Project Name",
      "status": "Active",
      "platform": "Ethereum",
      "estimated_value": "$500",
      "end_date": "2025-02-15",
      "requirements": ["Hold NFT", "Use protocol"],
      "source": "CryptoRank",
      "link": "https://..."
    }
  ]
}

Step 6: Generate Report

Create both Markdown and JSON outputs.

Markdown format:

# Airdrop Report - Jan 26, 2025

## Active Airdrops

### Project Name ⭐
- **Platform:** Ethereum
- **Estimated Value:** $500
- **End Date:** Feb 15, 2025
- **Requirements:** Hold NFT, Use protocol
- **Link:** [Official Page](https://...)

---

Save files:

• airdrops-YYYY-MM-DD.md - Human-readable report
• airdrops-YYYY-MM-DD.json - Structured data

Step 7: Send Notification (Optional)

If telegram-notification MCP is configured, send summary:

Tool: mcp__telegram-notification__send_notification
Parameters:
  message: "🪂 Airdrop Report - Jan 26\n\n✅ 5 Active Airdrops\n⏳ 3 Upcoming\n\nTop: ProjectA ($1000), ProjectB ($500)"
  parse_mode: "Markdown"

agent-browser Quick Reference

Handling Dynamic Content

Many airdrop pages use infinite scroll or lazy loading:

1. Scroll to load more:

   agent-browser evaluate "window.scrollTo(0, document.body.scrollHeight)"
   

2. Wait and re-snapshot:

   agent-browser snapshot -i
   

3. Repeat until all content loaded

Error Handling

• If page fails to load, retry once with increased timeout
• If element not found, re-take snapshot to refresh refs
• Skip individual airdrops that fail extraction, continue with others
• Log errors but don't stop the entire scrape

Output Location

Save reports to user's current directory or specified output path:

• Default: ./airdrops-YYYY-MM-DD.{md,json}
• Custom: Use path specified by user