majiayu000 02 - Agency Researcher Skill
Overview
This skill instructs Claude Code to find and qualify real estate agencies in a given suburb. It uses web search and browser automation to gather comprehensive agency data.
Skill File Location
.claude/skills/agency-researcher/SKILL.md
SKILL.md Content
---
name: agency-researcher
description: Find and qualify real estate agencies in a given suburb
---
# Agency Researcher Skill
You are an expert real estate industry researcher. Your task is to find, analyze, and qualify real estate agencies in Australian suburbs.
## Your Mission
Given a suburb name, find the top real estate agencies operating in that area and gather comprehensive data about each one. This data will be used to generate personalized demo pages.
## Research Process
### Step 1: Initial Search
Search for real estate agencies in the target suburb:
Search queries to use:
- "[suburb] real estate agents"
- "[suburb] real estate agencies"
- "best real estate agents [suburb] Sydney"
- "property agents [suburb]"
Use WebSearch tool to find agencies. Aim to identify 8-12 agencies initially.
### Step 2: For Each Agency, Gather Data
Visit each agency's website using Chrome browser tools and extract:
#### Basic Information
- **Agency Name**: Official business name
- **Website URL**: Main website
- **Phone Number**: Primary contact (look in header, footer, contact page)
- **Email**: General enquiry email
- **Address**: Physical office location
#### Branding (CRITICAL - needed for demo pages)
- **Logo URL**: Direct URL to logo image
- Check: header, footer, about page
- Right-click logo → "Copy image address"
- Prefer PNG or SVG, fallback to JPG
- Must be publicly accessible URL
- **Primary Brand Color**: Main color used in branding
- Check: header background, buttons, headings
- Extract hex code (e.g., #1a365d)
- Use browser dev tools if needed: inspect element → computed styles
- **Secondary Color**: Accent/secondary color
- Check: hover states, borders, secondary buttons
- Extract hex code
#### Team & Size Indicators
- **Team Size**: Number of agents
- Check "Our Team" or "Meet the Team" page
- Count agent profiles
- If no team page, estimate from listings ("Listed by X agents")
- **Principal/Owner Name**: Decision maker if findable
- Look for "Principal", "Director", "Owner" in team page
- Note their name for personalization
#### Listing Activity
- **Active Listings Count**: Current properties for sale/rent
- Check "Properties" or "Listings" page
- Count or note the displayed total
- Note mix of sales vs rentals if visible
- **Has Property Management**: Do they offer PM services?
- Check services page
- Look for "Property Management", "Rentals", "Landlords"
- Boolean: true/false
#### Current Solutions (Pain Indicators)
- **Has After-Hours Number**: Do they have 24/7 contact?
- Check contact page for "after hours", "emergency", "24/7"
- If only business hours listed = false
- **Has Chat Widget**: Live chat on website?
- Check for chat bubble/widget on homepage
- Look for Intercom, Drift, LiveChat, etc.
- Boolean: true/false
- **Has Online Booking**: Can visitors book inspections online?
- Check listing pages for booking buttons
- Boolean: true/false
#### Review Analysis (Optional but valuable)
- Search Google for "[Agency Name] reviews"
- Check Google Business Profile rating
- Note any reviews mentioning:
- "couldn't reach", "didn't answer", "no response"
- These indicate communication pain points
### Step 3: Calculate Pain Score
For each agency, calculate a "pain score" (0-100) indicating likelihood to need Voqo:
Pain Score Formula:
Base Score: 0
High Listing Volume:
- 30+ listings: +20 points
- 20-29 listings: +15 points
- 10-19 listings: +10 points
Has Property Management: +25 points (PM means more after-hours calls)
Understaffed (high volume, small team):
- <5 agents AND 20+ listings: +20 points
- <3 agents AND 10+ listings: +15 points
No After-Hours Solution: +15 points
No Chat Widget: +10 points
No Online Booking: +5 points
Bad Review Signals: +10 points (If reviews mention communication issues)
Maximum possible: 100 points
### Step 4: Generate Pain Reasons
For each agency, create a list of specific pain points:
Examples:
- "45 active listings generating high call volume"
- "Team of only 4 agents managing 30+ properties"
- "No after-hours contact solution"
- "Property management adds rental enquiries"
- "No chat widget to capture web leads"
### Step 5: Output Format
Save results to `/data/agencies/[suburb-slug].json`:
```json
{
"suburb": "Surry Hills",
"searchedAt": "2025-01-15T10:30:00Z",
"agencies": [
{
"id": "ray-white-surry-hills",
"name": "Ray White Surry Hills",
"website": "https://raywhitesurryhills.com.au",
"phone": "+61 2 9361 6000",
"email": "surryhills.nsw@raywhite.com",
"address": "123 Crown Street, Surry Hills NSW 2010",
"branding": {
"logoUrl": "https://raywhitesurryhills.com.au/logo.png",
"primaryColor": "#ffe512",
"secondaryColor": "#1a1a1a"
},
"metrics": {
"teamSize": 6,
"listingCount": 45,
"hasPropertyManagement": true,
"hasAfterHoursNumber": false,
"hasChatWidget": false,
"hasOnlineBooking": true,
"principalName": "John Smith"
},
"painScore": 87,
"painReasons": [
"45 active listings generating high call volume",
"No after-hours contact solution",
"Property management adds rental enquiries",
"No chat widget to capture web leads"
],
"notes": "Major franchise, likely high-quality lead"
}
]
}
Also save individual agency files to /data/agencies/[agency-id].json for quick lookup.
Quality Guidelines
Logo URL Validation
- Must be direct image URL (ends in .png, .jpg, .svg, or served with image content-type)
- Must be publicly accessible (test in incognito)
- If logo not findable, use placeholder: leave field as null
Color Extraction
- Use actual hex values, not color names
- Verify colors are visible (not white on white)
- Primary color should be distinctive brand color
Data Accuracy
- Double-check phone numbers (should start with +61 or 02/03/07/08)
- Verify website URLs are correct
- Count listings manually if automated count unavailable
Handling Missing Data
- If data unavailable, use null not empty string
- Note in "notes" field what couldn't be found
- Don't make up data
Example Usage
When invoked with prompt:
"Research real estate agencies in Surry Hills, Sydney. Find top 10 agencies and gather full data for each."
Execute the full research process and save results to:
/data/agencies/surry-hills.json(full list)/data/agencies/ray-white-surry-hills.json(individual)/data/agencies/lj-hooker-surry-hills.json(individual)- etc.
Return summary:
Found 10 agencies in Surry Hills:
1. Ray White Surry Hills - Pain Score: 87
2. LJ Hooker Darlinghurst - Pain Score: 82
3. ...
Data saved to /data/agencies/surry-hills.json
---
## Invocation from Next.js
The API route `/api/search` will invoke Claude Code with this skill:
```typescript
// Pseudocode for API route
async function searchAgencies(suburb: string) {
// Invoke Claude Code with the skill
const result = await invokeClaudeCode({
prompt: `Use the agency-researcher skill to find and qualify real estate agencies in ${suburb}, Sydney. Find top 10 agencies and save results to /data/agencies/${slugify(suburb)}.json`,
tools: ['WebSearch', 'WebFetch', 'Read', 'Write', 'Bash', 'Glob'],
permissionMode: 'bypassPermissions',
skills: ['agency-researcher']
});
// Read results from saved file
const agencies = await readFile(`/data/agencies/${slugify(suburb)}.json`);
return JSON.parse(agencies);
}
Expected Output Quality
A high-quality agency research should include:
- 8-10 agencies from the suburb
- Complete branding for at least 80% (logo, colors)
- Accurate metrics (team size, listings)
- Calculated pain scores with reasoning
- Proper JSON format for downstream use
Troubleshooting
Can't find logo URL
- Try right-clicking logo in Chrome → Copy image address
- Check page source for og:image meta tag
- Look in favicon/apple-touch-icon as fallback
- Check brand guidelines page if exists
Can't determine colors
- Use Chrome DevTools → pick element → Computed styles
- Look for CSS variables (--primary-color)
- Check stylesheets for brand colors
- Screenshot and use color picker tool
Website blocks scraping
- Try using WebFetch with different user agent
- Check if site has API or feed
- Note in data that full scraping wasn't possible
- Gather what you can from Google Business listing
Team size unclear
- Count agent profiles on team page
- Check "our agents" or "meet the team"
- Look at recent listings for unique agent names
- Estimate from LinkedIn company page