signal-scanner

Signal Scanner

Searches multiple platforms for companies and individuals showing real-time buying signals that match the agency's ICP. Uses WebSearch to find leads across Reddit, Twitter/X, LinkedIn, job boards, funding news, Shopify Community, HackerNews, and gig platforms.

Prerequisites

• agency.config.json at repo root with services, icp, and scoring sections
• WebSearch tool available
• Optional: crm-writer skill for dedup against existing CRM leads

Phase 0: Intake

1. Read agency.config.json from the project root.

2. Extract:

   • services[].keywords -- all service keyword arrays
   • icp.segments[] -- each segment's markets, industries, titles, description
   • icp.primary_keywords, icp.secondary_keywords, icp.intent_keywords
   • icp.negative_keywords -- to filter out self-promoters
   • scoring.platform_weights -- to know which platforms to search
   • scoring.hiring_signals -- phrases that indicate active buying

   CRITICAL: All search queries MUST be derived from agency.config.json keywords. When Plasho's positioning changes week-to-week, queries change automatically. NEVER hardcode search queries.

3. Accept optional parameters:

   • platforms -- list of platforms to search (default: all from platform_weights)
   • max_results -- max leads to return (default: 25)
   • time_window -- how far back to search (default: "past week")
   • focus_segment -- specific ICP segment to target (default: all)
   • daily_targets -- read from agency.config.json outreach.daily_targets (default: 20 gig + 5 company = 25 total)
   • geo_split -- read from agency.config.json outreach.geo_split (default: 75% international, 25% India)

Phase 1: Query Generation

Build search queries by combining service keywords with intent signals and platform-specific syntax.

Lead Type Targeting

Queries are split into two categories:

GIG LEAD QUERIES (target: 20 leads) Platforms: Freelancer, Upwork, PeoplePerHour, Guru, Fiverr Must show clear buying signal and budget.

COMPANY LEAD QUERIES (target: 5 leads) Platforms: LinkedIn, Reddit, Twitter/X, Funding News, Product Hunt, Shopify Community, Instagram Brands, Google Maps, Shopify Store Discovery Must show very strong signal + ICP fit.

Geo Split Enforcement

75% of queries target international markets (US, UK, AU, EU):

• Add geo modifiers: "United States", "UK", "Australia", "Europe"
• Filter by .com, .co.uk, .com.au domains where applicable

25% of queries target India:

• Add geo modifiers: "India", "Mumbai", "Delhi", "Bangalore"
• Include Indian platforms and directories

Query templates per platform:

Reddit:

• site:reddit.com "{service_keyword}" "{intent_keyword}" after:{date}
• Subreddits to target: r/shopify, r/ecommerce, r/smallbusiness, r/startups, r/Entrepreneur, r/DTC
• Example: site:reddit.com "shopify developer" "need help" after:2024-01-01

Twitter/X:

• site:twitter.com OR site:x.com "{service_keyword}" "{intent_keyword}"
• Example: site:x.com "looking for shopify expert" "hire"

LinkedIn:

• site:linkedin.com/posts "{service_keyword}" "{intent_keyword}"
• site:linkedin.com/jobs "{service_keyword}"
• Example: site:linkedin.com/posts "shopify developer" "hiring"

Job Boards:

• site:indeed.com OR site:glassdoor.com "{service_keyword}" "{market}"
• site:angel.co OR site:wellfound.com "{service_keyword}"

Funding News:

• "{industry} startup" "raises" OR "funding" OR "seed round" OR "series A" {time_window}
• Filter to companies in ICP industries

Shopify Community:

• site:community.shopify.com "{intent_keyword}" "{service_keyword}"

HackerNews:

• site:news.ycombinator.com "{service_keyword}" "{intent_keyword}"

Gig Platforms (Freelancer, Upwork, PeoplePerHour, Guru, Fiverr):

• site:freelancer.com/projects "{service_keyword}"
• site:peopleperhour.com "{service_keyword}"

Upwork:

• site:upwork.com/jobs "{service_keyword}"
• Example: site:upwork.com/jobs "shopify developer"

Twitter/X (Brand Discovery):

• site:twitter.com OR site:x.com "{d2c_keyword}" "shopify" OR "ecommerce" OR "d2c"
• Also: site:x.com "{industry}" "just launched" OR "coming soon" OR "new store"
• Focus on brand accounts, not agencies

Instagram Brands:

• site:instagram.com "{d2c_keyword}" "shop" OR "store" OR "link in bio"
• Target hashtags: #shopifystore, #d2cbrand, #ecommerce, #shopifyseller
• Extract: profile name, handle, website link from bio

Product Hunt:

• site:producthunt.com "{d2c_keyword}" OR "ecommerce" OR "shopify"
• Focus on recently launched D2C products

Google Maps / Business Directories:

• site:google.com/maps "{industry}" "{market}" + justdial.com (India), yelp.com (US/UK)
• Extract: business name, phone, website

Shopify Store Discovery:

• site:myshopify.com "{industry_keyword}" + site:builtwith.com "shopify" "{industry}"
• Look for stores with basic themes (Dawn, Debut) indicating redesign need

Query generation rules:

• Generate queries to hit daily targets: 20 gig leads + 5 company leads.
• Prioritize platforms with higher platform_weights scores.
• Include market/country filters for geo-targeted segments.
• Allocate queries based on daily targets. Gig platforms need more queries (20 leads vs 5).
• Enforce geo split: 75% of queries must target US/UK/AU/EU markets, 25% India.

Phase 2: Search Execution

Execute searches using WebSearch with rate limiting:

• Max 3 concurrent searches at any time.
• 2-second pause between batches of 3.
• Process results as they return; do not wait for all to complete.

For each search result, extract:

• url -- the source URL
• title -- page title or post title
• snippet -- the text excerpt from the search result
• platform -- which platform (inferred from URL domain)
• posted_date -- if visible in the search result

Phase 3: Signal Validation

For each raw result, validate it is a genuine buying signal:

1. Negative keyword filter: Check title + snippet against icp.negative_keywords. Discard if any match (these are self-promoters, not buyers).

2. Relevance check: The result must contain at least one primary_keyword OR one secondary_keyword AND at least one intent_keyword. If it has only keywords but no intent, mark as LOW confidence.

3. Recency check: Prefer results from the last 7 days. Flag anything older than 30 days as STALE.

4. Duplicate check: Compare URLs against previously returned results in this session. Skip exact URL duplicates. Also skip if the same company/person appears from a different URL (same underlying signal).

5. Lead type classification: Classify each result as either "gig" or "company" based on the source platform. Gig platforms (Freelancer, Upwork, PPH, Guru, Fiverr) = gig lead. Everything else = company lead.

6. Geo classification: Determine the lead's geography. Classify as "international" (US/UK/AU/EU) or "india" based on content, URL, currency, or explicit location mentions.

Phase 4: Entity Extraction

For each validated signal, extract structured data:

{
  "company": "Company name (if identifiable)",
  "website": "Company website (if findable from context)",
  "person": "Name of the person posting/mentioned",
  "title": "Their job title (if available)",
  "url": "Source URL where signal was found",
  "platform": "Reddit | Twitter | LinkedIn | Freelancer | Upwork | etc.",
  "signal_type": "hiring | funding | job_posting | community_question | gig_request | tech_migration | product_launch | brand_discovery | store_discovery",
  "urgency": "HIGH | MEDIUM | LOW",
  "reason": "1-line summary of why this is a signal",
  "country": "Country (if determinable)",
  "posted_date": "ISO date or relative",
  "raw_snippet": "The relevant text excerpt",
  "confidence": "HIGH | MEDIUM | LOW",
  "lead_type": "gig | company",
  "geo_bucket": "international | india",
  "contact_surfaces": {
    "has_email": true,
    "has_linkedin": false,
    "has_instagram": false,
    "has_phone": false,
    "has_website": true,
    "channel_count": 2,
    "discovery_notes": "Email from gig platform. Website from company field."
  }
}

Contact surface defaults by platform:

Platform	email	linkedin	instagram	phone	website
Freelancer/Upwork/PPH/Guru/Fiverr	YES	NO	NO	NO	MAYBE
LinkedIn Posts/Jobs	MAYBE	YES	MAYBE	MAYBE	MAYBE/YES
Reddit	NO	MAYBE	MAYBE	NO	MAYBE
Twitter/X	NO	MAYBE	MAYBE	NO	MAYBE
Instagram Brands	NO	MAYBE	YES	NO	YES
Shopify Community	NO	MAYBE	MAYBE	NO	YES
Funding News	MAYBE	YES	MAYBE	MAYBE	YES
Product Hunt	MAYBE	YES	MAYBE	NO	YES
Google Maps	MAYBE	NO	MAYBE	YES	YES
Shopify Store Discovery	NO	MAYBE	MAYBE	NO	YES

Use these defaults when extracting contact surfaces. Override with actual data when found in the signal content. channel_count = number of YES/MAYBE channels confirmed as available.

Urgency rules:

• HIGH: Explicit hiring/buying language + budget mentioned + recent (< 48h)
• MEDIUM: Intent keywords present + relevant service match + recent (< 7 days)
• LOW: Relevant topic but weak intent signal or older than 7 days

Phase 5: Dedup Against CRM

If crm-writer skill is available and CRM is configured:

1. Read existing leads from the relevant CRM tab (e.g., "Hawk Leads", "Researched Leads").
2. Compare by: company name (fuzzy), URL (exact), person name + company combo.
3. Mark duplicates as "is_duplicate": true but still include them in output with a note.

Phase 6: Review

Present the results to the user, separated by lead type:

Found {N} signals across {M} platforms:

COMPANY LEADS ({count}/5 target):
1. [Platform] Company - "reason" (urgency: HIGH, confidence: HIGH, geo: US)
2. ...

GIG LEADS ({count}/20 target):
1. [Platform] "gig title" - "reason" (urgency: HIGH, budget: $X, geo: UK)
2. ...

GEO SPLIT: {X}% international, {Y}% India (target: 75/25)
Duplicates skipped: {count}
Rejected (self-promoters): {count}

Write directly to CRM (no approval gate).

Phase 7: Log to CRM

Use crm-writer to append new signals to the configured CRM tab. Write one row per signal with columns: Date, Platform, Company, Person, URL, Signal Type, Urgency, Reason, Country, Lead Type, Geo Bucket, Score.

Example Usage

Trigger phrases:

• "Scan for signals"
• "Find buying signals"
• "Run a signal scan"
• "Search for leads showing intent"
• "Find companies looking for Shopify help"

User: Scan for buying signals this week
Assistant: [reads config, generates queries across Reddit/LinkedIn/Freelancer/Upwork/etc., executes with rate limiting, validates and structures results, presents sorted by lead type with geo split]

User: Find signals on Reddit and Shopify Community only
Assistant: [same flow but limited to those 2 platforms]