Skill: ipythoning/sdr-lead-discovery (version 1.2.0)

--- name: lead-discovery description: "AI-driven lead discovery for B2B export. Searches web for potential buyers matching ICP, evaluates fit, and creates CRM records for follow-up." --- # Lead Discovery — AI-Powered Prospecting Automatically search, filter, and evaluate potential buyers based on your ICP profile. ## Triggers - Cron scheduled execution (Daily 10:00) - Manual command from owner: "Search for leads in [market/industry]" ## Search Strategy ### Search Dimensions (rotate daily, pick 1-2) 1. **Target Market Procurement** - "{{product}} buyers [target country] 2026" - "[target country] fleet expansion logistics company" - "[target country] construction equipment procurement" 2. **Trade Shows & Procurement Signals** - "{{product}} buyers exhibition Africa Middle East 2026" - "transport logistics tender [region]" 3. **Company Research (read website)** - After discovering a target company, read their website for detailed info 4. **Customs / Trade Data** - "[target country] {{product}} import statistics" - "{{product}} import demand [region] 2026" ## Search Execution ### Jina Search (find potential buyers) ```bash curl -s 'https://s.jina.ai/QUERY_URL_ENCODED' \ -H 'Authorization: Bearer $JINA_API_KEY' \ -H 'Accept: application/json' ``` ### Jina Reader (read company website) ```bash curl -s 'https://r.jina.ai/https://target-company.com' \ -H 'Authorization: Bearer $JINA_API_KEY' \ -H 'Accept: application/json' ``` JINA_API_KEY in .secrets/env. Get one free at https://jina.ai/ ## 3-Layer Enrichment Pipeline ### Layer 1: Website Extraction Read company website via Jina Reader → extract: - Company size, employee count - Product lines, services - Certifications (ISO, etc.) - Contact info (email, phone, WhatsApp) - Office/warehouse locations ### Layer 2: Purchase Signal Search Jina Search for: - "[company name] procurement tender" - "[company name] fleet expansion" - "[company name] import export" ### Layer 3: Information Integration - Combine all findings into enrichment profile - Calculate ICP score based on USER.md criteria - Store research notes in Supermemory with tag "customer_research" ## Evaluation Flow For each discovered prospect: 1. Extract: company name, country, industry, size, contact info (email/WhatsApp/phone) 2. Read company website via Jina Reader for deep understanding 3. Score per USER.md ICP criteria (1-10) 4. ICP >= 5: Write to CRM (source=`web_discovery`, status=`new`) 5. ICP >= 7: Also mark as hot_lead, create research note 6. Email found: Mark next_action=`email_outreach` 7. WhatsApp found: Mark next_action=`whatsapp_outreach` ## Output Format (report to owner) ``` Today discovered X potential leads: 1. [Company] - [Country] - ICP [X]/10 Industry: [industry] | Size: [size] Source: [search query] Contact: [email/website/whatsapp] Recommendation: [Send cold email / WhatsApp contact / More research / Enter nurture pool] Added to CRM: X | Pending email outreach: X | Pending WhatsApp: X ``` ## Search Frequency & Quota - Max 20 searches per day (API quota management) - Weekly coverage: Africa 2 days, Middle East 2 days, SEA 1 day, LatAm 1 day, Other 1 day - Duplicate companies auto-skipped (check CRM first) ## Search Templates by Market ### Africa (Mon/Tue) - "{{product}} importers Nigeria Lagos" - "logistics company Tanzania fleet" - "construction company Kenya equipment procurement" ### Middle East (Wed/Thu) - "{{product}} dealers Saudi Arabia" - "logistics fleet UAE Dubai" - "construction equipment Oman transport" ### Southeast Asia (Fri) - "{{product}} importers Philippines Manila" - "logistics company Vietnam fleet" - "construction Indonesia heavy vehicles" ### Latin America (Sat) - "{{product}} importers Brazil" - "logistics company Chile fleet" - "mining transport vehicles Peru"


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)