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crates/openfang-hands/bundled/lead/SKILL.md
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crates/openfang-hands/bundled/lead/SKILL.md
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---
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name: lead-hand-skill
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version: "1.0.0"
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description: "Expert knowledge for AI lead generation — web research, enrichment, scoring, deduplication, and report generation"
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runtime: prompt_only
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---
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# Lead Generation Expert Knowledge
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## Ideal Customer Profile (ICP) Construction
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A good ICP answers these questions:
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1. **Industry**: What vertical does your ideal customer operate in?
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2. **Company size**: How many employees? What revenue range?
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3. **Geography**: Where are they located?
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4. **Technology**: What tech stack do they use?
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5. **Budget signals**: Are they funded? Growing? Hiring?
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6. **Decision-maker**: Who has buying authority? (title, seniority)
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7. **Pain points**: What problems does your product solve for them?
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### Company Size Categories
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| Category | Employees | Typical Budget | Sales Cycle |
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|----------|-----------|---------------|-------------|
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| Startup | 1-50 | $1K-$25K/yr | 1-4 weeks |
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| SMB | 50-500 | $25K-$250K/yr | 1-3 months |
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| Enterprise | 500+ | $250K+/yr | 3-12 months |
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---
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## Web Research Techniques for Lead Discovery
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### Search Query Patterns
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```
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# Find companies in a vertical
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"[industry] companies" site:crunchbase.com
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"top [industry] startups [year]"
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"[industry] companies [city/region]"
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# Find decision-makers
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"[title]" "[company]" site:linkedin.com
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"[company] team" OR "[company] about us" OR "[company] leadership"
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# Growth signals (high-intent leads)
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"[company] hiring [role]" — indicates budget and growth
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"[company] series [A/B/C]" — recently funded
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"[company] expansion" OR "[company] new office"
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"[company] product launch [year]"
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# Technology signals
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"[company] uses [technology]" OR "[company] built with [technology]"
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site:stackshare.io "[company]"
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site:builtwith.com "[company]"
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```
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### Source Quality Ranking
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1. **Company website** (About/Team pages) — most reliable for personnel
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2. **Crunchbase** — funding, company details, leadership
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3. **LinkedIn** (public profiles) — titles, tenure, connections
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4. **Press releases** — announcements, partnerships, funding
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5. **Job boards** — hiring signals, tech stack requirements
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6. **Industry directories** — comprehensive company lists
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7. **News articles** — recent activity, reputation
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8. **Social media** — engagement, company culture
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---
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## Lead Enrichment Patterns
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### Basic Enrichment (always available)
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- Full name (first + last)
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- Job title
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- Company name
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- Company website URL
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### Standard Enrichment
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- Company employee count (from About page, Crunchbase, or LinkedIn)
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- Company industry classification
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- Company founding year
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- Technology stack (from job postings, StackShare, BuiltWith)
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- Social profiles (LinkedIn URL, Twitter handle)
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- Company description (from meta tags or About page)
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### Deep Enrichment
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- Recent funding rounds (amount, investors, date)
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- Recent news mentions (last 90 days)
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- Key competitors
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- Estimated revenue range
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- Recent job postings (growth signals)
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- Company blog/content activity (engagement level)
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- Executive team changes
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### Email Pattern Discovery
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Common corporate email formats (try in order):
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1. `firstname@company.com` (most common for small companies)
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2. `firstname.lastname@company.com` (most common for larger companies)
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3. `first_initial+lastname@company.com` (e.g., jsmith@)
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4. `firstname+last_initial@company.com` (e.g., johns@)
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Note: NEVER send unsolicited emails. Email patterns are for reference only.
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---
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## Lead Scoring Framework
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### Scoring Rubric (0-100)
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```
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ICP Match (30 points max):
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Industry match: +10
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Company size match: +5
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Geography match: +5
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Role/title match: +10
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Growth Signals (20 points max):
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Recent funding: +8
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Actively hiring: +6
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Product launch: +3
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Press coverage: +3
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Enrichment Quality (20 points max):
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Email found: +5
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LinkedIn found: +5
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Full company data: +5
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Tech stack known: +5
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Recency (15 points max):
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Active this month: +15
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Active this quarter:+10
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Active this year: +5
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No recent activity: +0
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Accessibility (15 points max):
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Direct contact: +15
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Company contact: +10
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Social only: +5
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No contact info: +0
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```
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### Score Interpretation
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| Score | Grade | Action |
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|-------|-------|--------|
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| 80-100 | A | Hot lead — prioritize outreach |
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| 60-79 | B | Warm lead — nurture |
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| 40-59 | C | Cool lead — enrich further |
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| 0-39 | D | Cold lead — deprioritize |
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---
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## Deduplication Strategies
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### Matching Algorithm
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1. **Exact match**: Normalize company name (lowercase, strip Inc/LLC/Ltd) + person name
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2. **Fuzzy match**: Levenshtein distance < 2 on company name + same person
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3. **Domain match**: Same company website domain = same company
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4. **Cross-source merge**: Same person at same company from different sources → merge enrichment data
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### Normalization Rules
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```
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Company name:
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- Strip legal suffixes: Inc, LLC, Ltd, Corp, Co, GmbH, AG, SA
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- Lowercase
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- Remove "The" prefix
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- Collapse whitespace
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Person name:
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- Lowercase
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- Remove middle names/initials
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- Handle "Bob" = "Robert", "Mike" = "Michael" (common nicknames)
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```
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---
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## Output Format Templates
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### CSV Format
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```csv
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Name,Title,Company,Company URL,LinkedIn,Industry,Size,Score,Discovered,Notes
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"Jane Smith","VP Engineering","Acme Corp","https://acme.com","https://linkedin.com/in/janesmith","SaaS","SMB (120 employees)",85,"2025-01-15","Series B funded, hiring 5 engineers"
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```
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### JSON Format
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```json
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[
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{
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"name": "Jane Smith",
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"title": "VP Engineering",
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"company": "Acme Corp",
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"company_url": "https://acme.com",
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"linkedin": "https://linkedin.com/in/janesmith",
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"industry": "SaaS",
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"company_size": "SMB",
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"employee_count": 120,
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"score": 85,
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"discovered": "2025-01-15",
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"enrichment": {
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"funding": "Series B, $15M",
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"hiring": true,
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"tech_stack": ["React", "Python", "AWS"],
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"recent_news": "Launched enterprise plan Q4 2024"
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},
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"notes": "Strong ICP match, actively growing"
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}
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]
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```
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### Markdown Table Format
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```markdown
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| # | Name | Title | Company | Score | Key Signal |
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|---|------|-------|---------|-------|------------|
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| 1 | Jane Smith | VP Engineering | Acme Corp | 85 | Series B funded, hiring |
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| 2 | John Doe | CTO | Beta Inc | 72 | Product launch Q1 2025 |
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```
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---
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## Compliance & Ethics
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### DO
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- Use only publicly available information
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- Respect robots.txt and rate limits
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- Include data provenance (where each piece of info came from)
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- Allow users to export and delete their lead data
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- Clearly mark confidence levels on enriched data
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### DO NOT
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- Scrape behind login walls or paywalls
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- Fabricate any lead data (even "likely" email addresses without evidence)
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- Store sensitive personal data (SSN, financial info, health data)
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- Send unsolicited communications on behalf of the user
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- Bypass anti-scraping measures (CAPTCHAs, rate limits)
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- Collect data on individuals who have opted out of data collection
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### Data Retention
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- Keep lead data in local files only — never exfiltrate
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- Mark stale leads (>90 days without activity) for review
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- Provide clear data export in all supported formats
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