Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · Developer Tools
Lead Enrichment
Turn a name into a full dossier in seconds. Feed in a name + company (or email, or LinkedIn URL) and get back a rich profile with social links, bio, company intel, recent activity, and personalized talking points. Aggregates data from multiple public sources — LinkedIn, Twitter, GitHub, company websites, news — so you can skip the manual research and jump straight to personalized outreach. Your agent does the detective work while you close deals. Supports single enrichment, batch processing, and multiple output formats (JSON, Markdown, CRM-ready). Use when researching prospects, preparing for sales calls, personalizing cold outreach, or building lead lists. Pairs perfectly with trawl for autonomous lead gen → enrichment → outreach pipelines.
skill openclawclawhub Free
Turn a name into a full dossier in seconds. Feed in a name + company (or email, or LinkedIn URL) and get back a rich profile with social links, bio, company intel, recent activity, and personalized talking points. Aggregates data from multiple public sources — LinkedIn, Twitter, GitHub, company websites, news — so you can skip the manual research and jump straight to personalized outreach. Your agent does the detective work while you close deals. Supports single enrichment, batch processing, and multiple output formats (JSON, Markdown, CRM-ready). Use when researching prospects, preparing for sales calls, personalizing cold outreach, or building lead lists. Pairs perfectly with trawl for autonomous lead gen → enrichment → outreach pipelines.
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, config.example.json, scripts/batch.sh, scripts/enrich.sh, scripts/export.sh, scripts/setup.sh
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.1.0
Provenance
- Publisher
- audsmith28
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Lead Enrichment — Research Prospects in Seconds
Stop spending hours stalking LinkedIn. Let your agent do it. Sales teams waste 6+ hours per week manually researching prospects. You Google their name, check LinkedIn, scroll their Twitter, hunt for their email, read their company's About page, search for recent news... and then do it all over again for the next lead. Lead Enrichment automates all of it. Give your agent a name and company (or email, or LinkedIn URL), and get back a complete dossier: contact info, social profiles, bio, company intel, recent posts, news mentions, and AI-generated talking points. The pain: Generic outreach gets ignored. Personalization takes forever. You're always behind quota. The fix: Your agent researches 10 leads while you grab coffee. Rich profiles ready when you need them. Spend your time selling, not searching.
What You Get
For each lead, the enrichment pulls: Personal Profile: Full name, current title, company Professional bio/summary Profile photo URL Location Social media handles (LinkedIn, Twitter, GitHub, personal site) Contact Discovery: Likely email addresses (pattern-based + verification attempts) Public phone numbers (if available) Best channels for outreach Company Context: Company description, industry, size Funding stage, recent news Tech stack (for technical sales) Key decision makers Intelligence & Timing: Recent posts/articles (last 30 days) Job change signals Company news mentions Shared connections or interests Conference/event participation AI-Generated Talking Points: 3-5 personalized hooks based on their recent activity Common ground opportunities Relevant pain points to address Recommended opening lines
Setup
Run scripts/setup.sh to initialize config Edit ~/.config/lead-enrichment/config.json with preferences No API keys required for basic enrichment (uses public sources) Optional: Add premium data sources (see config)
Scripts
ScriptPurposescripts/setup.shInitialize config and data directoriesscripts/enrich.shEnrich a single lead (main script)scripts/batch.shProcess multiple leads from CSV/JSONscripts/export.shExport enriched leads (JSON/MD/CSV)
Single Lead
# By name + company ./scripts/enrich.sh --name "Sarah Chen" --company "Acme Corp" # By email ./scripts/enrich.sh --email "sarah@acmecorp.com" # By LinkedIn URL ./scripts/enrich.sh --linkedin "https://linkedin.com/in/sarahchen" # Output to file ./scripts/enrich.sh --name "Sarah Chen" --company "Acme Corp" --output sarah-chen.json # With talking points ./scripts/enrich.sh --name "Sarah Chen" --company "Acme Corp" --talking-points
Batch Processing
# From CSV (columns: name, company, email, linkedin_url) ./scripts/batch.sh --input leads.csv --output enriched/ # From JSON array ./scripts/batch.sh --input leads.json --output enriched/ # Process with concurrency ./scripts/batch.sh --input leads.csv --parallel 3
Export Formats
# Export as JSON (default) ./scripts/export.sh --format json enriched/*.json > leads.json # Export as Markdown (readable) ./scripts/export.sh --format markdown enriched/*.json > leads.md # Export as CSV (CRM import) ./scripts/export.sh --format csv enriched/*.json > leads.csv # Pipe to your CRM ./scripts/export.sh --format json enriched/*.json | \ curl -X POST https://your-crm.com/api/leads -d @-
Config
Config lives at ~/.config/lead-enrichment/config.json. See config.example.json for full schema. Key sections: enrichment.sources — Which data sources to check (all public by default): linkedin — Public profiles via search twitter — Social activity and bio github — For technical leads company_website — About pages, team directories news — Recent mentions crunchbase — Company funding (public data) enrichment.depth — How thorough to be: quick — Basic profile only (name, title, LinkedIn, company) standard — Above + social profiles + recent activity (default) deep — Above + news mentions + talking points + shared connections output.format — Default output format (json/markdown/csv) output.include — What to include in output: contact_info — Email attempts, phone social_profiles — All discovered links recent_activity — Posts, articles (last 30 days) company_intel — Company description, size, funding talking_points — AI-generated personalization hooks raw_sources — Source URLs for verification talking_points.enabled — Generate AI talking points (requires Claude) talking_points.style — Tone for suggestions (professional/friendly/bold) privacy.respect_robots — Skip profiles with clear "no scraping" signals privacy.store_locally — Cache enriched profiles (default: true)
Data Sources
All sources are public and free: LinkedIn — Public profiles via search (no API, respects robots.txt) Twitter/X — Bio, recent tweets, follower count GitHub — For technical roles (repos, activity, README) Company websites — Team pages, About sections Google News — Recent mentions Crunchbase — Public company data (no API key needed for basic info) Common email patterns — firstname@company.com, f.lastname@company.com, etc. Premium sources (optional, requires API keys): Hunter.io — Email verification Clearbit — Enhanced company data Apollo — Direct contact info Add API keys to ~/.clawdbot/secrets.env if you have them. Enrichment works fine without them.
Output Schema
Each enriched lead is saved as JSON: { "lead_id": "sarah-chen-acme-corp", "enriched_at": "2025-01-29T10:30:00Z", "input": { "name": "Sarah Chen", "company": "Acme Corp" }, "profile": { "full_name": "Sarah Chen", "title": "VP of Engineering", "company": "Acme Corp", "location": "San Francisco, CA", "bio": "Building the future of...", "photo_url": "https://...", "social_profiles": { "linkedin": "https://linkedin.com/in/sarahchen", "twitter": "https://twitter.com/sarahchen", "github": "https://github.com/sarahchen", "personal_site": "https://sarahchen.com" } }, "contact": { "emails": [ { "address": "sarah@acmecorp.com", "confidence": 0.85, "verified": false }, { "address": "s.chen@acmecorp.com", "confidence": 0.60, "verified": false } ], "phones": [], "preferred_channel": "email" }, "company": { "name": "Acme Corp", "domain": "acmecorp.com", "industry": "SaaS", "size": "51-200 employees", "description": "AI-powered...", "funding": "Series B ($25M)", "tech_stack": ["React", "Node.js", "AWS"], "recent_news": [ { "title": "Acme Corp raises $25M...", "url": "https://...", "date": "2025-01-15" } ] }, "intelligence": { "recent_activity": [ { "type": "twitter_post", "content": "Excited to announce...", "url": "https://...", "date": "2025-01-20" } ], "job_change_signal": false, "shared_connections": [], "interests": ["AI", "startups", "engineering leadership"] }, "talking_points": [ "Reference their recent Series B — congrats and ask about growth plans", "Mention mutual interest in AI/ML engineering", "Their tech stack (React/Node) aligns with your solution" ], "sources": [ "https://linkedin.com/in/sarahchen", "https://twitter.com/sarahchen", "https://acmecorp.com/about" ], "confidence_score": 0.88 }
Integration with Trawl
Lead Enrichment pairs perfectly with Trawl (autonomous lead gen): # Trawl finds leads, enrichment researches them trawl sweep.sh # Discover leads trawl leads.sh list --json | # Export qualified leads jq -r '.[] | "\(.name)|\(.company)"' | while IFS='|' read name company; do ./enrich.sh --name "$name" --company "$company" done # Or automate it via config: # trawl config: "post_qualify_action": "enrich"
Tips
Email Discovery: Works best when you provide company domain Tries common patterns (first@company, f.last@company, etc.) Marks confidence level (high/medium/low) Does NOT spam or verify via email sends (respects privacy) Talking Points: Most valuable when enrichment depth = "deep" Requires recent activity data (posts, news) AI analyzes content for personalization hooks Style can be professional, friendly, or bold Batch Processing: Use --parallel for speed (3-5 concurrent recommended) Progress saved (resume if interrupted) Failed leads logged to batch-errors.json Data Freshness: Cached profiles expire after 30 days Force refresh with --refresh flag Social activity always fetched fresh
Use Cases
Sales Reps: Research prospects before calls Personalize cold email sequences Find mutual connections or interests Recruiters: Assess candidate backgrounds Find contact info for passive candidates Check GitHub activity for technical roles Partnerships: Research potential partners Understand company context Find the right contact person Investors: Quick founder background checks Company traction signals Network mapping
Privacy & Ethics
This skill only uses publicly available data. It: Respects robots.txt and rate limits Does NOT scrape private profiles or paywalled content Does NOT send verification emails (won't spam your leads) Does NOT store data if privacy.store_locally = false Provides source URLs for transparency Be a human: Just because you CAN enrich someone doesn't mean you should spam them. Use this for genuine, personalized outreach.
Data Storage
Enriched leads are stored at ~/.config/lead-enrichment/data/leads/: ~/.config/lead-enrichment/ ├── config.json # User configuration ├── data/ │ ├── leads/ # Enriched profiles (one file per lead) │ │ ├── sarah-chen-acme.json │ │ └── john-smith-techco.json │ ├── cache/ # Temporary data (30-day expiry) │ └── batch-runs/ # Batch processing logs └── exports/ # Generated exports
FAQ
Q: Is this legal? A: Yes. All data is publicly available. We respect robots.txt and rate limits. Q: How accurate are the emails? A: Pattern-based = 60-80% accuracy. Verified (if you add Hunter.io key) = 95%+. Q: Can I enrich 1000 leads? A: Yes via batch.sh. Expect ~30 sec per lead (deep mode). That's 8 hours for 1000. Run overnight. Q: Does this work for non-US leads? A: Yes. LinkedIn and Twitter are global. Some data sources are US-biased. Q: Will this get me blocked by LinkedIn? A: No. We use search (public), not scraping. Rate-limited and respectful.
What's Next
Ideas for future versions: Chrome extension (enrich while browsing LinkedIn) CRM integrations (auto-enrich on lead create) Slack bot (enrich on-demand from Slack) Email warmup integration (find + verify + warm sequence) Mutual connection finder (via agent networks) Real-time alerts (when a lead changes jobs) Stop researching. Start selling. Feed your agent a list of names. Get back a stack of dossiers. Personalize every message. Close more deals. That's Lead Enrichment.
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
4 Scripts1 Docs1 Config
- SKILL.md
- scripts/batch.sh
- scripts/enrich.sh
- scripts/export.sh
- scripts/setup.sh
- config.example.json