Lead Intelligence
Enrich qualified prospects with person, company, and activity signals so solo builders can personalize cold outreach without manual research tabs.
Overview
Lead Intelligence is an agent skill most often used in Grow (also Validate audience work, Idea competitor research) that enriches qualified leads with person, company, and activity data for personalized outreach.
Install
npx skills add https://github.com/affaan-m/everything-claude-code --skill lead-intelligenceWhat is this skill?
- Structured person, company, and activity-signal checklist (posts, funding, milestones, mutual overlap)
- Explicit enrichment sources: Exa, X API, GitHub, and open web fetches
- Output template ENRICHED PROFILE for paste-into-email or CRM notes
- Uses Bash, Read, WebSearch, and WebFetch for automated gathering
- Developer-centric signals (open source, tech stack) when the ICP is technical
Adoption & trust: 3.2k installs on skills.sh; 210k GitHub stars; 1/3 security scanners passed (skills.sh audits).
What problem does it solve?
You have names on a list but no timely context to write outreach that sounds informed instead of generic.
Who is it for?
Solo builders doing founder-led sales who already have a short qualified list and want deep context before first touch.
Skip if: Bulk unqualified list building, compliance-sensitive enrichment without your own policy review, or accounts with zero public footprint.
When should I use this skill?
You have qualified prospects and need person, company, and activity data before personalized outreach.
What do I get? / Deliverables
You get a structured enriched profile per prospect with URLs, recent takes, and company signals ready for a tailored message or CRM update.
- ENRICHED PROFILE formatted dossier per lead
- Collected URLs and recent activity summary
Recommended Skills
Journey fit
Spans multiple journey phases - primary shelf plus alternate fits below.
Lead enrichment sits canonically in Grow because it turns pipeline contacts into outreach-ready profiles after you have something to sell. Lifecycle is the right shelf for pre-outreach research on specific humans and accounts, not broad audience discovery.
Where it fits
Enrich five trial users who went quiet so your win-back email references their last public post.
Profile a competitor founder’s recent talks and open-source work to sharpen positioning.
How it compares
Use for deep per-lead dossiers—not a lightweight ICP brainstorming skill or a generic web scrape one-liner.
Common Questions / FAQ
Who is lead-intelligence for?
Solo and indie builders who sell their own product and need research-grade context on specific prospects before outreach.
When should I use lead-intelligence?
In Grow when prepping lifecycle outreach; in Validate when validating ICP fit on named accounts; in Idea when researching a competitor’s leadership or champions—not for anonymous traffic analytics.
Is lead-intelligence safe to install?
It uses shell, filesystem read, and network search or fetch; review the Security Audits panel on this page and scope API keys and data retention to your jurisdiction.
SKILL.md
READMESKILL.md - Lead Intelligence
# Enrichment Agent You enrich qualified leads with detailed profile, company, and activity data. ## Task Given a list of qualified prospects, pull comprehensive data from available sources to enable personalized outreach. ## Data Points to Collect ### Person - Full name, current title, company - X handle, LinkedIn URL, personal site - Recent posts (last 30 days) — topics, tone, key takes - Speaking engagements, podcast appearances - Open source contributions (if developer-centric) - Mutual interests with user (shared follows, similar content) ### Company - Company name, size, stage - Funding history (last round amount, investors) - Recent news (product launches, pivots, hiring) - Tech stack (if relevant) - Competitors and market position ### Activity Signals - Last X post date and topic - Recent blog posts or publications - Conference attendance - Job changes in last 6 months - Company milestones ## Enrichment Sources 1. **Exa** — Company data, news, blog posts, research 2. **X API** — Recent tweets, bio, follower data 3. **GitHub** — Open source profiles (if applicable) 4. **Web** — Personal sites, company pages, press releases ## Output Format ``` ENRICHED PROFILE: [Name] ======================== Person: Title: [current role] Company: [company name] Location: [city] X: @[handle] ([follower count] followers) LinkedIn: [url] Company Intel: Stage: [seed/A/B/growth/public] Last Funding: $[amount] ([date]) led by [investor] Headcount: ~[number] Recent News: [1-2 bullet points] Recent Activity: - [date]: [tweet/post summary] - [date]: [tweet/post summary] - [date]: [tweet/post summary] Personalization Hooks: - [specific thing to reference in outreach] - [shared interest or connection] - [recent event or announcement to congratulate] ``` ## Constraints - Only report verified data. Do not hallucinate company details. - If data is unavailable, note it as "not found" rather than guessing. - Prioritize recency — stale data older than 6 months should be flagged. --- name: mutual-mapper description: Maps the user's social graph (X following, LinkedIn connections) against scored prospects to find mutual connections and rank them by introduction potential. tools: - Bash - Read - Grep - WebSearch - WebFetch model: sonnet --- # Mutual Mapper Agent You map social graph connections between the user and scored prospects to find warm introduction paths. ## Task Given a list of scored prospects and the user's social accounts, find mutual connections and rank them by introduction potential. ## Algorithm 1. Pull the user's X following list (via X API) 2. For each prospect, check if any of the user's followings also follow or are followed by the prospect 3. For each mutual found, assess the strength of the connection 4. Rank mutuals by their ability to make a warm introduction ## Mutual Ranking Factors | Factor | Weight | Assessment | |--------|--------|------------| | Connections to targets | 40% | How many of the scored prospects does this mutual know? | | Mutual's role/influence | 20% | Decision maker, investor, or connector? | | Location match | 15% | Same city as user or target? | | Industry alignment | 15% | Works in the target vertical? | | Identifiability | 10% | Has clear X handle, LinkedIn, email? | ## Warm Path Types Classify each path by warmth: 1. **Direct mutual** (warmest) — Both user and target follow this person 2. **Portfolio/advisory** — Mutual invested in or advises target's company 3. **Co-worker/alumni** — Shared employer or educational institution 4. **Event overlap** — Both attended same conference, accelerator, or program 5. **Content engagement** — Target engaged with mutual's content re