Identifies high-quality leads for your product or service by analyzing your business, searching for target companies, and providing actionable contact strategies. Perfect for sales, business development, and marketing professionals.
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This skill helps you identify and qualify potential leads for your business by analyzing your product/service, understanding your ideal customer profile, and providing actionable outreach strategies.
Simply describe your product/service and what you're looking for:
I'm building [product description]. Find me 10 companies in [location/industry]
that would be good leads for this.
For even better results, run this from your product's source code directory:
Look at what I'm building in this repository and identify the top 10 companies
in [location/industry] that would benefit from this product.
For more targeted research:
My product: [description]
Ideal customer profile:
- Industry: [industry]
- Company size: [size range]
- Location: [location]
- Current pain points: [pain points]
- Technologies they use: [tech stack]
Find me 20 qualified leads with contact strategies for each.
When a user requests lead research:
Understand the Product/Service
Define Ideal Customer Profile
Research and Identify Leads
Prioritize and Score
Provide Actionable Output
For each lead, provide:
Format the Output
Present results in a clear, scannable format:
# Lead Research Results
## Summary
- Total leads found: [X]
- High priority (8-10): [X]
- Medium priority (5-7): [X]
- Average fit score: [X]
---
## Lead 1: [Company Name]
**Website**: [URL]
**Priority Score**: [X/10]
**Industry**: [Industry]
**Size**: [Employee count/revenue range]
**Why They're a Good Fit**:
[2-3 specific reasons based on their business]
**Target Decision Maker**: [Role/Title]
**LinkedIn**: [URL if available]
**Value Proposition for Them**:
[Specific benefit for this company]
**Outreach Strategy**:
[Personalized approach - mention specific pain points, recent company news, or relevant context]
**Conversation Starters**:
- [Specific point 1]
- [Specific point 2]
---
[Repeat for each lead]
Offer Next Steps
User: "I'm building a tool that masks sensitive data in AI coding assistant queries. Find potential leads."
Output: Creates a prioritized list of companies that:
User: "I run a consulting practice for remote team productivity. Find me 10 companies in the Bay Area that recently went remote."
Output: Identifies companies that:
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Testing patterns for PHPUnit and Playwright E2E tests. Use when writing tests, debugging test failures, setting up test coverage, or implementing test patterns for ActivityPub features.
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Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
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Add unsigned integer (uint) type support to PyTorch operators by updating AT_DISPATCH macros. Use when adding support for uint16, uint32, uint64 types to operators, kernels, or when user mentions enabling unsigned types, barebones unsigned types, or uint support.
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This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.
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Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
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Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
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