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Lead Research Assistant

CommunityPopular
Prat011
lead-research-assistant

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.

Overview

PublisherPrat011
Repositoryawesome-llm-skills
Skill namelead-research-assistant
Stars
1.7K
Forks
303
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Prat011 on GitHub. Read the source before you install it.

Installation

Install the Lead Research Assistant AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Prat011/awesome-llm-skills.git /tmp/awesome-llm-skills
mkdir -p .claude/skills
cp -r /tmp/awesome-llm-skills/lead-research-assistant .claude/skills/lead-research-assistant
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Lead Research Assistant in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Lead Research Assistant on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Lead Research Assistant is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Lead Research Assistant

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.

When to Use This Skill

  • Finding potential customers or clients for your product/service
  • Building a list of companies to reach out to for partnerships
  • Identifying target accounts for sales outreach
  • Researching companies that match your ideal customer profile
  • Preparing for business development activities

What This Skill Does

  1. Understands Your Business: Analyzes your product/service, value proposition, and target market
  2. Identifies Target Companies: Finds companies that match your ideal customer profile based on:
    • Industry and sector
    • Company size and location
    • Technology stack and tools they use
    • Growth stage and funding
    • Pain points your product solves
  3. Prioritizes Leads: Ranks companies based on fit score and relevance
  4. Provides Contact Strategies: Suggests how to approach each lead with personalized messaging
  5. Enriches Data: Gathers relevant information about decision-makers and company context

How to Use

Basic Usage

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.

With Your Codebase

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.

Advanced Usage

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.

Instructions

When a user requests lead research:

  1. Understand the Product/Service

    • If in a code directory, analyze the codebase to understand the product
    • Ask clarifying questions about the value proposition
    • Identify key features and benefits
    • Understand what problems it solves
  2. Define Ideal Customer Profile

    • Determine target industries and sectors
    • Identify company size ranges
    • Consider geographic preferences
    • Understand relevant pain points
    • Note any technology requirements
  3. Research and Identify Leads

    • Search for companies matching the criteria
    • Look for signals of need (job postings, tech stack, recent news)
    • Consider growth indicators (funding, expansion, hiring)
    • Identify companies with complementary products/services
    • Check for budget indicators
  4. Prioritize and Score

    • Create a fit score (1-10) for each lead
    • Consider factors like:
      • Alignment with ICP
      • Signals of immediate need
      • Budget availability
      • Competitive landscape
      • Timing indicators
  5. Provide Actionable Output

    For each lead, provide:

    • Company Name and website
    • Why They're a Good Fit: Specific reasons based on their business
    • Priority Score: 1-10 with explanation
    • Decision Maker: Role/title to target (e.g., "VP of Engineering")
    • Contact Strategy: Personalized approach suggestions
    • Value Proposition: How your product solves their specific problem
    • Conversation Starters: Specific points to mention in outreach
    • LinkedIn URL: If available, for easy connection
  6. Format the Output

    Present results in a clear, scannable format:

    markdown
    # 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]
  7. Offer Next Steps

    • Suggest saving results to a CSV for CRM import
    • Offer to draft personalized outreach messages
    • Recommend prioritization based on timing
    • Suggest follow-up research for top leads

Examples

Example 1: From Lenny's Newsletter

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:

  • Use AI coding assistants (Copilot, Cursor, etc.)
  • Handle sensitive data (fintech, healthcare, legal)
  • Have evidence in their GitHub repos of using coding agents
  • May have accidentally exposed sensitive data in code
  • Includes LinkedIn URLs of relevant decision-makers

Example 2: Local Business

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:

  • Recently posted remote job listings
  • Announced remote-first policies
  • Are hiring distributed teams
  • Show signs of remote work challenges
  • Provides personalized outreach strategies for each

Tips for Best Results

  • Be specific about your product and its unique value
  • Run from your codebase if applicable for automatic context
  • Provide context about your ideal customer profile
  • Specify constraints like industry, location, or company size
  • Request follow-up research on promising leads for deeper insights

Related Use Cases

  • Drafting personalized outreach emails after identifying leads
  • Building a CRM-ready CSV of qualified prospects
  • Researching specific companies in detail
  • Analyzing competitor customer bases
  • Identifying partnership opportunities

Frequently asked questions

What does the Lead Research Assistant AI skill do?

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.

Why use Lead Research Assistant on TypingMind?

Because you install it once and use it with any model. Lead Research Assistant is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Lead Research Assistant in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Prat011/awesome-llm-skills/tree/master/lead-research-assistant. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Lead Research Assistant?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Lead Research Assistant?

As many as you like. As long as a model supports skills, you can use Lead Research Assistant with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Lead Research Assistant AI skill free?

It is published on GitHub by Prat011. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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