Lead Scorer
Score and qualify leads using customizable criteria. Prioritize your pipeline by fit, intent, and engagement to focus on deals most likely to close.
About this skill
This AI agent skill acts as a dedicated lead scoring and qualification specialist. It enables users to systematically evaluate potential sales leads by defining and applying custom criteria across three key dimensions: Fit Score (how well they match the Ideal Customer Profile), Intent Score (their readiness to buy), and Engagement Score (their activity level). The skill provides a clear framework for assigning points based on various lead attributes, from company size and industry match to website interactions and email engagement. Beyond just scoring, the skill incorporates robust lead qualification frameworks like BANT (Budget, Authority, Need, Timeline) and advanced MEDDIC principles to ensure a comprehensive assessment of each lead's viability. It then assigns a clear lead grade (A-F) based on the total score, with recommended next actions tailored to each grade, such as 'Hot — contact within 24 hours' or 'Developing — add to email sequence.' A powerful feature is its ability to perform batch scoring, allowing users to input lists of leads and receive a ranked table with detailed scores, grades, and actionable steps for each. This ensures consistent and objective prioritization across an entire pipeline, helping sales and marketing teams focus their efforts efficiently on the most promising opportunities.
Best use case
This skill is primarily designed for sales development representatives (SDRs), business development representatives (BDRs), sales managers, and marketing teams who need to efficiently process, qualify, and prioritize a large volume of leads. It helps them streamline their pipeline management, ensure consistent lead quality, and ultimately increase conversion rates by focusing resources on the most promising opportunities.
Score and qualify leads using customizable criteria. Prioritize your pipeline by fit, intent, and engagement to focus on deals most likely to close.
A clearly ranked and graded list of leads, complete with individual scores, detailed breakdowns, and specific, actionable next steps to optimize sales and marketing efforts.
Practical example
Example input
Please score the following leads and provide next actions: 1. Company: Stellar Solutions, Industry: SaaS, Size: 250, Budget: $100k, Visited Pricing Page: Yes, Requested Demo: Yes, Downloaded Content: Yes, Email Open Rate: 90%, Response Speed: Very Fast, Multiple Stakeholders: Yes. 2. Company: Global Mfg, Industry: Manufacturing, Size: 5000, Budget: $5k, Attended Webinar: No, Asked about Timeline: No, Email Open Rate: 20%, Response Speed: Slow, Social Engagement: Low.
Example output
Lead 1: Stellar Solutions Total Score: 95 (A - Hot) Breakdown: Fit: 38, Intent: 32, Engagement: 25 Next Action: Contact within 24 hours, prioritize for immediate follow-up. Lead 2: Global Mfg Total Score: 30 (D - Cold) Breakdown: Fit: 15, Intent: 5, Engagement: 10 Next Action: Add to a long-term nurture email sequence, re-evaluate in 3-6 months.
When to use this skill
- When managing a large incoming volume of new leads.
- To standardize and objectify your lead qualification process.
- To quickly identify and prioritize high-potential leads for sales outreach.
- For aligning sales and marketing efforts on lead quality and next steps.
When not to use this skill
- For very small, manually manageable lead lists where deep human qualitative analysis is preferred.
- If your lead data is incomplete or highly unreliable, making objective scoring difficult.
- When needing complex, highly customized scoring algorithms that go beyond the defined framework without explicit instruction.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/lead-scorer/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Lead Scorer Compares
| Feature / Agent | Lead Scorer | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | easy | N/A |
Frequently Asked Questions
What does this skill do?
Score and qualify leads using customizable criteria. Prioritize your pipeline by fit, intent, and engagement to focus on deals most likely to close.
How difficult is it to install?
The installation complexity is rated as easy. You can find the installation instructions above.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Lead Scorer You are a lead scoring and qualification specialist. Help users evaluate and prioritize their leads. ## Scoring Framework ### 1. Lead Scoring Model Setup Help users define scoring criteria across three dimensions: **Fit Score (0-40 points)** — How well do they match your ICP? - Company size (0-10) - Industry match (0-10) - Budget range (0-10) - Geography (0-5) - Tech stack compatibility (0-5) **Intent Score (0-35 points)** — How ready are they to buy? - Visited pricing page (10) - Requested demo (10) - Downloaded content (5) - Attended webinar (5) - Asked about timeline (5) **Engagement Score (0-25 points)** — How active are they? - Email open rate (0-10) - Response speed (0-5) - Multiple stakeholders involved (0-5) - Social engagement (0-5) ### 2. Lead Qualification (BANT + MEDDIC) Run leads through: - **Budget**: Can they afford it? - **Authority**: Are you talking to the decision maker? - **Need**: Is the pain real and urgent? - **Timeline**: When do they need a solution? Advanced (MEDDIC): Metrics, Economic buyer, Decision criteria, Decision process, Identify pain, Champion. ### 3. Lead Grading - **A (80-100)**: Hot — contact within 24 hours - **B (60-79)**: Warm — nurture actively, book a call - **C (40-59)**: Developing — add to email sequence - **D (20-39)**: Cold — long-term nurture - **F (0-19)**: Disqualify — don't waste time ### 4. Batch Scoring Accept lists of leads and score them all, outputting a ranked table with scores, grades, and recommended next actions. ## Output Always provide: total score, grade, breakdown by dimension, and specific next action for each lead.
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