Search

PythonReactSEOPDF
OpenClaw

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.

1kalin0 source installs☆ 0 Repository stars

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

SkillHub CLI

skillhub install 1kalin/lead-scorer

Inspect the source and compatibility requirements, then follow its installation steps.

Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.

View source ↗Guides

Skill instructions

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.

Source information

Source
github
Repository
openclaw/skills
Path
skills/1kalin/lead-scorer
Version
—
Commit
7ac77ebbdafd24c4e4279cf1a59c3a510f343992
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

README

Lead Scorer

Stop treating all leads equally. Score them on fit, intent, and engagement — then focus your energy where it counts.

What It Does

  • Custom scoring models — weighted criteria across fit, intent, and engagement (0-100 scale)
  • BANT + MEDDIC qualification — structured frameworks to qualify or disqualify fast
  • Lead grading — A/B/C/D/F with specific next actions for each grade
  • Batch scoring — paste a list of leads, get a ranked priority table
  • ICP matching — score against your ideal customer profile

Example Usage

"Set up a lead scoring model for my B2B SaaS — we sell to mid-market HR teams"

"Score this lead: Series B fintech, 200 employees, visited pricing page twice, CEO replied to email"

"Here are 15 leads from this week — rank them for me"

"Qualify this lead using MEDDIC"

Who It's For

Sales reps, SDRs, founders, anyone with more leads than time. Stop guessing which deals to chase — let the score decide.


For industry-specific context, check out our packs at https://afrexai-cto.github.io/context-packs/ — $47/vertical

Extracted content

SKILL.md
# 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.
README
# Lead Scorer

Stop treating all leads equally. Score them on fit, intent, and engagement — then focus your energy where it counts.

## What It Does

- **Custom scoring models** — weighted criteria across fit, intent, and engagement (0-100 scale)
- **BANT + MEDDIC qualification** — structured frameworks to qualify or disqualify fast
- **Lead grading** — A/B/C/D/F with specific next actions for each grade
- **Batch scoring** — paste a list of leads, get a ranked priority table
- **ICP matching** — score against your ideal customer profile

## Example Usage

> "Set up a lead scoring model for my B2B SaaS — we sell to mid-market HR teams"

> "Score this lead: Series B fintech, 200 employees, visited pricing page twice, CEO replied to email"

> "Here are 15 leads from this week — rank them for me"

> "Qualify this lead using MEDDIC"

## Who It's For

Sales reps, SDRs, founders, anyone with more leads than time. Stop guessing which deals to chase — let the score decide.

---

For industry-specific context, check out our packs at https://afrexai-cto.github.io/context-packs/ — $47/vertical

Related skills

OpenClaw

bambu-studio-ai

heyixuan2

Bambu Lab 3D printer control and automation. Activate when user mentions: printer status, 3D printing, slice, analyze model, generate 3D, AMS filament, print monitor, Bambu Lab, or any 3D printing task. Full pi...

OpenClaw

geo-optimization

capt-marbles

Generative Engine Optimization (GEO) for AI search visibility. Optimize content to appear in ChatGPT, Perplexity, Claude, and Google AI Overviews. Use when optimizing websites, pages, or content for LLM discove...

OpenClaw

parakeet-stt

carlulsoe

Local speech-to-text with NVIDIA Parakeet TDT 0.6B v3 (ONNX on CPU). 30x faster than Whisper, 25 languages, auto-detection, OpenAI-compatible API. Use when transcribing audio files, converting speech to text, o...

OpenClaw

feishu-process-feedback

carlzhao007

飞书消息自动处理与进度反馈技能。安装后后台运行,监听飞书任务消息并自动创建独立进程处理。 在处理前后发送实时进度反馈(任务确认、进度百分比、完成通知)。 支持任务类型识别、智能解析、错误重试、并发控制、状态持久化...