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1kalin

Lead Scorer

by 1kalin · GitHub ↗ · v1.0.0
cross-platform ✓ Security Clean
1625
Downloads
1
Stars
4
Active Installs
1
Versions
Install in OpenClaw
/install lead-scorer
Description
Score and qualify leads using customizable criteria. Prioritize your pipeline by fit, intent, and engagement to focus on deals most likely to close.
README (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.

Usage Guidance
This skill is instruction-only and appears coherent with its stated purpose. Before using it, avoid pasting sensitive personally identifiable information or confidential account data into chat (use anonymized or synthetic examples if needed). The README references an external paid resource URL — review that site separately if you plan to follow up. If you need automated integration with your CRM, expect to supply explicit connectors or credentials (this skill does not provide them). Otherwise it's safe to try for manual/batch scoring workflows.
Capability Analysis
Type: OpenClaw Skill Name: lead-scorer Version: 1.0.0 The skill bundle appears benign. All files, including `_meta.json`, `SKILL.md`, and `README.md`, align with the stated purpose of a 'Lead Scorer'. The `SKILL.md` provides clear, task-specific instructions for the AI agent without any evidence of prompt injection attempts, unauthorized actions, or data access. The `README.md` contains a promotional link to an external GitHub Pages site, but this is a passive link in documentation and not an active component or dependency leveraged by the skill's execution logic, thus posing no direct security risk within the skill itself.
Capability Assessment
✓ Purpose & Capability
Name, description, README and SKILL.md all describe lead scoring, grading, and batch scoring. There are no unexpected required binaries, env vars, or credentials; the declared purpose matches what the skill asks the agent to do.
✓ Instruction Scope
SKILL.md defines scoring criteria, qualification frameworks (BANT/MEDDIC), and expected outputs. It does not instruct the agent to read arbitrary files, access environment variables, or call external endpoints. Batch scoring implies the user will provide lead data (paste/upload) — the skill stays within that scope.
✓ Install Mechanism
No install spec and no code files. This is the lowest-risk model: nothing is written to disk or fetched at install time.
✓ Credentials
The skill declares no environment variables, credentials, or config paths. There is nothing disproportionate or unexplained for a lead-scoring helper.
✓ Persistence & Privilege
always is false and there are no indications the skill requests persistent system privileges or modifies other skills. Autonomous invocation is allowed by platform default but is not combined with any broad privileges here.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install lead-scorer
  3. After installation, invoke the skill by name or use /lead-scorer
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Lead Scorer 1.0.0 – Initial release - Launches Lead Scorer for evaluating and prioritizing sales leads. - Introduces a scoring framework across Fit, Intent, and Engagement dimensions. - Supports lead qualification using both BANT and MEDDIC methodologies. - Provides lead grading system (A–F) with actionable next steps. - Enables batch scoring and ranking of multiple leads with detailed output for each.
Metadata
Slug lead-scorer
Version 1.0.0
License —
All-time Installs 4
Active Installs 4
Total Versions 1
Frequently Asked Questions

What is 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. It is an AI Agent Skill for Claude Code / OpenClaw, with 1625 downloads so far.

How do I install Lead Scorer?

Run "/install lead-scorer" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Lead Scorer free?

Yes, Lead Scorer is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Lead Scorer support?

Lead Scorer is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Lead Scorer?

It is built and maintained by 1kalin (@1kalin); the current version is v1.0.0.

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