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.

Security Scan

The skill's requirements and runtime instructions match its stated purpose (lead scoring) and it does not request extra credentials, installs, or suspicious actions.

Purpose & Capability

Name/description match the instructions: scoring framework (fit/intent/engagement), BANT/MEDDIC qualification, grading, and batch scoring. No unrelated binaries, env vars, or config paths are requested.

Instruction Scope

SKILL.md is limited to how to score and qualify leads and what outputs to return. It does not instruct the agent to read system files, fetch external data, access credentials, or transmit data to unexpected endpoints. The only external references are documentation/marketing links in README.

Install Mechanism

Instruction-only skill with no install spec and no code files, so nothing is written to disk or downloaded during install.

Credentials

No environment variables, credentials, or config paths are requested — proportional for a skill that processes user-provided lead data interactively.

Persistence & Privilege

always is false (default) and the skill does not request persistent privileges or modify other skills/system settings.

Assessment

This skill appears coherent and low-risk as-is, but remember it will process whatever lead data you paste into the agent — which may include personal or sensitive information. Before using: (1) avoid pasting unnecessary PII or confidential contract terms into the chat; (2) if you require automated CRM integration, use a dedicated CRM-integrator skill rather than pasting credentials here; (3) be aware that any data you send to the agent may be logged/processed according to your platform/provider policies; (4) verify external links (the README points to afrexai-cto.github.io) before following them. If you need on-premise or private processing for sensitive leads, prefer a self-hosted/private model deployment rather than a public cloud model.

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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