list-quality-scorecard

Grades lead list CSVs across eight quality dimensions and outputs a letter grade with fixes.

Updated Aug 2, 2026
One-click install
npx skills add https://github.com/Pinkycherry/newbusinessideas3 --skill list-quality-scorecard-pinkycherry
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: list-quality-scorecard
Source: https://github.com/Pinkycherry/newbusinessideas3/tree/main/.claude/skills/list-quality-scorecard
Command: npx skills add https://github.com/Pinkycherry/newbusinessideas3 --skill list-quality-scorecard-pinkycherry

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve? Cold email campaigns fail when lists contain duplicates, unverified emails, bad titles, or off-ICP contacts, burning domain reputation before copy even matters. This Skill scores a lead list before sending so preventable waste is caught in minutes. ## Core Features & Use Cases - Eight-dimension scoring: Grades email verification coverage, duplicate emails, duplicate domains, title relevance, bad-title patterns, catch-all density, ICP fit, and name quality, each on a 0-100 scale. - Letter grade with action items: Produces an A+ to F grade (verification and ICP fit weighted 2x), the top 5 issues to fix, and a pre-send checklist. - ICP comparison: Optionally compares the list against a client-profile.yaml file declaring target job titles, industries, and headcount ranges. - Use Case: After enriching 2,000 leads via an email waterfall, run the scorecard before uploading to Smartlead; if it returns a C due to 12% catch-all addresses and unverified emails, fix those issues and re-run until the grade reaches B. ## Quick Start Ask the AI to run the list quality scorecard on your leads.csv file with your client-profile.yaml ICP file and show the grade and top issues to fix.

Frequently Asked Questions about list-quality-scorecard

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I check lead list quality before sending cold email?

Run the score-list script against your CSV to score eight dimensions including verification coverage, duplicates, catch-all density, and ICP fit. It outputs a letter grade from A+ to F plus the top five issues to fix before uploading to your sending platform.

What CSV columns are required for lead list scoring?

The list needs email, first_name, last_name, and job_title or title, plus company_name or company. Optional columns like company_domain, company_industry, and company_headcount enable domain concentration and ICP fit scoring.

How is the lead list letter grade calculated?

Each of the eight dimensions is scored 0-100, then combined into a weighted average where email verification and ICP fit count double. Scores of 90 or above earn an A, 80-89 a B, and anything below 60 is an F meaning the list should be rebuilt.

Can I score a lead list against my ICP criteria?

Yes, pass an ICP file with the --icp-file flag containing job_titles, industries_in, and headcount_min or headcount_max values. The script then scores title relevance and ICP fit by matching each row against those declared filters.

When should I not run a lead list quality check?

Skip it for lists under 100 rows since the sample is too small for reliable statistics, and for fully static lists reused every send where one check suffices. It is designed for freshly built or enriched lists before first upload.