agentsclimarketplace

Lead list analysis

Skill spiralcrew-ou/profilespider-agent-skills/lead-list-analysis

24 free SKILL.md skills for Claude Code & compatible agents: qualify leads, research companies, clean lists.

Install
npx -y skills add spiralcrew-ou/profilespider-agent-skills --skill lead-list-analysis

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 6 stars6 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Assesses the quality, composition, and usefulness of a lead list. Use when the user provides a lead list and wants completeness, distribution, quality issues, and recommended next actions.

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

1.8 KB, as published. Nobody here has run it

Lead List Analysis

Purpose

Assess the quality, composition, and usefulness of a lead list with next actions.

When to use this skill

  • Sanity-checking a list before outreach
  • Measuring field completeness and gaps
  • Understanding list composition
  • Deciding what to fix or enrich next

When not to use this skill

  • You want per-record scoring (use Lead Qualification)
  • The file has no consistent structure
  • You need market-level patterns (use Market Research)

Required inputs

  • A lead list

Optional inputs

  • Required fields for your use
  • Your ICP for fit distribution
  • A quality threshold

Rules

  1. Report real completeness rates, not estimates.
  2. Surface concrete quality issues with counts.
  3. Tie next actions to the issues found.
  4. Do not invent missing values.
  5. Keep the analysis structure consistent.

Process

  1. Profile the list size and fields.
  2. Compute field completeness.
  3. Summarize segment distribution.
  4. Detect quality issues and missing data.
  5. Recommend next actions.

Output format

Return a list-quality report with the following fields:

  • list_overview
  • field_completeness
  • segment_distribution
  • quality_issues
  • missing_data
  • recommended_next_actions

Validation

  • Confirm completeness rates match the data.
  • Confirm issue counts are accurate.
  • Confirm actions address the issues.

Limitations

  • Analysis reflects the supplied list only.
  • It measures completeness, not factual correctness.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.