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Genpark amazon author ranker

Skill alphaparkinc/genpark-amazon-author-ranker

GenPark Distilled Skill: amazon-author-ranker

Install
npx -y skills add alphaparkinc/genpark-amazon-author-ranker

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

2 things to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 9 stars9 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

Author Performance Ranker. Tracks and analyzes creator/author performance across multi-year datasets based on feedback and frequency.

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

1.3 KB, 195 tokens by cl100k_base, as published. Nobody here has run it

Amazon Author Ranker

This skill focuses on the "human element" of e-commerce data. It ranks and analyzes authors or creators based on their longitudinal performance, helping identifying consistent "hits" and rising stars.

Instructions

  1. Consistency Tracking: Count occurrences of a specific author/creator across multi-year datasets to measure market longevity.
  2. Quality Scoring: Weight rankings by average user ratings and total review counts to ensure quality is prioritized over volume.
  3. Sentiment Extraction: (If text data is available) Summarize general customer sentiment toward specific authors.
  4. Output: Generate a leaderboard of creators with detailed metrics on their average price point and rating stability.

Examples

  • "Who are the most consistent best-selling authors in the Non-Fiction category from 2010 to 2020?"
  • "Rank authors in this dataset by a combination of their total number of best-sellers and their average user rating."

What ships with it: 3 files

0 B alongside SKILL.md

assets/

references/

scripts/

Keep looking

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