Scoring

Evaluate information against predefined criteria and output JSON scores with confidence levels.

Updated Mar 11, 2026

Search Tags:#decision making #evaluation #scoring #confidence #criteria #rating

Ready to run

npx skills add https://github.com/prathamchopra001/INQUIRO --skill scoring-prathamchopra001

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: Scoring
Source: https://github.com/prathamchopra001/INQUIRO/tree/main/skills/scoring
Command: npx skills add https://github.com/prathamchopra001/INQUIRO --skill scoring-prathamchopra001

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill automates the process of assigning objective scores and confidence levels to various inputs based on predefined criteria, ensuring consistency and reducing manual evaluation effort.

Core Features & Use Cases

Objective Evaluation: Applies a consistent scoring rubric to assess information.
Confidence Assessment: Provides a quantifiable measure of certainty for each score.
Use Case: Evaluating the quality of research findings on a scale of 1-5, or scoring the relevance of a document to a specific query.

Quick Start

Use the scoring skill to evaluate the provided dataset quality with a score from 1 to 5.

Frequently Asked Questions about Scoring

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

FAQPage Schema

How do I automatically assign a numerical score and confidence rating to data?▼

Automated scoring applies predefined criteria to evaluate inputs and assigns a numerical score alongside a confidence level. It outputs structured JSON detailing the score, reasoning, and confidence percentage to ensure evaluation consistency.

What is the best way to evaluate research findings quality on a numerical scale?▼

Evaluating research findings quality is best handled by applying a consistent scoring rubric to assess the information. This objective evaluation method ensures consistent measurement and reduces manual effort across multiple datasets.

Can I get structured JSON output when scoring document relevance?▼

Yes, you can get structured JSON output when scoring document relevance. The evaluation process details the assigned score, the reasoning behind it, and a quantifiable confidence percentage directly within the JSON structure.

How does confidence assessment handle edge cases like insufficient data?▼

Confidence assessment handles edge cases like insufficient data or conflicting criteria by adjusting the evaluation output. It provides a quantifiable measure of certainty that reflects data limitations rather than failing the process.

Do I need to define evaluation criteria before scoring dataset quality?▼

Yes, you need to define evaluation criteria before scoring dataset quality. The scoring mechanism applies a consistent rubric based on your predefined parameters to assign objective scores and confidence levels.