confidence-scorer

Name: confidence-scorer
Availability: InStock
Author: brucetyndall

Validate confidence scoring implementation across intelligence data surfaces.

Updated Aug 23, 2026

Search Tags:#validation #data quality #code audit #confidence score #signal reliability #trust indicator

Ready to run

npx skills add https://github.com/BruceTyndall/socelle-global --skill confidence-scorer

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: confidence-scorer
Source: https://github.com/BruceTyndall/socelle-global/tree/main/.agents/skills/confidence-scorer
Command: npx skills add https://github.com/BruceTyndall/socelle-global --skill confidence-scorer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill ensures that confidence scoring is consistently and correctly implemented across all intelligence data surfaces, verifying that every signal has an appropriate confidence tier and that these scores are derived from a sound methodology.

Core Features & Use Cases

Schema Validation: Checks for the presence of 'confidence' columns in database migration files.
Codebase Scan: Analyzes source code (hooks, components, integrations) for confidence-related logic and UI elements.
Hardcoded Value Detection: Identifies instances where confidence values might be hardcoded instead of dynamically generated.
Use Case: Before deploying a new feature that relies on data reliability, use this Skill to automatically audit the confidence scoring implementation, ensuring users can trust the displayed data.

Quick Start

Run the confidence scorer skill to validate confidence tier implementation across the SOCELLE-WEB application.

Frequently Asked Questions about confidence-scorer

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

FAQPage Schema

How do I validate confidence scoring implementation across my application?▼

You can validate confidence scoring by scanning database migrations, application hooks, integrations, and UI components to verify confidence tiers, score methodology, and UI indicators are correctly implemented.

What is confidence scoring validation for data surfaces?▼

Confidence scoring validation ensures intelligence signals have assigned confidence tiers derived from sound methodology and that UI components display consistent confidence indicators.

How do I detect hardcoded confidence values in my codebase?▼

Detect hardcoded confidence values by scanning hooks, components, and integrations for static confidence-related patterns instead of dynamically generated scores.

Do I need Node.js to audit confidence score methodology in my application?▼

Yes, you need Node.js along with grep and find utilities to audit confidence score methodology by scanning database migrations and application components for validation patterns.

Can I check if database migration files include confidence columns?▼

Yes, you can check database migration files for confidence columns by scanning schema patterns to ensure data surfaces support score validation.

What are the limitations of automated codebase scans for confidence indicators?▼

Automated codebase scans for confidence indicators rely on pattern matching and cannot verify the statistical soundness of the underlying score methodology itself.