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anthony-chaudhary
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skill-score

Quantifies skill-debt via nine KPI scorecard in agentic repositories requiring fak kernel environment.

30|12|Updated Jun 21, 2026
Search Tags:#automation#validation#governance#quality-assurance#technical-debt#scorecard
One-click install
npx skills add https://github.com/anthony-chaudhary/fak --skill skill-score
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: skill-score
Source: https://github.com/anthony-chaudhary/fak/tree/main/.claude/skills/skill-score
Command: npx skills add https://github.com/anthony-chaudhary/fak --skill skill-score

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill addresses the lack of objective quality metrics for the skill pack itself, turning the subjective claim of skill effectiveness into a provable, data-driven reality.

Core Features & Use Cases

  • Skill-Debt Measurement: Evaluates every skill against nine hard and soft KPIs, including discoverability, operational safety, and trust.
  • Worst-First Remediation: Generates a prioritized work-list to retire debt by adding concrete affordances like trigger clauses and scoped tool permissions.
  • Verification Loop: Re-measures the skill pack after improvements to prove the reduction in debt and ensure the repository remains in a high-quality, maintainable state.

Quick Start

Run the skill-score command to measure the current skill-debt and generate a prioritized improvement plan for the repository.

Frequently Asked Questions about skill-score

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

FAQPage Schema
How do I quantify technical debt in AI skill repositories?▼

You measure skill-debt by evaluating each skill unit against a standardized scorecard of nine operational and discoverability KPIs. This generates a prioritized work-list to retire debt by adding concrete affordances like trigger clauses and scoped tool permissions.

What is the best way to prioritize technical debt remediation for agentic skills?▼

The best way to prioritize remediation is generating a worst-first work-list from the nine-KPI scorecard evaluation. This targets the highest debt skills first by prescribing concrete affordances like trigger clauses and scoped tool permissions.

How does a verification loop prove technical debt reduction in a skill pack?▼

A verification loop proves technical debt reduction by re-measuring the skill pack against the nine KPIs after improvements are applied. This ensures the repository maintains a high-quality, maintainable state with provable debt retirement.

Do I need a specific environment to run scorecard validation on skills?▼

Yes, you need the fak kernel environment to execute the effectiveness scorecard and validate the integrity of the skill-debt work-list generated during the technical debt evaluation process.

What operational safety metrics are used for AI skill quality assurance?▼

AI skill quality assurance uses a standardized scorecard of nine hard and soft KPIs covering discoverability, operational safety, and trust. This evaluates each skill unit to ensure consistent, safe, and reliable tool execution across the repository.

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