disambiguation-score

Audit terminology against a glossary to resolve naming collisions.

30|12|Updated Jun 21, 2026

Search Tags:#documentation #refactoring #vocabulary #clarity #governance #disambiguation

Ready to run

npx skills add https://github.com/anthony-chaudhary/fak --skill disambiguation-score

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: disambiguation-score
Source: https://github.com/anthony-chaudhary/fak/tree/main/.claude/skills/disambiguation-score
Command: npx skills add https://github.com/anthony-chaudhary/fak --skill disambiguation-score

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill resolves naming collisions and conceptual blurring within a growing codebase, ensuring that every technical term has a single, canonical definition and clear boundaries against similar concepts.

Core Features & Use Cases

Concept Disambiguation: Automatically identifies overloaded terms and enforces a strict one-name-one-definition policy.
Debt Tracking: Measures and reports on clarity debt, providing a prioritized list of concepts that require formal distinction.
Use Case: When a project grows to include multiple types of caches or guards, this tool ensures that developers and AI agents use consistent terminology, preventing misuse and confusion.

Quick Start

Run the disambiguation scorecard tool to identify and address naming debt in the current repository.

Frequently Asked Questions about disambiguation-score

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

FAQPage Schema

How do I resolve naming collisions and concept drift in a complex codebase?▼

To resolve naming collisions and concept drift, audit terminology against a glossary of canonical definitions to enforce strict distinction rules and a one-name-one-definition policy. This requires a structured data directory of confusable terms and a defined glossary anchor.

What is clarity debt and how do I track it during codebase refactoring?▼

Clarity debt is the accumulated vocabulary ambiguity from overloaded technical terms. You track it by running a disambiguation scorecard tool that measures and reports prioritized concepts requiring formal distinction, ensuring developers use consistent terminology.

When do I need to enforce strict vocabulary governance in technical documentation?▼

You need strict vocabulary governance when a project grows to include multiple types of similar concepts, like caches or guards. Enforcing a one-name-one-definition policy prevents misuse and confusion among developers and AI agents interacting with the documentation.

What's the best way to disambiguate overloaded technical terms against a glossary?▼

The best way to disambiguate overloaded terms is to validate conceptual clarity using a defined glossary anchor. You must structure a data directory of confusable terms to systematically audit terminology and enforce clear boundaries between related concepts.

Do I need a structured data directory to audit terminology in documentation?▼

Yes, you need a structured data directory of confusable terms to audit terminology effectively. This directory, paired with a defined glossary anchor, validates conceptual clarity and ensures strict distinction rules are enforced across the codebase.

Can I use this disambiguation approach for AI agent documentation governance?▼

Yes, this disambiguation approach directly supports AI agent documentation governance. By enforcing a strict one-name-one-definition policy, it ensures AI agents and developers use consistent terminology, preventing misuse and confusion when processing complex technical concepts.