Skill Validator

Validate skill implementations against manifests using Codex semantic comparisons.

34|7|Updated Oct 22, 2025
One-click install
npx skills add https://github.com/daffy0208/ai-dev-standards --skill skill-validator-daffy0208
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: Skill Validator
Source: https://github.com/daffy0208/ai-dev-standards/tree/main/SKILLS/skill-validator
Command: npx skills add https://github.com/daffy0208/ai-dev-standards --skill skill-validator-daffy0208

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires codex, python3, and includes scripts (resource) components.

What problem does it solve?

This Skill solves the critical problem of implementation-manifest drift, where code implementations diverge from their documented capabilities and requirements.

Core Features & Use Cases

  • Semantic Validation: Uses Codex AI to perform deep semantic analysis comparing descriptions, preconditions, and effects against actual code.
  • Use Case: Imagine you've updated a skill implementation. Use this Skill to automatically validate that all described functionality is actually implemented and no undocumented features have been added.

Quick Start

Use the Skill Validator to check if the implementation in the 'rag-implementer' directory matches its manifest description.

Frequently Asked Questions about Skill Validator

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

FAQPage Schema
How do I detect when my skill implementation doesn't match its manifest description?

Skill Validator uses Codex-powered semantic analysis to compare your code implementation against manifest descriptions, preconditions, and effects. It flags description-implementation drift, missing capabilities, and over-promised features, producing metrics on accuracy and coverage.

Can I validate skills and MCP directories for undocumented features and capability gaps?

Yes. Skill Validator scans skill and MCP directories to detect both undocumented code additions and unimplemented promised features. It generates a descriptive validation artifact with drift metrics and inconsistency flags for remediation.

What's the best way to catch implementation-manifest drift during development and QA?

Run Skill Validator against your skill directory during development cycles and before releases. Semantic comparison across descriptions, preconditions, and API surfaces catches drift early, ensuring functional requirements are met before deployment.

Do I need Python and Codex to use Skill Validator?

Yes. Skill Validator requires Python 3 and Codex as dependencies. These enable the semantic analysis engine that compares implementations against manifest specifications.

What validation metrics does Skill Validator produce?

Skill Validator outputs accuracy, coverage, and drift metrics in a descriptive validation artifact. These metrics quantify how closely your implementation matches its manifest and identify specific inconsistencies requiring remediation.

When should I run validation—during development, QA, or release?

Apply Skill Validator throughout development, during QA cycles, and before releases. Early detection of drift prevents over-promised capabilities from reaching production and ensures manifest accuracy at every stage.