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AribSudia
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arib-check-reality

Scan source files and manifests to detect mock data and disconnected API wiring.

2|Updated Apr 19, 2026
Search Tags:#testing#api#codebase#audit#quality#mocking
One-click install
npx skills add https://github.com/AribSudia/claude-code-methodology --skill arib-check-reality
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: arib-check-reality
Source: https://github.com/AribSudia/claude-code-methodology/tree/main/.claude/skills/arib-check-reality
Command: npx skills add https://github.com/AribSudia/claude-code-methodology --skill arib-check-reality

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This skill eliminates the risk of shipping mock data or disconnected frontend components to production by identifying hardcoded responses, fake API endpoints, and placeholder content.

Core Features & Use Cases

  • Reality Scoring: Quantifies the percentage of data-driven components actually connected to real backends.
  • Mock Detection: Scans for mock libraries like MSW, Faker, and MirageJS in production code.
  • Remediation Planning: Generates a structured, phase-based plan to replace fake data with real API integrations.

Quick Start

Run the arib-check-reality command to perform a full codebase scan and generate a reality audit report.

Frequently Asked Questions about arib-check-reality

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

FAQPage Schema
How do I scan my codebase for mock data and fake APIs?▼

Scanning a codebase for mock data involves systematically checking source files, dependency manifests, and environment configurations to identify hardcoded responses and disconnected API wiring. This process generates a reality score quantifying actual backend connections.

What is a reality score in codebase auditing?▼

A reality score quantifies the percentage of data-driven components actually connected to real backends instead of mock data. It is calculated by scanning source files, dependency manifests, and environment configurations to assess overall production readiness.

How do I detect mock libraries like MSW and MirageJS in production code?▼

Detecting mock libraries like MSW, Faker, and MirageJS in production code requires scanning dependency manifests and source files for their specific imports and usage patterns. This identifies fake API endpoints and hardcoded responses that risk shipping to production.

How do I generate a remediation plan to replace fake data with real API integrations?▼

Generating a remediation plan to replace fake data involves creating a structured, phase-based approach after auditing the codebase. The plan systematically guides the replacement of hardcoded responses and mock data with functional real API integrations.

When should I run an audit for mock data and hardcoded responses?▼

An audit for mock data and hardcoded responses should be run during end-of-sprint reviews, pre-release verification, and technical debt assessment. This ensures data-driven applications are production ready and free of disconnected API wiring.

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