llt-find-sources

Map C++ test-source file relationships using evidence-based scoring and output structured JSON with confidence breakdowns.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/ai-sand-castles/local-marketplace --skill llt-find-sources
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: llt-find-sources
Source: https://github.com/ai-sand-castles/local-marketplace/tree/main/test-automation-plugin/skills/llt-find-sources
Command: npx skills add https://github.com/ai-sand-castles/local-marketplace --skill llt-find-sources

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Map test files to source files and vice versa using evidence-based confidence scoring to reveal relationships between tests and production code.

Core Features & Use Cases

  • Forward lookup: test -> sources by analyzing includes and naming conventions.
  • Reverse lookup: source -> tests by scanning test suite and correlating basenames.
  • Evidence-driven scoring: combines direct includes, naming-convention matches, and optional module-dependency signals to produce confidence levels.

Quick Start

Provide a test file path and project root to obtain mapped sources and/or tests with confidence scores.

Frequently Asked Questions about llt-find-sources

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

FAQPage Schema
How do I map C++ unit tests to source files using evidence-based confidence?▼

Map C++ unit tests to source files by parsing #include directives, applying naming-convention inferences, and evaluating optional module dependencies to generate structured JSON output with confidence breakdowns.

Can I find which tests cover a specific source file in an Unreal-like C++ project?▼

Find which tests cover a specific source file by performing a reverse lookup that scans the test suite and correlates basenames to map source files back to their corresponding tests.

How does confidence scoring work when mapping tests to production code?▼

Confidence scoring works by combining direct include matches, naming-convention inferences, and optional module-dependency signals to calculate evidence-driven confidence levels for each test-to-source mapping.

Does this test-to-source mapping tool work with Unreal-like project layouts?▼

This mapping tool works with Unreal-like project layouts, handling direct includes, naming-convention matching, and optional module dependencies to accurately map test files and source files across C++ projects.

What is the best way to identify relationships between test files and production code?▼

The best way to identify relationships is using evidence-based scoring that analyzes direct includes, naming conventions, and module dependencies to reveal forward and reverse mappings between tests and production code.

What do I need to provide to start mapping tests to source files?▼

Provide a test file path and a project root directory to obtain mapped sources and tests with corresponding confidence scores and structured JSON relationship mappings.