Measure repository code size and test metrics from actual source files.
npx skills add https://github.com/fukukei23/claude-config --skill code-metrics-fukukei23
Please help me install this Agent Skill. Skill: code-metrics Source: https://github.com/fukukei23/claude-config/tree/main/skills/code-metrics Command: npx skills add https://github.com/fukukei23/claude-config --skill code-metrics-fukukei23
This Skill prevents inaccurate portfolio and engineering reports by measuring code size and test coverage from actual repository files instead of relying on estimates or assumptions.
Ask the AI to measure the code lines and test cases for my repositories and record the verified results in the SSOT.
High-intent search queries and answers about installing and using this skill.
You can verify code volume claims for a technical resume by applying multi-layer validation: scanning actual source files, performing byte-size consistency checks, and reviewing git history. This proves measurements match real repository contents, preventing inaccurate portfolio reporting.
You can verify code volume claims for a technical resume by applying multi-layer validation: scanning actual source files, performing byte-size consistency checks, and reviewing git history. This proves measurements match real repository contents, preventing inaccurate portfolio reporting.
Line counting during repository analysis does exclude generated artifacts, virtual environments, and irrelevant directories. It applies deterministic file scanning rules to supported programming files to ensure only actual application and test code metrics are measured.
You can export code metrics and test measurements to a spreadsheet for engineering reports using optional openpyxl support. This allows you to record verified codebase reporting results across multiple repositories into a source-of-truth document.
The best way to audit code size across multiple repositories without estimates is to use deterministic file scanning combined with validation samples and test counting methods. This approach produces trustworthy engineering metrics derived directly from actual source files.
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