warmeaf/code-quality-report-skill

Overview

This skill generates a single-page code quality report named code-quality-report.html for a project's source files. It combines a Node.js file-structure script and an HTML template to produce a browsable report that includes per-file quality scores. The workflow creates and updates a JSON data file and injects that data into the template to produce the final HTML output.

How this skill works

The skill runs a Node.js script to scan the source folder (typically src/) and emits code-quality-report.json containing the project file tree with initial code_quality values. It then reads each source file, evaluates quality against a reference standard, and updates the JSON with scores (0–100). Finally it injects the JSON into code-quality-report-template.html by replacing the rawData variable and writes the single-page report to .cqm/code-quality-report/code-quality-report.html.

When to use it

• When you need a quick, project-wide snapshot of code quality across source files.
• Before a release to identify files that require refactoring or additional review.
• When onboarding new contributors to show code hotspots and maintainability concerns.
• As part of a periodic CI job to track quality trends over time.
• When you want a local, self-contained HTML report that can be shared with non-technical stakeholders.

Best practices

• Keep the source folder path explicit (e.g., src/) when invoking the generation script to avoid scanning irrelevant files.
• Store the output in the default .cqm/code-quality-report/ folder or configure a dedicated report directory for CI artifacts.
• Maintain and update the reference quality standard file used for evaluations to reflect team conventions.
• Run file evaluations in parallel workers or sub-agents for large repositories to speed up scoring.
• Commit only the template and scripts to VCS; treat generated JSON and HTML as build artifacts to avoid merge conflicts.

Example use cases

• Generate a one-off quality audit to prioritize refactors before a major release.
• Integrate into CI to produce per-commit or nightly quality reports for engineering dashboards.
• Use during code review to attach objective quality scores and highlight problematic files.
• Run after automated linting and tests to add a higher-level, AI-assisted quality assessment.
• Produce a sharable HTML snapshot for managers to review progress without opening code.