hf.audit-code

Audit Python code quality and create themed GitHub issues.

5|2|Updated Feb 18, 2026
One-click install
npx skills add https://github.com/T-rav/hydraflow --skill hf-audit-code
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: hf.audit-code
Source: https://github.com/T-rav/hydraflow/tree/main/.codex/skills/hf.audit-code
Command: npx skills add https://github.com/T-rav/hydraflow --skill hf-audit-code

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Identifies code quality issues (dead code, high complexity, duplication, and robustness gaps) across a repository and triggers actionable GitHub issues to drive remediation.

Core Features & Use Cases

  • Code quality auditing: dead code detection, complexity and duplication checks, error handling robustness review, and type-safety checks across Python projects.
  • Automated GitHub issue creation: groups findings into themed issues and assigns to a repository owner to drive remediation.
  • Configurable workflow: respects repository configuration for target repo, assignee, and labels to ensure traceability.

Quick Start

Run the hf.audit-code skill to perform a full code-quality audit and publish grouped GitHub issues for findings to your repository.

Frequently Asked Questions about hf.audit-code

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

FAQPage Schema
How do I automate Python code quality audits for dead code and complexity?

To automate Python code quality audits, this Skill scans your repository to identify dead code, complexity, duplication, and robustness gaps, then automatically generates grouped GitHub issues to drive remediation.

Can I automatically create GitHub issues for code quality findings?

Yes, you can automatically create GitHub issues for code quality findings. The Skill groups audit results by theme, assigns them to a repository owner, and applies configured labels to ensure traceability.

What is the best way to check for code duplication and robustness gaps in Python?

The best way to check for code duplication and robustness gaps is running a full repository audit. This Skill evaluates Python source files to determine metrics for duplication, error handling robustness, and type-safety.

Does the code quality audit respect my repository configuration for assignees and labels?

Yes, the code quality audit respects your repository configuration. It uses your defined target repository, assignee, and labels to ensure that generated issues match your existing project management workflow.

How do I track and assign ownership for dead code detection results?

To track and assign ownership for dead code detection results, the Skill assigns the generated themed GitHub issues directly to a configured repository owner and stores discovered values for reproducible planning.

What Python code metrics are calculated during a repository complexity audit?

During a repository complexity audit, the Skill calculates metrics for dead code, complexity, duplication, error handling robustness, and type-safety across your Python source files.