find-weeds

Detect code hygiene issues and generate actionable GitHub issues.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/bketelsen/ytsejam --skill find-weeds
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: find-weeds
Source: https://github.com/bketelsen/ytsejam/tree/main/contrib/skills/find-weeds
Command: npx skills add https://github.com/bketelsen/ytsejam --skill find-weeds

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill helps you identify and triage small, non-disruptive code hygiene issues in a codebase, enabling teams to keep software healthy without major refactors.

Core Features & Use Cases

  • Automated weed discovery: detects missing tests, duplicated blocks, lint/style violations, narrowable types, and stale documentation.
  • Issue filing guidance: prioritizes actionable items and formats concise GitHub issues for tracking.
  • Use Case: during a maintenance sprint, run the weed scan to surface a handful of safe improvements to log as issues and close technical debt.

Quick Start

Scan the repository for a handful of small, safe maintenance issues and file up to five GitHub issues describing concrete fixes.

Frequently Asked Questions about find-weeds

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

FAQPage Schema
How do I find small code hygiene issues like missing tests and lint violations in my codebase?

Code cleanup issues are identified by targeting common maintenance scenarios such as missing tests, duplicated blocks, lint violations, type gaps, and stale docs. It enforces non-structural changes to ensure maintenance remains safe and non-disruptive to the codebase.

How do I automatically file GitHub issues for TODOs and code cleanup tasks?

GitHub issues are generated by prioritizing actionable items and formatting concise descriptions for each finding. This process targets safe improvements like TODOs and duplicated blocks, creating precise issues for tracking technical debt.

What is the best way to triage technical debt during a maintenance sprint?

Technical debt during a maintenance sprint is triaged by running a weed scan to surface safe improvements. This identifies small, non-disruptive code hygiene issues and logs them as GitHub issues to close technical debt efficiently.

Does this code hygiene scanner support multiple programming languages?

Yes, the code hygiene scanner detects issues such as missing tests, duplicated blocks, and stale docs across languages. It targets common maintenance scenarios without being limited to a single programming language environment.

Can I use this to identify duplicated code blocks and narrowable types?

Yes, duplicated blocks and narrowable types are identified as part of automated weed discovery. The skill also detects missing tests, lint violations, TODOs, and stale documentation to provide comprehensive code hygiene coverage.

What are the limitations of using automated weed discovery for code cleanup?

The limitation of automated weed discovery is that it enforces non-structural changes, focusing only on small, safe code hygiene issues. It does not perform major refactors, but instead surfaces actionable items like missing tests and lint violations.