worktrees

Guide for using git worktrees to parallelize development with coding agents. Use this skill when the user requests to work in a new worktree or wants to work on a separate feature in isolation (e.g., "Work in a new worktree", "Create a worktree for feature X").

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Repository: maragudk/skills
Last source activity: October 31, 2025 at 13:49
Detected SKILL.md language: English
Stars: 49
Forks: 9

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The review-first prompt is selected by default. You can switch to a direct command or download a local copy.

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Copy this prompt into the AI assistant you're using.

Follow https://skillsmp.com/skill-install/prompt.md to install only the Agent Skill at https://github.com/maragudk/skills/tree/main/worktrees.

A direct command skips the review prompt. Inspect the source before running it.

npx skills add https://github.com/maragudk/skills --skill worktrees

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Read SKILL.md and any companion files shown by SkillsMP before deciding whether to install.

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SKILL.md

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name	worktrees
description	Guide for using git worktrees to parallelize development with coding agents. Use this skill when the user requests to work in a new worktree or wants to work on a separate feature in isolation (e.g., "Work in a new worktree", "Create a worktree for feature X").

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garden

Autonomous project gardening. Scans for maintenance issues (starting with documentation), picks one, fixes it in a worktree, self-reviews with competing agents, and opens a PR. Use when the user wants to tidy up the project, fix stale docs, or generally tend the codebase. Invoke with /garden.

2026-03-26

diary

Write and maintain an implementation diary capturing what changed, why, what worked, what failed (with exact errors and commands), what was tricky, and how to review and validate. Activates proactively during non-trivial implementation work (new features, bug fixes, refactors, research spikes). Does not activate for trivial tasks like one-line fixes, config tweaks, or quick questions.

2026-03-25

autoresearch

Autonomous experiment loop that iteratively improves a measurable metric. Given a goal, a verify command, and an optional guard, the agent branches, makes one change, measures the result, and keeps or discards the experiment -- repeating indefinitely. Use this skill when the user wants to optimize something measurable through automated experimentation, autonomous improvement loops, or when they mention "autoresearch". Works for any domain with a quantifiable metric (code performance, ML training, build size, test scores, content quality metrics, etc.).

2026-03-24

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worktrees

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