worktree-cleanup

worktree-cleanup is a skill for Claude Code, Codex from hxy91819/mason-skills. It costs 34 tokens per session (1,064 once invoked), scanned A, original, MIT.

A guide for reviewing and retiring Git worktrees, which are extra working directories linked to branches. It checks whether a clean worktree is safely stored on GitHub before removing it.

In plain words
What is it for?
Use it to find removable worktrees, review why each one is or is not eligible, and delete only candidates approved with the required review tokens.
Why use it?
It reduces clutter without deleting work that has not been preserved. The audit also identifies locked, changed, concurrent, or otherwise ineligible worktrees.

Skill for Claude CodeCodex

Written for Claude Code and Codex: disable-model-invocation in frontmatter, but also agents/openai.yaml present. Also seen: $skill-name invocation.

Good fit Use it to find removable worktrees, review why each one is or is not eligible, and delete only candidates approved with the required review tokens.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/hxy91819/mason-skills/worktree-cleanup
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add hxy91819/mason-skills --skill worktree-cleanup
Clone the repo
git clone --depth 1 https://github.com/hxy91819/mason-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for worktree-cleanup

README.md
[![agentmods](https://agentmods.dev/badge/skills/hxy91819/mason-skills/worktree-cleanup/github.svg)](https://agentmods.dev/skills/hxy91819/mason-skills/worktree-cleanup)
Your own site
<a href="https://agentmods.dev/skills/hxy91819/mason-skills/worktree-cleanup"><img src="https://agentmods.dev/badge/skills/hxy91819/mason-skills/worktree-cleanup/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for worktree-cleanup

Your own site · 80×15
<a href="https://agentmods.dev/skills/hxy91819/mason-skills/worktree-cleanup"><img src="https://agentmods.dev/badge/skills/hxy91819/mason-skills/worktree-cleanup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 34 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,064 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00034 $0.01064
Opus 5 $0.00017 $0.00532
Sonnet 5 $0.00007 $0.00213
Haiku 4.5 $0.00003 $0.00106

Measured 11d ago against content hash 82de8f413008, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

worktree-cleanup scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/cleanup_worktrees.py, tests/test_cleanup_worktrees.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

common-skills/worktree-cleanup/SKILL.md · 76 lines

How it starts

The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Worktree Cleanup

Run this workflow only when the user explicitly invokes $worktree-cleanup. It performs repository-wide discovery and can remove worktrees. Always audit first, present the exact candidates, and apply only the approval tokens the user selects.

Requirements

Require Git, Python 3.10+, GitHub CLI, and an authenticated gh session with read access to the repository's pull requests. Run from a repository checkout or pass --repo <path>.

Audit

  1. Check the current branch, git status --short, and git worktree list. Preserve concurrent and unrelated work.

  2. Create a new temporary report path outside the repository and run the helper in dry-run mode:

    python3 <skill-dir>/scripts/cleanup_worktrees.py \
      --repo <repo-path> \
      --dry-run \
      --json \
      --write-approval-report <temporary-report.json>
    
  3. Review every candidate and skip reason. A candidate is eligible only when all of these hold:

    • Git status is known and clean, including untracked files.
    • The worktree is neither locked nor marked prunable.
    • It is not the primary checkout or the checkout selected by --repo.
    • Its exact HEAD is contained in the remote head of a merged or closed GitHub pull request; or no pull request exists, the worktree is at least 24 hours old by default, and its HEAD is either the tip of a GitHub remote branch or contained in the remote default branch.
  4. Review ignored.discarded_sample and ignored.discarded_count for every candidate. These count ignored path roots, not files or bytes; one listed directory may contain substantial data. .local is backed up; all other ignored files are deliberately discarded if that candidate is approved.

  5. Tell the user the exact paths, whether each path is managed or external, remote durability proof, ignored data impact, backup base directory, and all retained paths with their reasons. Ask once whether to remove all listed candidates or a named subset; do not make the user copy or re-approve token strings. Worktrees outside .worktrees/ follow the same eligibility rules.

Read the full file on GitHub · 76 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 76 lines · 34 tokens per session scan A 82de8f413008

Subscribe to this mod's changes

worktree-cleanup is a skill published in the GitHub repository hxy91819/mason-skills (2 stars, last pushed today), licensed MIT. It adds 34 tokens to every session and 1,064 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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