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SmartTrim

AI community

Description

macOS menu bar app that fixes mangled clipboard text from AI coding assistants. Removes ghost indentation, unwraps hard-wrapped lines, preserves lists.

Installation

This entry records only its repository, not the path inside it, so there is no exact command to give. Open the source below and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

README

SmartTrim

macOS menu bar utility that fixes mangled clipboard text from AI coding assistants.

You know the problem: you're deep in Claude Code, Cursor, or Copilot, copy some text, paste it into Slack or Notion, and it's full of ghost indentation, hard line breaks mid-sentence, and weird formatting artifacts.

SmartTrim sits in your menu bar and fixes it automatically.

smarttrim smarttrim-settings

Features

  • Auto-Trim — Monitors clipboard, automatically cleans malformed text
  • Manual Trim — Global hotkey (⌘⇧.) or menu bar button
  • Smart Detection — Only processes text that looks broken
  • Preserves Structure — Keeps lists, paragraphs, and intentional formatting

What It Fixes

Problem Example
Ghost indentation text with invisible leading spaces
Hard-wrapped lines This sentence was\nbroken mid-flow
Mixed formatting Bullet points with broken continuations

Install

Download from [Releases](https://github.com/gmickel/SmartTrim/releases) or build from source:

brew install xcodegen
git clone https://github.com/gmickel/SmartTrim.git
cd SmartTrim
xcodegen && xcodebuild -scheme SmartTrim -configuration Release

Requirements

  • macOS 14.0 (Sonoma) or later
  • Apple Silicon or Intel

Settings

  • Launch at Login — Start automatically
  • Auto-Trim — Enable/disable clipboard monitoring
  • Hotkey — Customize the manual trim shortcut

Tech

Swift 6, SwiftUI, strict concurrency. No Electron. No dependencies. ~500 lines.

Author

**Gordon Mickel** — [mickel.tech](https://mickel.tech)

Origin

Built as part of [gmickel-bench](https://mickel.tech/gmickel-bench), a project comparing AI coding assistants on real-world task