How do I install the Browser Bookmarks Cleanup skill?

Run npx skillmds@latest add dvcrn/browser-bookmarks-cleanup in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Browser Bookmarks Cleanup safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: executes scripts. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Browser Bookmarks Cleanup?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Browser Bookmarks Cleanup free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Browser Bookmarks Cleanup?

dvcrn (@dvcrn) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Browser Bookmarks Cleanup by dvcrn — Agent Skill

Name: Browser Bookmarks Cleanup
Rating: 4.5 (4 reviews)
Author: dvcrn

Browser Bookmarks Cleanup

Analyze, organize, and clean browser bookmarks on macOS using on-disk bookmark and history files. Detects duplicates, stale bookmarks, tracking parameters, and folder issues. All writes are opt-in with backup and rollback.

dvcrn Updated Sep 8, 2026 32 repo stars

File contents

Browser Bookmark Cleanup

Analyze first, organize, then clean up. All writes are opt-in and reversible.

Supported browsers: Chrome and Firefox out of the box. Other Chromium-based browsers (Edge, Brave, Arc, etc.) can be handled by pointing to their profile directories, which use the same Bookmarks JSON format as Chrome.

Workflow

Discover browser profiles.
Run read-only analysis and share findings.
Propose cleanup plan with preview.
Get explicit user approval before any writes.
Dry-run first, then write with automatic backup.
Report changes and how to roll back.

Hard Safety Rule

Never send network requests to bookmark URLs. Analysis uses only local files.

Commands

Discover profiles:

python3 scripts/browser_bookmarks.py discover [--browser chrome|firefox]

Analyze bookmarks:

python3 scripts/browser_bookmarks.py analyze --bookmarks "<PATH>" --output /tmp/bookmark-analysis.json

Apply plan (dry-run by default, --write to commit):

python3 scripts/browser_bookmarks.py apply-plan --bookmarks "<PATH>" --plan /tmp/bookmark-plan.json [--write]

Analysis Categories

Exact and semantic duplicate URLs
Tracking-parameter variants (utm_*, gclid, fbclid, etc.)
Subdomain and domain concentration
HTTP links that should be HTTPS
Empty, singleton, deep, and oversized folders
Weak bookmark names
Old bookmarks by age
Never-visited and stale bookmarks (from browser history)

Approval Gate

Before any write: show plan preview, get explicit approval, ask user to close the browser.

Plan Format

See references/plan-schema.md for the JSON plan structure.

Rollback

Restore the timestamped backup file created before any write.

---name: browser-bookmarks-cleanupdescription: Analyze, organize, and clean browser bookmarks on macOS using on-disk bookmark and history files. Detects duplicates, stale bookmarks, tracking parameters, and folder issues. All writes are opt-in with backup and rollback.---# Browser Bookmark CleanupAnalyze first, organize, then clean up. All writes are opt-in and reversible.> **Supported browsers:** Chrome and Firefox out of the box. Other Chromium-based browsers (Edge, Brave, Arc, etc.) can be handled by pointing to their profile directories, which use the same Bookmarks JSON format as Chrome.## Workflow1. Discover browser profiles.2. Run read-only analysis and share findings.3. Propose cleanup plan with preview.4. Get explicit user approval before any writes.5. Dry-run first, then write with automatic backup.6. Report changes and how to roll back.## Hard Safety RuleNever send network requests to bookmark URLs. Analysis uses only local files.## CommandsDiscover profiles:```bashpython3 scripts/browser_bookmarks.py discover [--browser chrome|firefox]```Analyze bookmarks:```bashpython3 scripts/browser_bookmarks.py analyze --bookmarks "<PATH>" --output /tmp/bookmark-analysis.json```Apply plan (dry-run by default, `--write` to commit):```bashpython3 scripts/browser_bookmarks.py apply-plan --bookmarks "<PATH>" --plan /tmp/bookmark-plan.json [--write]```## Analysis Categories1. Exact and semantic duplicate URLs2. Tracking-parameter variants (`utm_*`, `gclid`, `fbclid`, etc.)3. Subdomain and domain concentration4. HTTP links that should be HTTPS5. Empty, singleton, deep, and oversized folders6. Weak bookmark names7. Old bookmarks by age8. Never-visited and stale bookmarks (from browser history)## Approval GateBefore any write: show plan preview, get explicit approval, ask user to close the browser.## Plan FormatSee `references/plan-schema.md` for the JSON plan structure.## RollbackRestore the timestamped backup file created before any write.

Frequently asked questions