Automation and integrations decision

Hazel

A basic Hazel-like folder watcher and rule engine is realistic for a single technical person to build and run; matching the complete product (deep macOS integrations, polished GUI, and convenience features) is more work and where the commercial product retains advantage.

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SubscriptionCustom pricing
Initial build30 hours
Monthly upkeep4 hours + $0
Evidence3/3 runs agree

Open-source builds that already do this

Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need — the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship.

What a replacement has to do

  • Watch folders for filesystem changes, match files against rule patterns, then move/rename/tag/delete or run actions on matched files.

What it still won’t have

  • Deep macOS integrations (Spotlight integration, Photos/Music/TV importing, Shortcuts)
  • App Sweep behaviour for finding and removing app support files
  • Polished commercial GUI and curated UX
  • AppleScript & Automator integration out of the box
  • Vendor support, updates, and QA across macOS versions

What remains hard

  • Execution quality“Hazel's combination of power and ease of use makes it one of the handiest Mac utilities I’ve used”
Read the build prompt

First-year cost

No published price

Hazel does not publish a price we could read, so there is nothing to compare against. What building costs is below.

Money you would actually spend

Keep paying

Subscription price × seats × 12

Build it

AI build APIs + hosting

Time you would spend

What you would spend

What we assumed

The verdict above measures whether you could build it. This one is only about money.

Runnable build prompt

Not run yet
Build a macOS file-organization daemon in Swift that watches configured folders (FSEvents/DispatchSource), evaluates files against a JSON-defined rule set (name, type, dates, source URL, metadata), and executes actions (move, rename, tag via metadata APIs if available, delete, or run shell scripts). Include a minimal CLI to add/list/remove rules, persist rules in a local SQLite DB, log actions to a rotating file, and expose a read-only HTTP status endpoint for recent activity. Out of scope: full macOS GUI polish, Automator/AppleScript integration, Photos/Music/TV import pipelines, and App Sweep heuristics. Provide unit tests for the rule engine, integration tests for file actions (using a temp folder), robust error handling, and a launchd plist for installation.
How we checked2 sources · 3/3 runs agreed · evidence score 62

How the score was reached

  • Partly verdict base52
  • An open-source build was found+5
  • 2 cited sources+1
  • 3/3 assessment runs agreed+4
  • Evidence score62

The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time — so the same evidence always produces the same number.

How scoring works →

Cited sources · 2

Every page the run actually retrieved.

Integrity checks

What held up, and what did not.

✓ 3 independent runs, one answer✓ Citations limited to fetched pages! 1 moat quoted from the page