Photo cleanup

Photo Cleanup

⚠️ Connection Required — ALWAYS CHECK FIRST

Before doing ANYTHING else in this skill, call ping on the Immich MCP server.

• If ping succeeds → proceed with the skill normally.
• If ping fails or the MCP tools are not available → STOP. Do not continue. Tell the user:

❌ Immich is not connected. This plugin needs a running Immich MCP server to work.

Run /setup-immich-photo-manager to configure your Immich connection. You'll need:

1. Your Immich server URL (e.g., http://192.168.1.100:2283)
2. An Immich API key (how to create one)
3. The MCP server configured (see /setup-immich-photo-manager)

Nothing in this plugin will work until the connection is configured.

Do NOT skip this check. Do NOT try to run any other tool first. Always ping, always block if it fails.

Intelligent photo library cleanup for Immich. Identifies and helps remove screenshots, duplicates, and low-quality images while protecting valuable photos.

Safety First

NEVER delete photos automatically. Always:

1. Identify candidates for removal
2. Present findings with counts and examples to the user
3. Get explicit approval before any deletion
4. Use delete_assets(asset_ids, force=False) to send photos to trash (recoverable). Use restore_assets or restore_trash to undo. Only use force=True for permanent deletion when the user explicitly requests it.

Cleanup Categories

1. Screenshot Detection

Screenshots are the #1 source of library bloat. Surface candidates with search_smart(query="screenshot") (CLIP) plus filename patterns (Screenshot*, Screen Shot*, Captura*) in search_metadata/list_assets results — dimensions are NOT searchable. Then score each candidate by combining multiple signals (dimensions and EXIF come from get_asset_info, per asset):

Signal	Weight	How to detect
Screen resolution	High	get_asset_info dimensions match known screen sizes exactly
No GPS data	Medium	EXIF GPS fields empty
No lens info	Medium	No focal length, aperture, or lens model
Filename pattern	Low	Contains "Screenshot", "Screen Shot", "Captura"
No camera make/model	Medium	Missing or generic device info

Screen resolutions to flag (exact pixel matches):

iPhone screens: 750x1334, 1125x2436, 1170x2532, 1242x2688, 1284x2778, 1290x2796 Mac screens: 1920x1080, 2560x1440, 2560x1600, 2880x1800, 3024x1964, 3456x2234 Common Android: 1080x1920, 1080x2340, 1080x2400, 1440x2560, 1440x3200

A photo matching 2+ signals is a strong screenshot candidate. Report confidence level:

• High confidence: Screen resolution + no GPS + no lens → almost certainly screenshot
• Medium confidence: Screen resolution only, or no GPS + no lens but non-standard resolution
• Low confidence: Only one signal matches → needs human review

2. Duplicate Detection

Sources of duplicates:

• Same photo in Google Fotos AND Apple Fotos (most common)
• Multiple exports of the same original (different formats: HEIC, JPEG, PNG)
• Burst photos that look identical
• Edited versions alongside originals

Detection strategy:

1. Immich ML duplicates: Use get_duplicates tool as a fast first pass — returns groups of visually similar assets detected by Immich's ML engine. Resolve with resolve_duplicates.
2. Exact duplicates: Same file hash (SHA-256) → safe to remove the copy
3. Format duplicates: Same timestamp + same dimensions, different format → keep highest quality (HEIC > JPEG > PNG)
4. Near-duplicates: Same timestamp + similar dimensions + high CLIP similarity → present to user
5. Burst groups: Sequential timestamps (< 2 seconds apart) + same location → let user pick best

3. Low-Quality Photo Detection

Issue	Detection	Action
Very dark	Average brightness < 20 (if available)	Flag for review
Very blurry	Motion blur EXIF hints, very low sharpness	Flag for review
Tiny resolution	Under 640x480	Flag for review
Corrupt/partial	File size anomalies, unreadable EXIF	Flag for review

Important: Some intentionally dark or blurry photos are artistic. Always flag, never auto-remove.

Cleanup Workflow

Quick Scan (recommended first step)

1. Get library statistics: total photos, videos, storage
2. Estimate screenshots: run search_smart(query="screenshot") and scan filenames (Screenshot*, Captura*) in search_metadata/list_assets results
3. Estimate duplicates: search for same-timestamp clusters
4. Report summary:

📊 Library: {total} assets ({size})
📱 Probable screenshots: ~{count} ({percentage}%)
🔄 Probable duplicates: ~{count} ({percentage}%)
📉 Low quality candidates: ~{count} ({percentage}%)
💾 Estimated space recoverable: {size}

Targeted Cleanup

After the quick scan, clean up category by category:

1. Screenshots first (highest confidence, biggest impact)

   • search_smart(query="screenshot") (CLIP) to surface visual screenshots
   • Scan filenames from search_metadata/list_assets for Screenshot*, Screen Shot*, Captura* patterns
   • Confirm borderline candidates with get_asset_info: no GPS + no lens info + dimensions matching known screen sizes
   • Present list grouped by confidence level
   • User approves → delete_assets(asset_ids, force=False) (moves to trash, recoverable)

2. Duplicates second (requires more care)

   • Find exact hash duplicates first (safest)
   • Then find format duplicates (same photo, different format)
   • Keep the highest quality version
   • User approves → delete_assets(asset_ids, force=False) to trash copies. For ML duplicates, use get_duplicates + resolve_duplicates first.

3. Low quality last (most subjective)

   • Present candidates with thumbnails if possible
   • User decides per-photo or in batches

Progress Reporting

For large cleanups, report progress every 500 assets processed:

🧹 Scanning... {processed} / {total} ({percentage}%)
Found so far: {screenshots} screenshots, {duplicates} duplicates

Cleanup by Source

Since Immich imports from specific folders, cleanup can target specific sources:

• Google Photos imports — Oldest photos, most likely to have duplicates with Apple Photos
• Apple Photos imports — Higher quality (HEIC), but overlaps with Google
• Manual imports — Manually organized, least likely to need cleanup
• Screen capture folders — ALL screenshots by definition

What NOT to Clean

• Photos with faces detected (Immich's face recognition) — may be valuable memories
• Photos in existing albums — someone already curated these
• Favorited photos — explicitly marked as wanted
• Videos — different cleanup criteria, handle separately
• Photos with GPS in known "home" locations — daily life photos may seem like junk but are memories