nano-banana-pro-prompts-recommend-skill
AI skill for OpenClaw & Claude Code — recommend from 10000+ Nano Banana Pro (Gemini) image prompts. Smart search by use case, content remix, sample images.
Apple Photos Cleaner
Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.
SkillHub CLI
skillhub install and3rn3t/apple-photos-cleanerExaminez la source et la compatibilité, puis suivez les étapes d’installation.
Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.
Comprehensive toolkit for analyzing and cleaning up Apple Photos libraries. Goes beyond what Photos.app offers: intelligent junk detection, detailed storage analysis, duplicate finding with quality scoring, timeline recaps for storytelling, and smart export planning.
Apple Photos is great at organizing and syncing photos, but it's not so great at cleanup. This skill fills that gap:
Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.
Analyze, audit, and clean up your Apple Photos library by querying its SQLite database directly.
Goes beyond what Photos.app offers: intelligent junk detection, detailed storage analysis, duplicate finding with quality scoring, timeline recaps, people analytics, location mapping, and more.
Safety: All operations are read-only database queries. No photos are modified or deleted without explicit user action through the cleanup executor.
# Clone the repo
git clone https://github.com/and3rn3t/apple-photos-cleaner.git
cd apple-photos-cleaner
# Install dev/test dependencies
make install
Every script lives in scripts/ and outputs JSON by default (for piping / AI consumption). Add --human for readable terminal output.
| Script | Purpose |
|---|---|
library_analysis.py |
Big-picture stats: counts, storage, date ranges, quality distribution |
junk_finder.py |
Identify screenshots, low-quality photos, burst leftovers |
duplicate_finder.py |
Find duplicates via Apple's detection + timestamp/dimension matching |
storage_analyzer.py |
Breakdown by year, type, format; growth trends; storage hogs |
timeline_recap.py |
Narrative summaries of photo activity for any date range |
smart_export.py |
Plan organized exports by year/month, person, album, or location |
best_photos.py |
Surface high-quality photos you haven't favorited |
people_analyzer.py |
People co-occurrence, trends over time, best photos per person |
location_mapper.py |
Cluster GPS coordinates into locations, identify trips |
scene_search.py |
Search by ML-detected content (beach, dog, food) or browse inventory |
photo_habits.py |
Time-of-day, day-of-week, streaks, seasonal trends |
on_this_day.py |
Photos from today's date in prior years |
| `album_auditor.... |
# Apple Photos Cleaner Comprehensive toolkit for analyzing and cleaning up Apple Photos libraries. Goes beyond what Photos.app offers: intelligent junk detection, detailed storage analysis, duplicate finding with quality scoring, timeline recaps for storytelling, and smart export planning. ## Overview Apple Photos is great at organizing and syncing photos, but it's not so great at cleanup. This skill fills that gap: - **Library Analysis** — Get the big picture: counts, storage, date ranges, people, quality distribution - **Junk Finder** — Identify screenshots, low-quality photos, burst leftovers, old screenshots - **Duplicate Finder** — Find duplicates using Apple's detection + timestamp/dimension matching - **Storage Analyzer** — Detailed breakdown by year, type, file format, growth trends, storage hogs - **Timeline Recap** — Generate narrative summaries of photo activity for any date range - **Smart Export** — Plan organized exports by year/month, person, album, or location; AppleScript export - **Best Photos / Hidden Gems** — Surface high-quality photos you haven't favorited - **People Analyzer** — Deep analysis of people: co-occurrence, trends over time, best photos per person - **Location Mapper** — Cluster GPS coordinates into locations, identify trips, offline reverse geocoding - **Scene Search** — Search by ML-detected content (beach, dog, food) or generate content inventory - **Photo Habits** — Behavioral analytics: time-of-day, day-of-week, streaks, seasonal trends - **On This Day** — See what you photographed on today's date in prior years - **Album Auditor** — Find orphan photos, empty albums, overlap between albums - **Cleanup Executor** — Batch move junk to trash via AppleScript with confirmation - **Live Photo Analyzer** — Compare Live Photos vs stills, find conversion candidates, storage impact - **Shared Library** — Analyze Shared Library vs personal: contributors, content splits, storage - **iCloud Status** — Check iCloud sync coverage: synced...
# Apple Photos Cleaner Analyze, audit, and clean up your Apple Photos library by querying its SQLite database directly. Goes beyond what Photos.app offers: intelligent junk detection, detailed storage analysis, duplicate finding with quality scoring, timeline recaps, people analytics, location mapping, and more. > **Safety:** All operations are read-only database queries. No photos are modified or deleted without explicit user action through the cleanup executor. ## Requirements - **macOS** (accesses the Photos SQLite database) - **Python 3.9+** (uses stdlib only — no external runtime dependencies) ## Setup ```bash # Clone the repo git clone https://github.com/and3rn3t/apple-photos-cleaner.git cd apple-photos-cleaner # Install dev/test dependencies make install ``` ## Commands Every script lives in `scripts/` and outputs **JSON** by default (for piping / AI consumption). Add `--human` for readable terminal output. | Script | Purpose | |---|---| | `library_analysis.py` | Big-picture stats: counts, storage, date ranges, quality distribution | | `junk_finder.py` | Identify screenshots, low-quality photos, burst leftovers | | `duplicate_finder.py` | Find duplicates via Apple's detection + timestamp/dimension matching | | `storage_analyzer.py` | Breakdown by year, type, format; growth trends; storage hogs | | `timeline_recap.py` | Narrative summaries of photo activity for any date range | | `smart_export.py` | Plan organized exports by year/month, person, album, or location | | `best_photos.py` | Surface high-quality photos you haven't favorited | | `people_analyzer.py` | People co-occurrence, trends over time, best photos per person | | `location_mapper.py` | Cluster GPS coordinates into locations, identify trips | | `scene_search.py` | Search by ML-detected content (beach, dog, food) or browse inventory | | `photo_habits.py` | Time-of-day, day-of-week, streaks, seasonal trends | | `on_this_day.py` | Photos from today's date in prior years | | `album_auditor....
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