photo-rename — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited photo-rename (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Rename photo batches with consistent descriptive filenames based on EXIF data, visual content, confidence, and review-safe output.
Rename photos to descriptive real-world names using a combination of image analysis, EXIF metadata, reverse geocoding, and web research.
Use this skill when the user's message starts with rp, or when they upload photos and ask to rename, identify, or label them.
Extract GPS coordinates and date-taken metadata from each image when available.
Useful EXIF tags include:
GPS GPSLatitudeGPS GPSLatitudeRefGPS GPSLongitudeGPS GPSLongitudeRefEXIF DateTimeOriginalIf metadata extraction tooling is needed, use a lightweight EXIF reader and convert GPS rational values to decimal degrees.
Treat metadata as supporting evidence, not automatic truth. If GPS values are missing, obviously wrong, or inconsistent with the image, lower confidence and fall back to image and context based naming.
Use a combination of:
A. Image analysis
Look for:
B. GPS reverse geocoding
If GPS coordinates exist, use them to get place context through a reverse-geocoding service.
C. Web research for specificity
Combine what the image shows with the GPS location to identify the most specific likely landmark, trail, attraction, or place name.
When multiple images are provided, review them as a set before finalizing names:
If the user provides only one image, skip the grouping logic.
Event clustering: when timestamps and locations cluster (same day, same area), treat the cluster as one event and settle its naming pattern once. Every photo in the cluster inherits the event segment, such as road_to_hana or container_home_weld_day, and only the subject segment varies between files. This keeps a 40-photo hike from producing 40 unrelated names. Photos that fall outside every cluster are named individually.
Subject category rules: pick the subject segment by what dominates the frame:
summit_group_photo; never guess names from facesdog_lake_swim; use the pet's name only when the user provides itridge_view or sunset_overlookmig_welder_corner_jointsolar_rack_mounting, so files sort into a build timelineRules:
snake_casedate_location_event_subject when enough evidence existslocation_subject or date_location_subjectwaterfall, trail, overlook, or beach when it helpsOrdering guidance:
Examples:
2026_05_road_to_hana_black_sand_beach.jpgparis_eiffel_tower_night_view.jpgstewart_county_container_home_weld_frame.jpgFallback priority when confidence is low:
stewart_county_tennesseeunidentified_photo_01, unidentified_photo_02, and so onCollision handling:
_01, _02, and so onConfidence handling:
Produce a clear rename report rather than assuming the files can be renamed in place.
Example format:
PHOTO RENAME REPORT
===================
[PASS] IMG_4821.jpg -> phantom_ranch_grand_canyon.jpg
Confidence: High | GPS: 36.1069, -112.0605 | Method: GPS + vision + web search
Reason: Landmark and location agree clearly
[PASS] IMG_4822.jpg -> colorado_river_bright_angel_trail.jpg
Confidence: High | GPS: 36.0975, -112.1129 | Method: GPS + web search
Reason: GPS and trail context support the same destination
[WARN] IMG_4823.jpg -> stewart_county_tennessee.jpg
Confidence: Low | GPS: 36.3012, -87.8456 | Method: GPS reverse geocode only
Note: Could not identify a specific landmark
[FAIL] IMG_4824.jpg -> unidentified_photo_01.jpg
Confidence: None | No GPS data | Could not identify from image alone
===================
4 photos processed | 2 high confidence | 1 fallback to GPS | 1 unidentifiedFor batch requests, also include:
For large batches, open the report with a preview summary so the user reviews exceptions instead of every row:
PREVIEW: 38 photos | 2 events detected (road_to_hana: 24, kipahulu_coast: 9)
Outliers needing review: 5
- IMG_4901.jpg: GPS contradicts the cluster (300 miles away)
- IMG_4907.jpg: low confidence, subject unclear
...Outliers are anything low or no confidence, GPS that contradicts its cluster, or a name that broke the batch pattern. The user should be able to approve the batch by checking only the outliers.
If the user is not sure how to use this skill, asks what it needs, or asks for examples:
Minimum useful input:
Example prompts:
Use photo-rename to propose clean filenames for this folder of build progress photos.Help me rename these travel photos with date, place, and subject in a consistent format.Show me an example prompt for using this skill on a batch of mixed photos.~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.