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lemondepat

Organise photos

by Pat · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
297
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Install in OpenClaw
/install organise-photos
Description
Organize a photo folder by cleaning non-photo files, removing bad exposures, detecting blur and burst shots, and classifying photos into numbered subfolders...
Usage Guidance
Before installing or running this skill: 1) Backup the photo folder — the skill can move or delete files. 2) Verify how the “AI vision” step is implemented: does it run locally or send images to an external API? If it sends data externally, ask for the endpoint and what credentials are required. 3) Be aware the included Python scripts will run pip install at runtime (network download and package installation into the environment); run in a sandbox or virtualenv if you are concerned. 4) Because the skill has unknown source/owner and no homepage, prefer to manually review the full SKILL.md and any scripts before use. 5) If you want to proceed, test on a small folder first and keep manual approval required for deletions.
Capability Analysis
Type: OpenClaw Skill Name: organise-photos Version: 1.0.0 The skill performs extensive file system operations, including moving and deleting files, and executes Python scripts that dynamically install dependencies via `os.system('pip install ...')`. While these actions are aligned with the stated purpose of organizing photos and include user confirmation steps, the use of shell templates (e.g., in SKILL.md steps 1, 3, and 4) with variables like `$FOLDER` and `$BAD_PHOTO` introduces a significant risk of shell injection if the agent processes maliciously crafted file or folder names. No evidence of intentional malice or data exfiltration was found, but the high-risk capabilities and inherent vulnerabilities meet the criteria for a suspicious classification.
Capability Assessment
Purpose & Capability
The name/description align with the steps in SKILL.md (scan folder, move non-photo files, detect bad exposure, blur, burst, and sort). However the description promises “AI vision analysis” but the skill metadata declares no API keys or credentials and no code files that implement a remote vision API—it's unclear whether vision analysis is local (open-source libs) or sending images to an external service. That missing detail is an unexplained gap.
Instruction Scope
The instructions run shell commands and Python scripts that will move and delete files (though deletion is gated by user confirmation). The Python code dynamically installs packages via pip at runtime, reads EXIF metadata, and iterates files in the provided folder. There is no step that exfiltrates data visible in SKILL.md, but the vague “analyze content with AI vision” step could imply network calls not described. The skill therefore performs destructive file operations and network installs — both legitimate for this purpose but worthy of caution and explicit user consent.
Install Mechanism
No declared install spec (instruction-only), which is low friction. However the embedded Python scripts call os.system('pip install ...') to fetch dependencies at runtime (Pillow, numpy, opencv-python-headless, imagehash). Dynamic pip installs are moderate risk: they download and install third‑party packages into the runtime environment and require network access.
Credentials
The skill requests no environment variables, credentials, or config paths, which is proportionate for a local organizer. But the SKILL.md's reference to AI vision is not backed by declared credentials or an explicit local implementation; if the vision step requires an external API (cloud vision, paid model), the missing credential requirements are an inconsistency. Also runtime pip installs will use network access — this is not signaled in metadata.
Persistence & Privilege
always=false and there is no indication the skill modifies other skills or system-wide config. Its runtime effects are limited to the target folder and temporary package installation; no elevated persistent privileges are requested.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install organise-photos
  3. After installation, invoke the skill by name or use /organise-photos
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Photo Folder Organizer initial public release. - Organizes photo folders by removing non-photo files, cleaning up bad exposures (near-black or near-white), and sorting images using AI analysis. - Detects and offers to remove or move non-photo files. - Identifies photos with poor exposure and allows user review before deletion. - Runs local Python scripts to detect blurry images and burst shot groups for organization. - Classifies and sorts photos into numbered, descriptive subfolders, with all interactions and folder names in the user’s language.
Metadata
Slug organise-photos
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Organise photos?

Organize a photo folder by cleaning non-photo files, removing bad exposures, detecting blur and burst shots, and classifying photos into numbered subfolders... It is an AI Agent Skill for Claude Code / OpenClaw, with 297 downloads so far.

How do I install Organise photos?

Run "/install organise-photos" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Organise photos free?

Yes, Organise photos is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Organise photos support?

Organise photos is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Organise photos?

It is built and maintained by Pat (@lemondepat); the current version is v1.0.0.

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