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Image Works

by haidong · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install image-works
Description
Batch image processing - compress, resize, format convert, watermark, EXIF clean, and crop. All local, no upload needed.
README (SKILL.md)

Image Workshop Skill

Local-first batch image processing toolkit. Compress, resize, convert formats, add watermarks, clean EXIF, crop — all on your machine with no image upload. Includes presets for Chinese social platforms (WeChat, Xiaohongshu, Taobao, etc.).

Core Capabilities

  • Compress: Quality target, size target, lossless, or auto-smart
  • Resize: Fixed dimensions, scale ratio, max-edge constraint, batch uniform
  • Convert: JPEG ↔ PNG ↔ WebP ↔ AVIF ↔ TIFF (bidirectional)
  • Watermark: Text or image, custom position/opacity, tile mode
  • EXIF: Remove all metadata, remove GPS only, or view metadata
  • Crop: Region crop, aspect-ratio crop (1:1, 4:3, 16:9, 3:4)
  • Presets: One-shot platform-optimized processing (WeChat, Xiaohongshu, Taobao, etc.)

Chinese Platform Presets

Platform Preset Name Specs
WeChat Moments wechat-moments 3×3 grid crop for 9-square layout
WeChat Official Account wechat-cover 900×383px (2.35:1), \x3C10MB
Xiaohongshu xiaohongshu 3:4 ratio, 1080×1440px
Taobao Main Image taobao-main 800×800px (1:1), \x3C500KB
Douyin Cover douyin-cover 1920×1080 (16:9)
Weibo Image weibo 1200px wide, \x3C20MB
Bilibili Cover bilibili-cover 16:9, 1920×1080
Avatar avatar 400×400 (1:1), \x3C200KB

Usage

clawhub run image-works --input \x3Cpaths> --op \x3Coperation> --output \x3Cdir>

Options

Option Type Default Description
--input json-array required File paths, directories, or glob patterns
--op json-array required Operations to apply (see below)
--preset string Platform preset (overrides --op)
--output.dir string ./processed/ Output directory
--output.suffix string '' Filename suffix
--output.overwrite bool false Overwrite existing files
--output.keep-structure bool true Preserve original dir structure
--recursive bool false Scan subdirectories
--max-files int 1000 Maximum files to process

Operations

Compress: {"type":"compress","quality":80,"target_size_kb":500} Resize: {"type":"resize","width":1200,"height":900,"fit":"inside"} Convert: {"type":"convert","format":"webp","quality":85} Watermark: {"type":"watermark","text":"© My Name","position":"bottom-right","opacity":0.5} EXIF: {"type":"exif","action":"remove"} Crop: {"type":"crop","aspect_ratio":"1:1"}

Operations are applied in array order.

Sample Prompts

1. Batch compress all JPEGs in a directory (most common)

clawhub run image-works --input './photos/*.jpg' \
  --op '[{"type":"compress","quality":80}]' \
  --output ./compressed/
# → 47 files processed, 156.2MB → 42.8MB (72.6% saved)

2. Xiaohongshu preset (one-shot)

clawhub run image-works --input ./product-photos/ \
  --preset xiaohongshu \
  --output ./xiaohongshu-ready/
# → Auto-resize to 3:4 (1080×1440), compress, export as JPEG

3. Add watermark with resize + format conversion

clawhub run image-works --input ./portfolio/ \
  --op '[{"type":"watermark","text":"© My Name","position":"bottom-right","opacity":0.3},{"type":"convert","format":"webp","quality":90}]' \
  --output ./watermarked-webp/
# → Watermarked + WebP converted

4. EXIF cleanup for privacy-safe sharing

clawhub run image-works --input ./vacation-photos/ \
  --op '[{"type":"exif","action":"remove"}]' \
  --output ./safe-to-share/
# → All GPS/device metadata removed

5. Batch resize for e-commerce (Taobao main image)

clawhub run image-works --input ./raw-products/ \
  --op '[{"type":"resize","width":800,"height":800,"fit":"cover"},{"type":"compress","quality":85}]' \
  --output ./taobao-ready/
# → Uniform 800×800 product images, optimized

First-Success Path

Step 1: Install → clawhub install image-works
Step 2: Run → clawhub run image-works --input ~/Pictures/ --op '{"type":"compress","quality":80}'
Step 3: See space-savings report → immediate value
Step 4: Explore presets → xiaohongshu, wechat-cover, etc.

Core Scripts

File Purpose
scripts/__init__.py Package init
scripts/scanner.py File scanner (glob, recursive)
scripts/processor.py Core processing pipeline
scripts/operations/compress.py Quality/target-size/lossless compression
scripts/operations/resize.py Dimension resize, fit modes
scripts/operations/convert.py Format conversion
scripts/operations/watermark.py Text/image/tile watermark
scripts/operations/exif.py EXIF read/remove/GPS-only
scripts/operations/crop.py Region/aspect-ratio crop
scripts/presets.py Platform preset definitions
scripts/reporter.py Processing report generator
scripts/progress.py Progress bar display
Usage Guidance
Reasonable to install if you want local batch image processing. Review input globs and directory choices before running, because the skill can scan many local image files and write processed outputs; leave overwrite disabled unless you intentionally want existing output files replaced.
Capability Assessment
Purpose & Capability
The stated purpose is local image compression, resizing, conversion, watermarking, EXIF cleanup, and cropping; the scripts implement those operations on user-supplied images.
Instruction Scope
Runtime scope is user-directed through input paths, operations, output directory, recursion, max-files, and overwrite options; recursion and overwrite are disabled by default.
Install Mechanism
Artifacts contain documentation, schemas, JSON presets, and Python processing scripts; no install hook, package-manager command, curl/wget fetch, or shell execution behavior was found.
Credentials
Local filesystem reads and output writes are proportionate for batch image processing; no network clients, subprocess execution, credential/session access, or unrelated data collection were found.
Persistence & Privilege
The skill creates output directories and processed image files, and can overwrite outputs only if the user enables that option. A user preset path constant is present but unused, with no background persistence or privilege escalation found.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install image-works
  3. After installation, invoke the skill by name or use /image-works
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of Image Workshop, a local-first batch image processing toolkit. - Supports compress, resize, format conversion, watermarking, EXIF cleaning, and cropping. - Includes ready-to-use presets for major Chinese social platforms (WeChat, Xiaohongshu, Taobao, etc.). - All processing is performed locally—no image upload required. - Flexible operation via command line with detailed options and operation chaining. - Provides user-friendly prompts, sample usage, and clear processing reports.
Metadata
Slug image-works
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Image Works?

Batch image processing - compress, resize, format convert, watermark, EXIF clean, and crop. All local, no upload needed. It is an AI Agent Skill for Claude Code / OpenClaw, with 32 downloads so far.

How do I install Image Works?

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

Is Image Works free?

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

Which platforms does Image Works support?

Image Works is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Image Works?

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

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