gimp
GIMP CLI Image Manipulation
Manipulate images via the CLI-Anything GIMP harness. Supports single-image operations, chained session workflows, and batch processing.
Configuration
Harness paths assume the author's macOS Anaconda install layout. Adjust the listed paths to match your local install of
cli-anything-gimpif needed.
| Setting | Value |
|---|---|
| CLI tool | ~/anaconda3/bin/cli-anything-gimp |
| GIMP backend | /Applications/GIMP.app/Contents/MacOS/gimp-console |
| Supported input | PNG, JPEG, TIFF, BMP, WebP, XCF |
| Supported output | PNG, JPEG, TIFF, BMP, WebP, XCF |
Quick Start
More from adebayobraimah/install-local-skills
inkscape
|
2data-viz
Use this skill whenever the user asks to visualize data, choose charts, critique plots, build publication-quality figures, analyze ML/statistical results, plot embeddings, inspect distributions/time series/geospatial data, create dashboards, or explain visualization tradeoffs. Produces visualization plans, reproducible code, interpretation, and critique while flagging misleading encodings, artifacts, uncertainty, and scalability limits.
1plan-review-cdx
|
1plan-review
|
1mathematician
Use this skill for mathematical reasoning, theorem proving, proof checking, Lean 4 formalization, LaTeX/Markdown math exposition, counterexample search, theorem/proof decomposition, and proof repair. Use it whenever the user asks to prove, disprove, formalize, verify, analyze, or repair a mathematical claim, especially if Lean, LaTeX, assumptions, lemmas, or counterexamples are involved.
1mathematician-ai-ml
Use this skill for AI/ML mathematical reasoning, proof checking, theorem critique, Lean 4 formalization, mathlib search, LaTeX/Markdown exposition, and paper-ready mathematical writing. Use it whenever the user asks to prove, disprove, formalize, verify, derive, critique, or repair mathematics in machine learning, deep learning, reinforcement learning, optimization, probability, statistics, information theory, linear algebra, convex analysis, generalization theory, Bellman equations, MDPs/POMDPs, SGD, concentration bounds, ELBOs, KL/mutual information, or related AI/ML research claims, even if they do not explicitly mention Lean.
1