Skill comparison
Compare agent skills before installing.
Comparing 4 skills
Use this as a shortlist, then open the skill detail page before adopting.
Decision summary
Remove AI Watermarks is the strongest overall pick here because it has a 100/100 readiness score and fits Multimodal media.
Strongest overall
Remove AI Watermarks
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Fastest prototype
Remove AI Watermarks
Best first install candidate based on install readiness and adoption.
Freshest repo
AliceVision
Most recent maintenance signal among this shortlist.
| Signal | Icevision An Agnostic Computer Vision Framework - Pluggable to any Training Library: Fastai, Pytorch-Lightning with more to come | Remove AI Watermarks AI watermark remover. CLI and Python library to strip visible and invisible AI watermarks (Gemini / Nano Banana sparkle, SynthID) and provenance metadata (C2PA, EXIF, IPTC) from images. | AliceVision 3D Computer Vision Framework | VLMEvalKit Open-source evaluation toolkit of large multi-modality models (LMMs), support 220+ LMMs, 80+ benchmarks |
|---|---|---|---|---|
| Quality | 56/100 Promising | 100/100 Excellent | 100/100 Excellent | 100/100 Excellent |
| Decision verdict | 58/100 Prototype first Prototype with this skill first; keep a fallback candidate ready. | 100/100 Production-ready Use this as a leading candidate, then validate the README and install path in your own agent stack. | 100/100 Production-ready Use this as a leading candidate, then validate the README and install path in your own agent stack. | 100/100 Production-ready Use this as a leading candidate, then validate the README and install path in your own agent stack. |
| Adoption | 867 stars Verified outcomes are shown on each skill page | 4.3K stars Verified outcomes are shown on each skill page | 3.5K stars Verified outcomes are shown on each skill page | 4.2K stars Verified outcomes are shown on each skill page |
| Freshness | Nov 26, 2024 | Jul 28, 2026 | Aug 12, 2026 | Jun 17, 2026 |
| Use-case fit | ||||
| Workflow fit | ||||
| Platform hints | Python, Computer Vision, Claude Code | Python, Computer Vision, Claude Code | C++, Computer Vision, Claude Code | Python, Computer Vision, Claude Code, OpenAI Agents |
| Warnings | Repository looks stale · No OpenAgentSkill engagement data yet | No OpenAgentSkill engagement data yet | No OpenAgentSkill engagement data yet | No OpenAgentSkill engagement data yet |
| Best for | Document processing workflows · Claude Code teams · teams that value GitHub adoption signals | Multimodal media workflows · Claude Code teams · teams that value GitHub adoption signals | Sports analytics workflows · Claude Code teams · teams that value GitHub adoption signals | Coding agents workflows · Claude Code teams · teams that value GitHub adoption signals |
| Not ideal for | teams that require actively maintained dependencies · production agents without a repository review | teams that need a vendor-supported SLA · high-compliance environments without internal security review | teams that need a vendor-supported SLA · high-compliance environments without internal security review | teams that need a vendor-supported SLA · high-compliance environments without internal security review |
| OpenAgentSkill engagement | 0 views 0 install copies | 0 views 0 install copies | 0 views 0 install copies | 0 views 0 install copies |
| Install | $ npx skills add airctic/icevision | $ npx skills add wiltodelta/remove-ai-watermarks | $ npx skills add alicevision/AliceVision | $ npx skills add open-compass/VLMEvalKit |