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 | Lighthouse [EMNLP2024 Demo], [ICASSP 2025], [ICASSP 2026] A user-friendly library for reproducible video moment retrieval and highlight detection. It also supports audio moment retrieval. | VLMEvalKit Open-source evaluation toolkit of large multi-modality models (LMMs), support 220+ LMMs, 80+ benchmarks | 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 |
|---|---|---|---|---|
| Quality | 71/100 Strong | 100/100 Excellent | 100/100 Excellent | 100/100 Excellent |
| Decision verdict | 70/100 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 | 254 stars Verified outcomes are shown on each skill page | 4.2K 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 |
| Freshness | Mar 26, 2026 | Jun 17, 2026 | Jul 28, 2026 | Aug 12, 2026 |
| Use-case fit | ||||
| Workflow fit | ||||
| Platform hints | Python, Computer Vision, Claude Code | Python, Computer Vision, Claude Code, OpenAI Agents | Python, Computer Vision, Claude Code | C++, Computer Vision, Claude Code |
| Warnings | No OpenAgentSkill engagement data yet | No major risk signals from current metadata | No OpenAgentSkill engagement data yet | No OpenAgentSkill engagement data yet |
| Best for | Multimodal media workflows · Claude Code teams · builders willing to evaluate younger projects | Coding agents 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 |
| Not ideal for | 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 | teams that need a vendor-supported SLA · high-compliance environments without internal security review |
| OpenAgentSkill engagement | 0 views 0 install copies | 25 views 1 install copies | 0 views 0 install copies | 0 views 0 install copies |
| Install | $ npx skills add line/lighthouse | $ npx skills add open-compass/VLMEvalKit | $ npx skills add wiltodelta/remove-ai-watermarks | $ npx skills add alicevision/AliceVision |