Skill comparison
Use this as a shortlist, then open the skill detail page before adopting.
Decision summary
Strongest overall
Apple Design
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Fastest prototype
Apple Design
Best first install candidate based on install readiness and adoption.
Freshest repo
iterate-ml-experiment
Most recent maintenance signal among this shortlist.
| Signal | iterate-ml-experiment Owns the iteration loop on top of an ML workspace: the `journal/JOURNAL.md` index and the per-experiment `journal/NN_short_name.md` design notes that must be drafted and approved by the user **before** `experiments/NN_short_name.py` is created. Drives the propose → iterate → approve → implement → record loop; dispatches to `iterate-from-skore` / `iterate-from-user` for sourcing. TRIGGER — any of: - A session opens in an ML workspace (whether or not `journal/` exists yet — missing/placeholder → bootstrap mode). - User says "what's next", "resume", "where were we", "let's iterate", "propose next", "first baseline". - About to create a new `experiments/NN_*.py` (the matching `journal/NN_*.md` must exist and be approved first). - User wants to record an outcome from a finished run. - User asks to compare past experiments or review what's been tried ("compare X and Y", "where are we?"). SKIP when: no `journal/` yet AND no workspace scaffold (route to `organize-ml-workspace`); the work is me | Apple Design Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces. |
|---|---|---|
| Quality | 62/100 Promising | 100/100 Excellent |
| Decision verdict | 61/100 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. |
| Adoption | 122 stars Verified outcomes are shown on each skill page | 34K stars Verified outcomes are shown on each skill page |
| Freshness | Sep 11, 2026 | Aug 21, 2026 |
| Use-case fit |
| Workflow fit |
| Platform hints | Claude Code | Claude Code, Codex, Cursor, OpenAI Agents |
| Warnings | No OpenAgentSkill engagement data yet | No OpenAgentSkill engagement data yet |
| Best for | Design and creative workflows · Claude Code teams · builders willing to evaluate younger projects | Design and creative 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 |
| OpenAgentSkill engagement | 0 views 0 install copies | 0 views 0 install copies |
| Install | $ npx skills add probabl-ai/skills --skill iterate-ml-experiment | $ npx skills@latest add emilkowalski/skills |