wanshuiyin/Auto-claude-code-research-in-sleep vs wanshuiyin/Auto-claude-code-research-in-sleep
Based on the latest public GitHub metadata. No paid placement influences this comparison.
The two products are tied on the current Radar signal.
wanshuiyin/Auto-claude-code-research-in-sleep is categorized as Agent Infrastructure; wanshuiyin/Auto-claude-code-research-in-sleep is categorized as Agent Infrastructure. Compare their product descriptions and source repositories before choosing.
| Signal | wanshuiyin/Auto-claude-code-research-in-sleep | wanshuiyin/Auto-claude-code-research-in-sleep |
|---|---|---|
| Radar Score | 90/100 | 90/100 |
| Adoption | 40/25 | 40/25 |
| Maintenance | 25/20 | 25/20 |
| Project quality | 0/20 | 0/20 |
| Agent relevance | 25/20 | 25/20 |
| Demand evidence | 0/10 | 0/10 |
| Observed momentum | 0/5 | 0/5 |
| GitHub stars | 15,760 | 15,760 |
| Category | Agent Infrastructure | Agent Infrastructure |
wanshuiyin/Auto-claude-code-research-in-sleep
ARIS ⚔️ (Auto-Research-In-Sleep) — Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in — works with Claude Code, Codex, OpenClaw, or any LLM agent.
Full analysiswanshuiyin/Auto-claude-code-research-in-sleep
ARIS ⚔️ (Auto-Research-In-Sleep) — Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in — works with Claude Code, Codex, OpenClaw, or any LLM agent.
Full analysisTransparent scoring
Adoption (25 points) uses stars and forks, maintenance (20) uses code activity, quality (20) checks license and metadata, relevance (20) checks agent focus, demand (10) uses open Issues, and momentum (5) uses star growth.