ARIS-Code

Yang Ruofeng·wanshuiyin.ARIS-Code

A terminal-based AI research assistant built for academic researchers

ARIS-Code (Auto Research in Sleep) is a terminal-based AI research assistant built for academic researchers. Its core philosophy: - πŸ€– Executor: The primary LLM β€” writes code, surveys literature, drafts papers, plans experiments - πŸ” Reviewer: An independent LLM that adversarially critiques the Executor's output via the LlmReview tool - πŸ”„ Iterate: Executor writes β†’ Reviewer critiques β†’ Executor revises β†’ loop until quality converges With 42 bundled research skills, ARIS covers the full pipeline from idea discovery to paper submission.

winget install --id wanshuiyin.ARIS-Code --exact --source winget

Latest 0.4.27·September 18, 2026

x64β€”0EE17CE9BAE1A3B3F691B1C18184BE5BEE96884DA0C257A94B803F4784E45DBA

Details

Homepage
https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep
License
MIT
Publisher
Yang Ruofeng
Support
https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/issues
Copyright
Copyright (c) 2026 wanshuiyin

Tags

academicailarge-language-modelllmpaperresearch

Older versions (23)

0.4.26
x64β€”69E6934193593E11171507756D45DD9A64AC1617032F0A4FC27734001CD5B62B
0.4.25
x64β€”B679BD50A13DEA9933F5DC7679BEAB7D6AE0D93FB3DD35F85A2930098D2E15A9
0.4.24
x64β€”132FF34F4ECEDCB2C9E182ACBC54B68642A2606A40ED64CCCC0F507803DB3851
0.4.23
x64β€”D6057894D34CD875A882A5A1E1BBCE3F807FCA634DC5956E8692FDFA03DCB8EE
0.4.22
x64β€”74E02E06DCC9C5F5A3954B3975C6400B1A0BBC54E88F3FE7C6CB03F47F90AFB1
0.4.21
x64β€”80687F2F20BF86787ED51019A82CFA7F6888E1B718FFCA72DBA3176EB97A4F38
0.4.20
x64β€”69A9BB55E606897E7E98D7EFA9994F7E5835DF05FE1CF8F9BF37CC94DA405F6B
0.4.19
x64β€”DBE3E7683DC7E63A834A4F40A7A952629A3CE7C5E90D2E0B8F9223BE1CF8A5AF
0.4.18
x64β€”01DC042CB8FAFA6C0DBCCDEBEE06AE3824BF00AAF6B874B88906DD2983B1BD89
0.4.17
x64β€”8729F1B5D92A810446FB4130AE11C30B08309E014FB065F832098CA759FD5A53
0.4.16
x64β€”07AA836E62AEA585287B8711DFCC72AAC271B55FAA4140CA2B47224C91E97225
0.4.15
x64β€”4ACDC737F93390E35EB41F84B8D190C879E363E04A55C96E8062782836B4FE1F
0.4.14
x64β€”2F1ADD759BC00E9674CE2E573873F7DF9E525260A79D1848DB0F98058F25FD3A
0.4.13
x64β€”891CF6D80CA7D8774066E658F9B1D7DB9A95D40DEB02BB9E268AB44A241BFF05
0.4.12
x64β€”93DB5171622F578E4AEB286F230311278C0DBDB4B80DF41256806B1B2AF5D7CC
0.4.11
x64β€”4CCD9900AC4B3FFE19C7BF02C21F1EB386A750C416F7658E09B356D79985AC04
0.4.10
x64β€”56FE2AC18B8F014A2494F79E994C04DEC50EE3AB6953E24D101A87522379C8B6
0.4.9
x64β€”9E945CBA4967C9B2EEFBB2D46B45B299BB19240B2028C5995D138285E1DE1158
0.4.8
x64β€”B62D8409DBECE93C0B6CA88D367ADADD4B50BE030C12098768CB8B3CEC301E03
0.4.7
x64β€”A7F4A6673EDCDF4974643C25692226CF2ED80EA1CE7C9E5445BDA79D1BD7F92B
0.4.6
x64β€”24B0C88C0C1B96A7DA9DD3C023C122807023276E9E4C761381AE8C15B76F9D5B
0.4.5
x64β€”23CEE954AA1B13392B06248CC9CB81F868E1043202A8C39C78907A11A35387F7
0.4.4
x64β€”EB8FBA46474C2C863E51FECD581150CD9D4887C625B90D89FDA05EA645B73A56