Agent skill

Aris Infra

ARIS (Auto-claude-code-research-in-sleep) infrastructure setup and configuration.

Install Aris Infra

skills CLI

$ npx skills add OpenLAIR/dr-claw --skill aris-infra -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install OpenLAIR/dr-claw aris-infra --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/OpenLAIR/dr-claw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/aris-infra .claude/skills/aris-infra && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "aris-infra" agent skill from https://github.com/OpenLAIR/dr-claw/tree/main/skills/aris-infra into .claude/skills/aris-infra/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aris-infra", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/OpenLAIR/dr-claw/tree/main/skills/aris-infra

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add OpenLAIR/dr-claw --skill aris-infra -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install OpenLAIR/dr-claw aris-infra --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/OpenLAIR/dr-claw.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/aris-infra .agents/skills/aris-infra && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "aris-infra" agent skill from https://github.com/OpenLAIR/dr-claw/tree/main/skills/aris-infra into .agents/skills/aris-infra/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aris-infra", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add OpenLAIR/dr-claw --skill aris-infra -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install OpenLAIR/dr-claw aris-infra --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/OpenLAIR/dr-claw.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/aris-infra .cursor/skills/aris-infra && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "aris-infra" agent skill from https://github.com/OpenLAIR/dr-claw/tree/main/skills/aris-infra into .cursor/skills/aris-infra/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aris-infra", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/OpenLAIR/dr-claw.git --path skills/aris-infra

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add OpenLAIR/dr-claw --skill aris-infra -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install OpenLAIR/dr-claw aris-infra --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/OpenLAIR/dr-claw.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/aris-infra .gemini/skills/aris-infra && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "aris-infra" agent skill from https://github.com/OpenLAIR/dr-claw/tree/main/skills/aris-infra into .gemini/skills/aris-infra/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aris-infra", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install OpenLAIR/dr-claw aris-infra

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add OpenLAIR/dr-claw --skill aris-infra -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/OpenLAIR/dr-claw.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/aris-infra .github/skills/aris-infra && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "aris-infra" agent skill from https://github.com/OpenLAIR/dr-claw/tree/main/skills/aris-infra into .github/skills/aris-infra/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aris-infra", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add OpenLAIR/dr-claw --skill aris-infra -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install OpenLAIR/dr-claw aris-infra --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/OpenLAIR/dr-claw.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/aris-infra .opencode/skills/aris-infra && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "aris-infra" agent skill from https://github.com/OpenLAIR/dr-claw/tree/main/skills/aris-infra into .opencode/skills/aris-infra/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aris-infra", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: aris-infra
GitHub stars: 1.2k
Token cost: ~1.4k tokens
SKILL.md length: 394 words
Files: 21
Skills in repo: 36
Repo updated: Sep 17, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

ARIS (Auto-claude-code-research-in-sleep) infrastructure setup and configuration.

Works in 3 steps: Register MCP Servers → Install Python Dependencies → Verify Setup
: setting up ARIS
SKILL.md covers Quick Start (One Command), Manual Setup (if you prefer), Overview and Prerequisites, plus 6 more sections
Runs Python and Shell scripts from its folder; calls claude, npm and pip; reaches api.openai.com; needs LLM_API_KEY and GEMINI_API_KEY

What it does

Aris Infra is an agent skill from OpenLAIR/dr-claw. ARIS (Auto-claude-code-research-in-sleep) infrastructure setup and configuration. Configures MCP servers for cross-model adversarial review, installs Python tools, and validates environment. Run this first before using any other ARIS skills. Use when: setting up ARIS, configuring review servers, "aris setup", "配置ARIS".

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 27 other files (for example `mcp-servers/claude-review/server.py`, `mcp-servers/feishu-bridge/server.py` and `mcp-servers/gemini-review/server.py`).

It sits in Agent Workflows, covering MCP servers and Messaging and chat bots. It works with Model Context Protocol, Python, OpenAI and MiniMax. The repository describes itself as: A Super AI Lab with massive AI Doctors as Assistants. Best IDE for Research via AI Power. The licence is MIT.

When your agent uses it

: setting up ARIS
Configuring review servers

Example prompts

“aris setup”
“配置ARIS”
“/aris-infra”

Requirements

Python 3
Node.js
A Bash shell
A credential in LLM_API_KEY
A credential in GEMINI_API_KEY
Pre-approved tools (allowed-tools): Bash, Read, Write, Edit, Glob, Grep

Workflow steps

3 steps, taken from the step headings in SKILL.md.

Register MCP Servers
Install Python Dependencies
Verify Setup

What it can do on your machine

Read from SKILL.md and the folder at commit d51b64e. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
- Bash
- Read
- Write
- Edit
- Glob
- Grep
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships script files (Python and Shell, from the files we listed), which the agent can run.
Shell commands in SKILL.md call:
- claude
- npm
- pip
- bash
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
- api.openai.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
- LLM_API_KEY
- GEMINI_API_KEY
- GOOGLE_API_KEY
- MINIMAX_API_KEY
- FEISHU_APP_SECRET
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Aris Infra loads about 1.4k tokens when it runs. Until then it costs about 83 tokens; SKILL.md has 394 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~83
When it runs · the whole SKILL.md, loaded when a task matches: ~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
```
allowed-tools: Bash, Read, Write, Edit, Glob, Grep
```

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from OpenLAIR/dr-claw at commit d51b64e, republished under its MIT licence (© OpenLAIR). 394 words, ~1,373 tokens.

Download SKILL.mdSave it as .claude/skills/aris-infra/SKILL.md (or your agent's skills folder). This skill also uses 20 other files; get the full folder from GitHub.

name: aris-infra
description: ARIS (Auto-claude-code-research-in-sleep) infrastructure setup and configuration. Configures MCP servers for cross-model adversarial review, installs Python tools, and validates environment. Run this first before using any other ARIS skills. Use when: setting up ARIS, configuring review servers, "aris setup", "配置ARIS".
allowed-tools: Bash, Read, Write, Edit, Glob, Grep
license: MIT
metadata.author: wanshuiyin/ARIS
metadata.version: 1.0.0
metadata.repository: https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep

ARIS Infrastructure Setup

Quick Start (One Command)

bash

bash skills/aris-infra/setup.sh

This interactive script will: check prerequisites → install dependencies → register skills → configure MCP reviewer server.

Manual Setup (if you prefer)

Overview

ARIS uses cross-model adversarial review — Claude Code executes research tasks while an external LLM (GPT-5.4, Gemini, or others) provides critical review. This avoids the "self-play blind spot" where a single model reviewing its own work produces predictable feedback.

Prerequisites

Python 3.10+
Claude Code CLI
At least one external LLM API key (OpenAI, Google Gemini, or MiniMax)

Step 1: Register MCP Servers

ARIS provides 5 MCP servers. Register the ones you need:

Core: Codex (GPT-5.4 Reviewer) — Recommended

bash

npm install -g @openai/codex
claude mcp add codex -s user -- codex mcp-server

Configure in ~/.codex/config.toml:

toml

model = "gpt-5.4"

Alternative: Generic LLM Chat (Any OpenAI-compatible API)

bash

claude mcp add llm-chat -s user -- python skills/aris-infra/mcp-servers/llm-chat/server.py

Environment variables:

LLM_API_KEY — API key
LLM_BASE_URL — API base URL (e.g., https://api.openai.com/v1)
LLM_MODEL — Model name (e.g., gpt-4o)
LLM_FALLBACK_MODEL — Fallback model on 504 errors

Alternative: Gemini Review

bash

claude mcp add gemini-review -s user -- python skills/aris-infra/mcp-servers/gemini-review/server.py

Environment variables:

GEMINI_API_KEY or GOOGLE_API_KEY — Google AI API key
GEMINI_REVIEW_MODEL — Model (default: gemini-2.5-pro)

Alternative: Claude Review (Cross-session)

bash

claude mcp add claude-review -s user -- python skills/aris-infra/mcp-servers/claude-review/server.py

Uses the claude CLI binary for reviews in a separate session.

Optional: MiniMax Chat

bash

claude mcp add minimax-chat -s user -- python skills/aris-infra/mcp-servers/minimax-chat/server.py

Environment variables:

MINIMAX_API_KEY — MiniMax API key
MINIMAX_MODEL — Model (default: MiniMax-M2.7)

Optional: Feishu/Lark Notifications

bash

claude mcp add feishu-bridge -s user -- python skills/aris-infra/mcp-servers/feishu-bridge/server.py

Environment variables:

FEISHU_APP_ID, FEISHU_APP_SECRET, FEISHU_USER_ID
BRIDGE_PORT — HTTP server port (default: 9100)

Step 2: Install Python Dependencies

bash

pip install httpx arxiv requests

Step 3: Verify Setup

bash

# Check MCP servers are registered
claude mcp list

# Test a tool call
# If using Codex: mcp__codex__codex should be available
# If using llm-chat: mcp__llm-chat__chat should be available

Available Workflows

After setup, use these one-click workflow skills:

Skill	Command	Description
`aris-idea-discovery`	`/aris-idea-discovery`	Full idea pipeline: literature → ideas → novelty → review → refine
`aris-experiment-bridge`	`/aris-experiment-bridge`	Implement experiments, deploy to GPU, collect results
`aris-auto-review-loop`	`/aris-auto-review-loop`	Multi-round cross-model adversarial review
`aris-paper-writing`	`/aris-paper-writing`	Plan → figures → write LaTeX → compile → improve
`aris-rebuttal`	`/aris-rebuttal`	Parse reviews → strategy → draft → stress test
`aris-research-pipeline`	`/aris-research-pipeline`	End-to-end: idea → experiments → review → paper

Show full SKILL.md (132 more words)Show less

Bundled Resources

MCP Servers (`mcp-servers/`)

llm-chat/server.py — Generic OpenAI-compatible bridge
gemini-review/server.py — Gemini review with async jobs
claude-review/server.py — Claude Code CLI review bridge
minimax-chat/server.py — MiniMax-specific bridge
feishu-bridge/server.py — Feishu/Lark notification bridge

Python Tools (`tools/`)

arxiv_fetch.py — arXiv search and PDF download
semantic_scholar_fetch.py — Semantic Scholar search with filters
research_wiki.py — Persistent research knowledge base
watchdog.py — GPU training/download monitoring daemon

Templates (`templates/`)

RESEARCH_BRIEF_TEMPLATE.md — Research direction input
RESEARCH_CONTRACT_TEMPLATE.md — Active idea working document
EXPERIMENT_PLAN_TEMPLATE.md — Claim-driven experiment roadmap
EXPERIMENT_LOG_TEMPLATE.md — Structured experiment results
NARRATIVE_REPORT_TEMPLATE.md — Paper writing input
PAPER_PLAN_TEMPLATE.md — Claims-evidence matrix
IDEA_CANDIDATES_TEMPLATE.md — Compact top ideas
FINDINGS_TEMPLATE.md — Cross-stage discovery log

Troubleshooting

MCP server not found: Ensure claude mcp add was run with -s user flag
API key errors: Set environment variables in your shell profile (~/.zshrc or ~/.bashrc)
Python import errors: Run pip install httpx arxiv requests
Codex not installed: Run npm install -g @openai/codex

Files

SKILL.md and 20 other files in skills/aris-infra of OpenLAIR/dr-claw.

SKILL.md
mcp-servers/claude-review/server.py
mcp-servers/feishu-bridge/server.py
mcp-servers/gemini-review/server.py
mcp-servers/llm-chat/server.py
mcp-servers/minimax-chat/server.py
setup.sh
templates/EXPERIMENT_LOG_TEMPLATE.md
templates/EXPERIMENT_PLAN_TEMPLATE.md
templates/FINDINGS_TEMPLATE.md
templates/IDEA_CANDIDATES_TEMPLATE.md
templates/NARRATIVE_REPORT_TEMPLATE.md
templates/PAPER_PLAN_TEMPLATE.md
templates/README.md
… and 7 more

Open the folder on GitHubat commit d51b64e

Compare with similar skills

Aris Infra next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Aris Infra compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Aris Infra this skillOpenLAIR/dr-claw	1.2k	—	~1.4k	Automated safety check: Notes	MIT	23 days ago
Retinuejklthinking/retinue	117	—	~279	Automated safety check: Pass	MIT	3 days ago
Mcpa Certificationfancyboi999/ai-engineering-from-scratch-zh	1.2k	—	~1.4k	Automated safety check: Pass	MIT	2 days ago
Ydc Openai Agent SDK IntegrationLeoYeAI/openclaw-master-skills	2.2k	—	~4.4k	Automated safety check: Notes	MIT	2 mo ago
LangBot Plugin Developmentlangbot-app/LangBot	18k	—	~3.9k	Automated safety check: Pass	Apache-2.0	today
Opikcomet-ml/opik-mcp	220	—	~2.1k	Automated safety check: Pass	Apache-2.0	2 days ago

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Questions about Aris Infra

What does Aris Infra do?

ARIS (Auto-claude-code-research-in-sleep) infrastructure setup and configuration. Aris Infra is an agent skill from OpenLAIR/dr-claw. ARIS (Auto-claude-code-research-in-sleep) infrastructure setup and configuration.

When should I use Aris Infra?

Aris Infra fits situations like: : setting up ARIS; configuring review servers.

How do I install Aris Infra in Claude Code?

Run `npx skills add OpenLAIR/dr-claw --skill aris-infra -a claude-code`. Or copy the skill folder (skills/aris-infra in OpenLAIR/dr-claw) into .claude/skills/aris-infra in your project. Claude Code loads it when a task matches its description.

How do I install Aris Infra in Codex?

Run `npx skills add OpenLAIR/dr-claw --skill aris-infra -a codex`. Or copy the skill folder (skills/aris-infra in OpenLAIR/dr-claw) into .agents/skills/aris-infra in your project. Codex loads it when a task matches its description.

Can I use Aris Infra in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add OpenLAIR/dr-claw --skill aris-infra -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/aris-infra, .gemini/skills/aris-infra, .github/skills/aris-infra and .opencode/skills/aris-infra in your project.

What does Aris Infra need to run?

Going by SKILL.md and its folder, Aris Infra needs Python and a shell for the scripts in its folder, the command-line tools its instructions call (claude, npm, pip and bash) and credentials named LLM_API_KEY, GEMINI_API_KEY, GOOGLE_API_KEY and MINIMAX_API_KEY. Our summary lists: Python 3; Node.js; A Bash shell; A credential in LLM_API_KEY; A credential in GEMINI_API_KEY. Its frontmatter pre-approves these tools: Bash, Read, Write, Edit, Glob, Grep.

Does Aris Infra access the network?

SKILL.md names 1 domain. In commands or code: api.openai.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Aris Infra safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Aris Infra use?

Aris Infra is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Aris Infra use?

About 1.4k tokens (SKILL.md is roughly 5.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Aris Infra?

Skills that share tags, products or a category with Aris Infra: Retinue (jklthinking/retinue, 117 stars), Mcpa Certification (fancyboi999/ai-engineering-from-scratch-zh, 1.2k stars), Ydc Openai Agent SDK Integration (LeoYeAI/openclaw-master-skills, 2.2k stars) and LangBot Plugin Development (langbot-app/LangBot, 18k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Aris Infra?

OpenLAIR (a GitHub organization) maintains it in OpenLAIR/dr-claw, which has 1,155 GitHub stars. The repository holds 36 skills in this directory. The repository was last updated on September 17, 2026.

Source: OpenLAIR/dr-claw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Aris Infra

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

ARIS Infrastructure Setup

Quick Start (One Command)

Manual Setup (if you prefer)

Overview

Prerequisites

Step 1: Register MCP Servers

Core: Codex (GPT-5.4 Reviewer) — Recommended

Alternative: Generic LLM Chat (Any OpenAI-compatible API)

Alternative: Gemini Review

Alternative: Claude Review (Cross-session)

Optional: MiniMax Chat

Optional: Feishu/Lark Notifications

Step 2: Install Python Dependencies

Step 3: Verify Setup

Available Workflows

Bundled Resources

MCP Servers (mcp-servers/)

Python Tools (tools/)

Templates (templates/)

Troubleshooting

Files

Compare with similar skills

Similar skills

More from OpenLAIR/dr-claw

Related

Questions about Aris Infra

MCP Servers (`mcp-servers/`)

Python Tools (`tools/`)

Templates (`templates/`)