ARIS is a collection of Markdown-based skills that define a workflow for autonomous machine-learning research, including idea discovery, experiment automation, and review loops. Researchers and AI coding agents use it across tools such as Claude Code, Codex, Cursor, and OpenClaw without depending on a single framework. The catalogue entries are ARIS workflow skills and agents.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill gemini-searchgit clone --depth 1 https://github.com/wanshuiyin/Auto-claude-code-research-in-sleepWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/wanshuiyin/auto-claude-code-research-in-sleep/gemini-search)<a href="https://agentmods.dev/skills/wanshuiyin/auto-claude-code-research-in-sleep/gemini-search"><img src="https://agentmods.dev/badge/skills/wanshuiyin/auto-claude-code-research-in-sleep/gemini-search/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/wanshuiyin/auto-claude-code-research-in-sleep/gemini-search"><img src="https://agentmods.dev/badge/skills/wanshuiyin/auto-claude-code-research-in-sleep/gemini-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 92 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium MCP Rug Pull · line 84 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00050 | $0.02426 |
| Opus 5 | $0.00025 | $0.01213 |
| Sonnet 5 | $0.00010 | $0.00485 |
| Haiku 4.5 | $0.00005 | $0.00243 |
Grade A, and why
gemini-search scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- gemini-search — 86% identical, 6 lines differ
How it starts
The opening of the file, as written. The whole thing — 232 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Gemini Literature Search
Search query: $ARGUMENTS
Role & Positioning
This skill uses Gemini as a broad literature discovery source:
| Skill | Source | Best for |
|---|---|---|
/arxiv |
arXiv API | Latest preprints, cutting-edge unrefereed work |
/semantic-scholar |
Semantic Scholar API | Published venue papers (IEEE, ACM, Springer) with citation counts |
/deepxiv |
DeepXiv CLI | Layered reading: search, brief, section map, section reads |
/exa-search |
Exa API | Broad web search: blogs, docs, news, companies, research papers |
/gemini-search |
Gemini MCP / CLI | AI-powered broad literature discovery — searches across multiple angles, aliases, and sub-problems |
Use Gemini when you want AI-driven discovery that goes beyond keyword matching — Gemini decomposes topics into sub-problems, explores naming variants, and surfaces papers that traditional API searches may miss.
Constants
- MAX_RESULTS = 15 — Target number of papers Gemini should find.
- MIN_YEAR = 2022 — Default minimum publication year. Override with
— year: 2020-. - DEFAULT_MODEL = auto-gemini-3 — Auto-routes within the Gemini 3 family (Pro / Flash) by server-side capacity. Required by
mcp__gemini-cli__ask-geminiandgemini-cliv0.40+; explicitgemini-3-pro-previewis silently downgraded togemini-2.5-proon OAuth-personal / Google One AI Pro accounts when capacity is exhausted. Override with— model: gemini-3-flash-preview(Gemini 3 Flash explicit, faster, higher quota), or— model: gemini-2.5-pro/gemini-2.5-flash(legacy, only for users on oldergemini-cli< v0.40). The MCP tool accepts all of these verbatim.
Overrides (append to arguments):
/gemini-search "topic" — max: 20— request up to 20 papers/gemini-search "topic" — year: 2020-— papers from 2020 onward/gemini-search "topic" — code-only— only papers with open-source code/gemini-search "topic" — venues: NeurIPS,ICML,ICLR— focus on specific venues/gemini-search "topic" — model: gemini-3-flash-preview— Gemini 3 Flash (faster, higher quota, less capable than Pro)/gemini-search "topic" — model: auto-gemini-3— auto-routes within the Gemini 3 family by load/gemini-search "topic" — model: gemini-2.5-pro— legacy (only if yourgemini-cli< v0.40)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 232 lines · 50 tokens per session scan A a8778e4e1dac
gemini-search is a skill published in the GitHub repository wanshuiyin/Auto-claude-code-research-in-sleep (16,030 stars, last pushed today), licensed MIT. It adds 50 tokens to every session and 2,426 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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