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
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/wanshuiyin/Auto-claude-code-research-in-sleepnpx agentmods add skills/wanshuiyin/auto-claude-code-research-in-sleep/idea-discoveryWrote 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/idea-discovery)<a href="https://agentmods.dev/skills/wanshuiyin/auto-claude-code-research-in-sleep/idea-discovery"><img src="https://agentmods.dev/badge/skills/wanshuiyin/auto-claude-code-research-in-sleep/idea-discovery/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/idea-discovery"><img src="https://agentmods.dev/badge/skills/wanshuiyin/auto-claude-code-research-in-sleep/idea-discovery.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket warn
- Snyk fail
- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to medium
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 →
- medium Rogue Agent · line 31 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
- medium Rogue Agent · line 442 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
- medium Excessive Agency · line 507 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00056 | $0.06734 |
| Opus 5 | $0.00028 | $0.03367 |
| Sonnet 5 | $0.00011 | $0.01347 |
| Haiku 4.5 | $0.00006 | $0.00673 |
Grade A, and why
idea-discovery 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 528 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Workflow 1: Idea Discovery Pipeline
Orchestrate a complete idea discovery workflow for: $ARGUMENTS
Overview
This skill chains sub-skills into a single automated pipeline:
/research-lit → /idea-creator → /novelty-check → /research-review → /research-refine-pipeline
(survey) (brainstorm) (verify novel) (critical feedback) (refine method + plan experiments)
Each phase builds on the previous one's output. The final deliverables are a validated idea-stage/IDEA_REPORT.md with ranked ideas, plus a refined proposal (refine-logs/FINAL_PROPOSAL.md) and experiment plan (refine-logs/EXPERIMENT_PLAN.md) for the top idea.
Constants
- PILOT_MAX_HOURS = 2 — Skip any pilot experiment estimated to take > 2 hours per GPU. Flag as "needs manual pilot" in the report.
- PILOT_TIMEOUT_HOURS = 3 — Hard timeout: kill any running pilot that exceeds 3 hours. Collect partial results if available.
- MAX_PILOT_IDEAS = 3 — Run pilots for at most 3 top ideas in parallel. Additional ideas are validated on paper only.
- MAX_TOTAL_GPU_HOURS = 8 — Total GPU budget across all pilots. If exceeded, skip remaining pilots and note in report.
- AUTO_PROCEED = true — When
true, checkpoints are informational: report the selected option and continue in the same turn. Set tofalseto ask for explicit user confirmation and end the turn at each selection checkpoint. - REVIEWER_MODEL =
gpt-6-astra— Model used via Codex MCP. Must be an OpenAI model (e.g.,gpt-6-astra,o3,gpt-4o). Passed to sub-skills. - OUTPUT_DIR =
idea-stage/— All idea-stage outputs go here. Create the directory if it doesn't exist. - ARXIV_DOWNLOAD = false — When
true,/research-litdownloads the top relevant arXiv PDFs during Phase 1. Whenfalse(default), only fetches metadata. Passed through to/research-lit. - COMPACT = false — When
true, generate compact summary files for short-context models and session recovery. Writesidea-stage/IDEA_CANDIDATES.md(top 3-5 ideas only) at the end of this workflow. Downstream skills read this instead of the fullidea-stage/IDEA_REPORT.md. - RENDER_HTML = true — When
true(default), auto-renderidea-stage/IDEA_REPORT.mdto HTML at workflow end via/render-html. Uses--no-review(the source MD already went through novelty + cross-model review during Phase 3). Setfalseto skip, or pass— render html: false. - REF_PAPER = false — Reference paper to base ideas on. Accepts: local PDF path, arXiv URL, or any paper URL. When set, the paper is summarized first (
idea-stage/REF_PAPER_SUMMARY.md), then idea generation uses it as context. Combine withbase repofor "improve this paper with this codebase" workflows. - RESUMABLE = true — Record stage evidence under
.aris/runs/<run_id>.jsonand require a deterministic evidence gate before declaring the final report complete.
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.
- 4d ago Changed ac2d06bde65b
- 12d ago First seen · 528 lines · 56 tokens per session scan A b5aaf4e24f19
idea-discovery is a skill published in the GitHub repository wanshuiyin/Auto-claude-code-research-in-sleep (15,970 stars, last pushed 2d ago), licensed MIT. It adds 56 tokens to every session and 6,734 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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