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/citation-auditWrote 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/citation-audit)<a href="https://agentmods.dev/skills/wanshuiyin/auto-claude-code-research-in-sleep/citation-audit"><img src="https://agentmods.dev/badge/skills/wanshuiyin/auto-claude-code-research-in-sleep/citation-audit/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/citation-audit"><img src="https://agentmods.dev/badge/skills/wanshuiyin/auto-claude-code-research-in-sleep/citation-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector pass
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 | $0.00086 | $0.07591 |
| Opus 5 | $0.00043 | $0.03795 |
| Sonnet 5 | $0.00017 | $0.01518 |
| Haiku 4.5 | $0.00009 | $0.00759 |
Grade A, and why
citation-audit 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- citation-audit — 97% identical, 31 lines differ
How it starts
The opening of the file, as written. The whole thing — 503 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Citation Audit
🔒 Do not wrap this skill in
/loop,/schedule, orCronCreate. It is verdict-bearing — it judges bibliographic correctness. Re-running that verdict on a timer adds no new signal (it changes only when the bibliography changes). Schedule the external wait that precedes it — bibliography finalized → then audit once. Seeshared-references/external-cadence.md.
Verify every \cite{...} in a paper against three independent layers:
- Existence — the cited paper actually exists at the claimed arXiv ID / DOI / venue.
- Metadata correctness — author names, year, venue, and title match canonical sources (DBLP, arXiv, ACL Anthology, Nature, OpenReview, etc.).
- Context appropriateness — the cited paper actually supports the claim it is being used to support in the manuscript.
This skill is the fourth layer of \aris{}'s evidence-and-claim assurance, complementing experiment-audit (code), result-to-claim (science verdict), and paper-claim-audit (numerical claims). Together they form a bottom-up integrity stack from raw evaluation code to manuscript bibliography.
When to Use This Skill
Run before submission. The right gating point is:
- After
paper-writehas produced the LaTeX draft and bib file - After
paper-claim-audithas verified numerical claims - Before final
paper-compilefor submission
Do not run this on a half-written draft — most of the work is in cross-checking each \cite against context, which is wasted on placeholder text.
What This Skill Catches
The dangerous citation problems are not wildly fake citations — those are easy to spot. The dangerous ones are:
- Wrong-context citations: real paper, but the cited claim is not what that paper actually establishes (e.g., citing Self-Refine to support "self-feedback produces correlated errors" — Self-Refine actually argues the opposite).
- Author hallucinations: anonymous-author placeholders that slipped through, missing co-authors, wrong order.
- Title drift: arXiv v1 vs v3 with different titles silently merged.
- Venue confusion: arXiv preprint cited but the official venue is now CVPR/ICML/NeurIPS — using the wrong record.
- Year mismatch: arXiv 2023 preprint with 2024 conference acceptance, year reported inconsistently.
- Phantom DOIs: DOI looks real but does not resolve.
- Self-citation drift: your own prior work cited with year off by one.
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 7f68355f009a
- 12d ago First seen · 503 lines · 86 tokens per session scan A c3e131c5747d
citation-audit 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 86 tokens to every session and 7,591 once invoked, about $0.0004 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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