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-crosscheckWrote 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-crosscheck)<a href="https://agentmods.dev/skills/wanshuiyin/auto-claude-code-research-in-sleep/citation-crosscheck"><img src="https://agentmods.dev/badge/skills/wanshuiyin/auto-claude-code-research-in-sleep/citation-crosscheck/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-crosscheck"><img src="https://agentmods.dev/badge/skills/wanshuiyin/auto-claude-code-research-in-sleep/citation-crosscheck.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00160 | $0.10010 |
| Opus 5.5 | $0.00064 | $0.04004 |
| Sonnet 5.5 | $0.00032 | $0.02002 |
| Haiku 4.5 | $0.00016 | $0.01001 |
Grade A, and why
citation-crosscheck scanned grade A with 1 finding 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 7d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
2. **Decide from what the fetch(es) returned** — each terminal rests on a completed fetch: How it starts
The opening of the file, as written. The whole thing — 532 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Citation Cross-Check (double-blind bib-vs-web field audit)
🔒 Do not wrap this skill in
/loop,/schedule, orCronCreate. It is verdict-bearing — it emits a per-reference verdict that gates.bibedits (an evidence instrument, not a cross-model acquittal; see the acceptance-gate note in Step 2). Re-running it on a timer adds no signal (the verdict changes only when the bibliography changes). Schedule the external wait that precedes it: bibliography finalized → run once. Seeshared-references/external-cadence.md.
Why this exists (and how it differs from citation-audit)
citation-audit is a single cross-model reviewer that judges three things holistically:
existence, metadata, and context-fit (is the cited paper used for a claim it
actually supports?). This skill does not do context-fit. It does one thing that a
single reviewer cannot do reliably: an adversarial, double-blind, field-level diff
of the local .bib entry against an independently reconstructed record.
The failure mode it targets is the hand-entry error that survives a plausibility read:
a dropped or re-ordered author, a wrong year, a swapped venue, a DOI that
404s. A single reviewer that sees the .bib entry tends to anchor on it and rate it
"looks correct." Two agents that never see each other's output cannot anchor — a
discrepancy only survives if both independent records agree, and the verifier reports
exactly where they diverge.
In practice it catches dropped/re-ordered authors, wrong years, and bad DOIs that a
single-pass audit rated "looks clean" — while NEEDS_WEBCHECK stops it from
false-flagging a legitimate non-arXiv (blog / tech-report) citation as fabricated. Use it
in addition to citation-audit, not instead: citation-audit protects your review
score (context-fit); this protects
against the integrity red flag of a wrong or fabricated reference (existence + fields).
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 7d ago First seen · 532 lines · 160 tokens per session scan A 8556f29c677b
citation-crosscheck is a skill published in the GitHub repository wanshuiyin/Auto-claude-code-research-in-sleep (18,117 stars, last pushed 2d ago), licensed MIT. It adds 160 tokens to every session and 10,010 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-20.
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