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/specification-writingWrote 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/specification-writing)<a href="https://agentmods.dev/skills/wanshuiyin/auto-claude-code-research-in-sleep/specification-writing"><img src="https://agentmods.dev/badge/skills/wanshuiyin/auto-claude-code-research-in-sleep/specification-writing/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/specification-writing"><img src="https://agentmods.dev/badge/skills/wanshuiyin/auto-claude-code-research-in-sleep/specification-writing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
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 | $0.00049 | $0.02211 |
| Opus 5.5 | $0.00020 | $0.00884 |
| Sonnet 5.5 | $0.00010 | $0.00442 |
| Haiku 4.5 | $0.00005 | $0.00221 |
Grade A, and why
specification-writing 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 6d 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:
- specification-writing — 91% identical, 23 lines differ
How it starts
The opening of the file, as written. The whole thing — 225 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Specification Writing: Section-by-Section Patent Description
Before each reviewer slot, follow Selectable Reviewers: resolve invocation →
.aris/reviewer.json→ Codex default (fresh native reviewer) withreviewer_route.pythrough the canonical helper resolver, preserving this slot's tier, fresh contexts, source/image inputs and deterministic gates. Codex examples/pins below apply only tobackend=codex; other routes use their own first-call/reply contract. Save the route and actual returned identity; unavailable selections areREVIEW_UNAVAILABLE. Classify acceptance from actual families/completion/scope. Forward invocation reviewer/model/effort overrides to reviewer-bearing children. Generation workers are unchanged.
Write the patent specification based on: $ARGUMENTS
Adapted from /paper-write for patent specifications. The specification supports the claims -- it is not a paper.
Constants
REVIEWER_MODEL = gpt-6-astra— External reviewer for specification qualityJURISDICTION = "auto"— Inherit from pipeline or detect from args;CN,US,EP,ALLOUTPUT_FORMAT = "markdown"— Markdown drafts; converted to filing format by/jurisdiction-formatOUTPUT_DIR = "patent/"— Base output directoryLANGUAGE = "auto"— Auto from jurisdiction: CN->Chinese, US/EP->English
Inputs
patent/CLAIMS.md— the drafted claims (primary source)patent/INVENTION_DISCLOSURE.md— invention decompositionpatent/PRIOR_ART_REPORT.md— for background section- User-provided figures (if any)
Shared References
Load ../shared-references/patent-writing-principles.md for specification writing rules, language guidelines, and reference numeral conventions.
Load ../shared-references/patent-format-cn.md or patent-format-us.md or patent-format-ep.md based on jurisdiction.
Workflow
Step 1: Initialize Specification Structure
Create the output directory and section files:
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.
- 6d ago Changed · +13 lines e6de83cdf45d
- 1mo ago Changed b122119891e5
- 1mo ago First seen · 212 lines · 49 tokens per session scan A 357f5a3aa493
specification-writing is a skill published in the GitHub repository wanshuiyin/Auto-claude-code-research-in-sleep (18,061 stars, last pushed yesterday), licensed MIT. It adds 49 tokens to every session and 2,211 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-03.
Other skills, from other repositories
privacy-by-design
Use when building apps that collect user data. Ensures privacy protections are built in from the start—data minimization, consent, encryption.
ethics-committee
Act as a research ethics committee — stress-test a protocol the way an IRB / REC / HREC would. Reviews informed consent, risk-benefit balance, vulnerable populations, data privacy, deception, debriefing, payment, dual-use risks, AI/LLM use in research, and equity in recruitment. Produces a committee-style decision…
freelance-dev-sow
When to use. A potential client wants a fixed-scope software project and needs a one-page SOW before they sign + pay deposit.
advogado-especialista
Advogado especialista em todas as areas do Direito brasileiro: familia, criminal, trabalhista, tributario, consumidor, imobiliario, empresarial, civil e constitucional.
advogado-criminal
Advogado criminalista especializado em Maria da Penha, violencia domestica, feminicidio, direito penal brasileiro, medidas protetivas, inquerito policial e acao penal.
fto-triage
Freedom-to-operate triage — a structured first look at potentially blocking patents, not an FTO opinion. Use when a product, process, or feature is being evaluated for blocking patents, when asked whether anything stops a launch, or to build a claim-chart first pass against the most plausible patents before patent…