Skip to main content

← All sources

Auto Research skills

ARIS ⚔️ (Auto-Research-In-Sleep) — Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in — works with Claude Code, Codex,.... 82 skills. skills-hub.ai mirrors 83 skills from Auto Research daily, every skill links back to its upstream GitHub source. Install with one command across Claude Code, Cursor, Codex, Windsurf, and any MCP-compatible tool.

Upstream: github.com/wanshuiyin/Auto-claude-code-research-in-sleep

Installing a Auto Research skill

Pick a skill below, then run the install command for your AI coding tool. The skills-hub CLI writes the SKILL.md to the right directory and tracks the install in .skills.json so your team gets reproducible installs.

# Install a Auto Research skill
npx @skills-hub-ai/cli install <skill-slug>

# Browse all Auto Research skills via API
curl https://skills-hub.ai/api/v1/skills?source=auto-research

# Browse all sources
open https://skills-hub.ai/sources

Top Auto Research skills

See all →

The most-installed skills from Auto Research, ranked by adoption.

  1. 01specification-writing

    1 installs

    Write the full patent specification from claims and invention disclosure. Use when user says "撰写说明书", "write specification", "写说明书", "patent description", or wants to draft the complete patent specification.

    Buildfrom Auto Research
  2. 02experiment-plan

    1 installs

    Turn a refined research proposal or method idea into a detailed, claim-driven experiment roadmap. Use after `research-refine`, or when the user asks for a detailed experiment plan, ablation matrix, evaluation protocol, run order, compute budget, or paper-ready validation that supports the core problem, novelty, simplicity, and any LLM / VLM / Diffusion / RL-based contribution.

    Buildfrom Auto Research
  3. 03openalex

    Search academic papers via OpenAlex API for open citation data, institutional affiliations, and funding information. Use when user says "openalex search", "search openalex", "open citation graph", or wants comprehensive academic metadata beyond arXiv/Semantic Scholar.

    Buildfrom Auto Research
  4. 04paper-claim-audit

    Zero-context verification that every number, comparison, and scope claim in the paper matches raw result files. Uses a fresh Codex reviewer with no prior context; base output is same-family provisional. Use when user says "审查论文数据", "check paper claims", "verify numbers", "论文数字核对", or before submission to ensure paper-to-evidence fidelity.

    Buildfrom Auto Research
  5. 05auto-review-loop

    Autonomous multi-round research review loop. Repeatedly reviews using Gemini via gemini-review MCP, implements fixes, and re-reviews until positive assessment or max rounds reached. Use when user says "auto review loop", "review until it passes", or wants autonomous iterative improvement.

    Buildfrom Auto Research
  6. 06idea-discovery

    Workflow 1: Full idea discovery pipeline. Orchestrates research-lit → idea-creator → novelty-check → research-review to go from a broad research direction to validated, pilot-tested ideas. Use when user says \"找idea全流程\", \"idea discovery pipeline\", \"从零开始找方向\", or wants the complete idea exploration workflow.

    Buildfrom Auto Research
  7. 07experiment-audit

    Audit experiment integrity before claiming results. Uses fresh-agent GPT-6-Astra review (same-family provisional in the base Codex mirror) to check for fake ground truth, score normalization fraud, phantom results, and insufficient scope. Use when user says "审计实验", "check experiment integrity", "audit results", "实验诚实度", or after experiments complete before writing claims.

    Buildfrom Auto Research
  8. 08experiment-queue

    SSH job queue for multi-seed/multi-config ML experiments with OOM-aware retry, stale-screen cleanup, and wave-transition race prevention. Use when user says "batch experiments", "队列实验", "run grid", "multi-seed sweep", "auto-chain experiments", or when /run-experiment is insufficient for 10+ jobs that need orchestration.

    Buildfrom Auto Research
  9. 09experiment-bridge

    Workflow 1.5: Bridge between idea discovery and auto review. Reads EXPERIMENT_PLAN.md, implements experiment code, deploys to GPU, collects initial results. Use when user says "实现实验", "implement experiments", "bridge", "从计划到跑实验", "deploy the plan", or has an experiment plan ready to execute.

    Buildfrom Auto Research
  10. 10alphaxiv

    Quick single-paper lookup via AlphaXiv LLM-optimized summaries with tiered source fallback. Use when user says "explain this paper", "summarize paper", pastes an arXiv/AlphaXiv URL, or provides a bare arXiv ID for quick understanding - not for broad literature search.

    Buildfrom Auto Research
  11. 11pixel-art

    Generate pixel art SVG illustrations for READMEs, docs, or slides. Use when user says "画像素图", "pixel art", "make an SVG illustration", "README hero image", or wants a cute visual.

    Buildfrom Auto Research
  12. 12ablation-planner

    Use when main results pass result-to-claim (`claim_supported = yes` or `partial`) and ablation studies are needed for paper submission. A secondary Codex agent designs ablations from a reviewer's perspective; the local executor reviews feasibility and implements.

    Buildfrom Auto Research
  13. 13claims-drafting

    Draft patent claims for an invention. Use when user says "撰写权利要求", "draft claims", "写权利要求书", "claim drafting", or wants to create patent claims. The core skill of the patent pipeline.

    Buildfrom Auto Research
  14. 14comm-lit-review

    Communications-domain literature review with Claude-style knowledge-base-first retrieval. Use when the task is about communications, wireless, networking, satellite/NTN, Wi-Fi, cellular, transport protocols, congestion control, routing, scheduling, MAC/PHY, rate adaptation, channel estimation, beamforming, or communication-system research and the user wants papers, related work, a survey, or a landscape summary.

    Buildfrom Auto Research
  15. 15deepxiv

    Search and progressively read open-access academic papers through DeepXiv. Use when the user wants layered paper access, section-level reading, trending papers, or DeepXiv-backed literature retrieval.

    Buildfrom Auto Research
  16. 16paper-writing

    Workflow 3: Full paper writing pipeline. Orchestrates paper-plan → paper-figure → paper-write → paper-compile → auto-paper-improvement-loop to go from a narrative report to a polished, submission-ready PDF. Use when user says \"写论文全流程\", \"write paper pipeline\", \"从报告到PDF\", \"paper writing\", or wants the complete paper generation workflow.

    Buildfrom Auto Research
  17. 17meta-optimize

    Analyze ARIS usage logs and propose optimizations to SKILL.md files, reviewer prompts, and workflow defaults. Outer-loop harness optimization inspired by Meta-Harness (Lee et al., 2026). Use when user says "优化技能", "meta optimize", "improve skills", "分析使用记录", or wants to optimize ARIS's own harness components based on accumulated experience.

    Buildfrom Auto Research
  18. 18figure-spec

    Generate deterministic publication-quality architecture, workflow, and pipeline diagrams from structured JSON (FigureSpec) into editable SVG. Use when user says "架构图", "workflow 图", "pipeline 图", "确定性矢量图", "figure spec", "draw architecture", or needs precise, editable, publication-ready vector diagrams. Preferred over AI illustration for formal architecture/workflow figures.

    Buildfrom Auto Research
  19. 19semantic-scholar

    Search published venue papers (IEEE, ACM, Springer, etc.) via Semantic Scholar API. Complements /arxiv (preprints) with citation counts, venue metadata, and TLDR. Use when user says "search semantic scholar", "find IEEE papers", "find journal papers", "venue papers", "citation search", or wants published literature beyond arXiv preprints.

    Buildfrom Auto Research
  20. 20paper-write

    Draft LaTeX paper section by section from an outline. Use when user says "写论文", "write paper", "draft LaTeX", "开始写", or wants to generate LaTeX content from a paper plan.

    Buildfrom Auto Research
  21. 21proof-checker

    Rigorous mathematical proof verification and fixing workflow. Reads a LaTeX proof, identifies gaps via fresh-agent Codex GPT-6-Astra ultra review, fixes each gap with full derivations, re-reviews, and generates an audit report. Base review is same-family provisional. Use when user says "检查证明", "verify proof", "proof check", "审证明", "check this proof", or wants rigorous mathematical verification of a theory paper.

    Buildfrom Auto Research
  22. 22idea-discovery-robot

    Workflow 1 adaptation for robotics and embodied AI. Orchestrates robotics-aware literature survey, idea generation, novelty check, and critical review to go from a broad robotics direction to benchmark-grounded, simulation-first ideas. Use when user says \"robotics idea discovery\", \"机器人找idea\", \"embodied AI idea\", \"机器人方向探索\", \"sim2real 选题\", or wants ideas for manipulation, locomotion, navigation, drones, humanoids, or general robot learning.

    Buildfrom Auto Research
  23. 23wiki-enrich

    Fill in the per-paper TODO sections of research-wiki/papers/<slug>.md pages that literature-ingest skills leave as bare scaffolds. Use when user says 'enrich wiki', 'fill paper TODOs', 'wiki body 補完', '把 paper 摘要寫進 wiki', 'research-wiki 自動填', or after a batch ingest that left papers/ as TODO scaffolds.

    Buildfrom Auto Research
  24. 24gemini-search

    Search research papers via Gemini for broad literature discovery. Use when user says "gemini search", "gemini papers", "search with gemini", or wants AI-powered literature discovery beyond arXiv/Semantic Scholar indexes.

    Buildfrom Auto Research

About this source

skills-hub.ai mirrors skills from 90+ official GitHub repositories every day. Each imported skill is parsed from a SKILL.md file in the source repo, gets a security scan and quality score on import, and links back to its upstream source of truth.

Last sync: Oct 2, 2026, 4:40 PM (success).

Auto Research skills, frequently asked

What are Auto Research skills?

Auto Research skills are AI coding skills published by Auto Research (ARIS ⚔️ (Auto-Research-In-Sleep) — Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in — works with Claude Code, Codex,.... 82 skills.) and mirrored daily on skills-hub.ai. They are SKILL.md files that follow the open Agent Skills standard, so they work in Claude Code, Cursor, Codex CLI, Windsurf, Copilot, and any MCP-compatible tool.

How many Auto Research skills are available?

skills-hub.ai indexes 83 skills from Auto Research, synced daily from the upstream GitHub repository (https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep).

How do I install a Auto Research skill?

Run `npx @skills-hub-ai/cli install <skill-slug>` in your project. The CLI writes the SKILL.md to the right directory for your AI tool and adds it to your `.skills.json` lockfile so your team gets the same skills at the same versions.

Are these official Auto Research skills?

Yes. Every skill from this source is mirrored from Auto Research's own GitHub repository (https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep). Each skill page links back to the upstream source of truth, so you can verify the original.