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wookat/ai-research-skills

SkillsMP は wookat/ai-research-skills から 60 件の skill を収集しています。skill を開くとソースと詳細を確認できます。

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収集済み skills
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このリポジトリの skills

収集済み skill 60 件中 40 件を表示しています。

職業分類
データサイエンティスト
説明

Lightweight pattern-driven research ideation with no script dependencies - generates 5-10 candidate ideas from a direction or gap matrix using proven ideation patterns, each with mechanism, falsification plan, and minimal validation experiment. Use for quick…

原文の言語: 中国語

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職業分類
データサイエンティスト
説明

Generate ONE reviewer-defensible, implementable research idea with a concrete method and falsification plan from a stated research direction. Use when the user asks for a research idea, novelty analysis, bottleneck diagnosis, or paper-shape suggestion. Skip…

原文の言語: 英語

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職業分類
データサイエンティスト
説明

Search papers across arXiv, DBLP, OpenAlex, OpenReview, Semantic Scholar, and Crossref for a given query and year range, using ./scripts/search_papers.py. Use when the user asks to find papers, related work, prior art, or recent publications on a specific…

原文の言語: 英語

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職業分類
データサイエンティスト
説明

Orchestrate the full research lifecycle (literature → ideation → novelty check → idea critique → experiments → paper writing → review simulation → rebuttal → thesis) with human decision cards between stages. Use when the user asks to start/resume a research…

原文の言語: 中国語

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職業分類
データサイエンティスト
説明

Check whether a proposed research novelty (given a problem statement and claimed idea/novelty) overlaps with existing published work. TRIGGER when the user asks to verify research novelty, check if an idea is new, compare a proposed contribution to prior art,…

原文の言語: 英語

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職業分類
その他の高等教育教員
説明

Fresh-context cross-model review protocol that prevents self-congratulatory score inflation - routes verdict-bearing reviews (idea critique, paper review, claim audits) to a different model or a zero-context fresh thread with a bias guard. Use when running…

原文の言語: 中国語

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職業分類
データサイエンティスト
説明

Select and run the correct hypothesis test based on data properties. Covers parametric/non-parametric tests, effect sizes, and multiple comparison correction.

原文の言語: 複数言語

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職業分類
ソフトウェア開発者
説明

Use when main results pass result-to-claim (claim_supported=yes or partial) and ablation studies are needed for paper submission. Do not use for general experiment design (use experiment-design).

原文の言語: 英語

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職業分類
ソフトウェア開発者
説明

Analyze ML experiment results, compute statistics, generate comparison tables and insights. Use when user says "analyze results" or needs to interpret experimental data. Do not use for run-vs-run alignment and tracking (use compare).

原文の言語: 複数言語

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職業分類
ソフトウェア開発者
説明

Autonomously improve a generated paper via GPT-5.6-Sol xhigh review → implement fixes → recompile, for 2 rounds. Use when user says "改论文", "improve paper", "论文润色循环", "auto improve", or wants to iteratively polish a generated paper.

原文の言語: 英語

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職業分類
ソフトウェア開発者
説明

Autonomous multi-round research review loop. Repeatedly reviews via external reviewer backend (Codex or manual), implements fixes, and re-reviews until positive assessment or max rounds reached. Use when user says "auto review loop", "review until it passes",…

原文の言語: 英語

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職業分類
ソフトウェア開発者
説明

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…

原文の言語: 英語

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職業分類
ソフトウェア開発者
説明

Draft a structured grant proposal from research ideas and literature. Supports KAKENHI (Japan), NSF (US), NSFC (China, including 面上/青年/优青/杰青/海外优青/重点), ERC (EU), DFG (Germany), SNSF (Switzerland), ARC (Australia), NWO (Netherlands), and generic formats. Use…

原文の言語: 英語

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職業分類
ソフトウェア開発者
説明

Adversarial attack-defense exercise on a near-final paper - a fresh reviewer writes the single strongest 200-word rejection memo, a second fresh reviewer defends point-by-point, and an adjudicator classifies each attack point as answered / partially answered…

原文の言語: 中国語

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職業分類
ソフトウェア開発者
説明

Unattended overnight research iteration - runs bounded experiment/tuning loops with objective machine-checkable stop conditions, safety rules, per-iteration logging, and a morning report, while explicitly excluding verdict-bearing decisions from automation.…

原文の言語: 中国語

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職業分類
ソフトウェア開発者
説明

Zero-context verification that every number, comparison, and scope claim in the paper matches raw result files. Uses a fresh cross-model reviewer with NO prior context to prevent confirmation bias. Use when user says "审查论文数据", "check paper claims", "verify…

原文の言語: 英語

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職業分類
ソフトウェア開発者
説明

Generate publication-quality AI illustrations for academic papers via pluggable image backends (Gemini / OpenAI gpt-image / any OpenAI-compatible endpoint, with mermaid fallback). Creates architecture diagrams, method illustrations with Claude-supervised…

原文の言語: 複数言語

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職業分類
ソフトウェア開発者
説明

Build a one-off HTML single-page academic poster with measurement-driven hard gates, real paper figures, a two-hue design-token system, and print-ready PDF via headless Chromium. Use only for "HTML 单页海报" or "one-off HTML poster" requests. Do not use for…

原文の言語: 英語

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職業分類
ソフトウェア開発者
説明

Generate conference presentation slides (beamer LaTeX → PDF + editable PPTX) from a compiled paper, with speaker notes and full talk script. Use when user says "做PPT", "做幻灯片", "make slides", "conference talk", "presentation slides", "生成slides", "写演讲稿", or…

原文の言語: 英語

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職業分類
ソフトウェア開発者
説明

Render an ARIS Markdown / JSON artifact (IDEA_REPORT, AUTO_REVIEW, KILL_ARGUMENT, PAPER_PLAN, research-wiki state, etc.) into a single-file HTML view designed for human reading. Use when the user says "渲染 HTML", "出一份 HTML 报告", "render html", "make this…

原文の言語: 英語

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職業分類
ソフトウェア開発者
説明

Use when the user wants to prepare code for open-source release, create reproducible research artifacts, or structure a repository for publication. Triggers on phrases like "publish code", "open source release", "reproducibility", "research repository", "code…

原文の言語: 複数言語

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職業分類
ソフトウェア開発者
説明

Persistent research knowledge base that accumulates papers, ideas, experiments, claims, and their relationships across the entire research lifecycle. Inspired by Karpathy's LLM Wiki pattern. Use when user says "知识库", "research wiki", "add paper", "wiki…

原文の言語: 英語

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職業分類
ソフトウェア開発者
説明

Use when experiments complete to judge what claims the results support, what they don't, and what evidence is still missing. Codex MCP evaluates results against intended claims and routes to next action (pivot, supplement, or confirm). Use after experiments…

原文の言語: 英語

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職業分類
ソフトウェア開発者
説明

Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop llm" or "llm review".

原文の言語: 英語

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職業分類
編集者
説明

Zero-context verification that every cited bibliography entry is real, correctly attributed, and actually supports the sentence citing it - catching hallucinated references, wrong metadata, and wrong-context citations with per-entry KEEP/FIX/REPLACE/REMOVE…

原文の言語: 中国語

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職業分類
データサイエンティスト
説明

Use when the user wants to analyze dataset bias, create stratified samples, evaluate fairness, or plan dataset collection. Triggers on phrases like "dataset bias", "stratified sample", "class imbalance", "data distribution", "fairness analysis", or "ethical…

原文の言語: 英語

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職業分類
データサイエンティスト
説明

Hypothesis-driven experiment loop with fair-comparison discipline - reproduce baselines, run minimal validation, iterate via hypothesis tree, and build the ablation/evidence base for a paper. Use when the user asks to run experiments, validate an idea,…

原文の言語: 中国語

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職業分類
ソフトウェア開発者
説明

Monitor running experiments, check progress, collect results. Use when user says "check results", "is it done", "monitor", or wants experiment output.

原文の言語: 英語

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職業分類
その他の高等教育教員
説明

Use when the user wants to verify paper claims against code or data, audit numerical accuracy, check formula-code alignment, or validate citation accuracy. Triggers on phrases like "verify claims", "check numbers", "do the numbers match", "formula vs code",…

原文の言語: 英語

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職業分類
テクニカルライター
説明

Improve academic paper writing quality for ML/CV/NLP-style papers with clear section structure, paragraph flow, and reviewer-facing presentation. Use when drafting or revising Abstract, Introduction, Related Work, Method, Experiments, or Conclusion; polishing…

原文の言語: 英語

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職業分類
グラフィックデザイナー
説明

Render a pre-extracted paper's structured 9-section spec (`paper_spec.md`) into a single-page HTML academic poster, fit the layout to the page via an iterative measured-fill loop, and export it to print-ready PDF + PNG thumbnail. Requires the upstream…

原文の言語: 英語

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職業分類
テクニカルライター
説明

Use this Skill to write structured academic peer-review rebuttals: point-by-point responses, tone calibration, LaTeX templates, and cover letters for re-submission. Also read references/rebuttal-strategy.md for concern triage (misunderstanding / fixable /…

原文の言語: 英語

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職業分類
ソフトウェア開発者
説明

Deploy and run ML experiments on local, remote, Vast.ai, or Modal serverless GPU. Use when user says "run experiment", "deploy to server", "跑实验", or needs to launch training jobs.

原文の言語: 英語

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職業分類
テクニカルライター
説明

Convert one or more published/submitted conference papers into a master's thesis - restructuring from paper format to thesis chapters, expanding background and related work, unifying notation, and complying with the university LaTeX template and Chinese…

原文の言語: 中国語

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職業分類
データサイエンティスト
説明

Systematic literature survey plus research-gap mining. Builds a structured literature table and a method-problem-dataset gap matrix, surfacing contradictions and unexplored cells that seed research ideas. Use when the user asks for a literature review, survey…

原文の言語: 中国語

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職業分類
データサイエンティスト
説明

Same-epoch comparison of training runs across wandb, neptune, tensorboard, or mlflow. Aligns runs at the student's current step (never current-vs-final-of-baseline) and separates proxy metrics from downstream targets. Use when the user asks to compare runs,…

原文の言語: 英語

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職業分類
データサイエンティスト
説明

Use when the user wants to design experiments, plan ablation studies, structure baselines, or create incremental evaluation strategies. Triggers on phrases like "design ablation", "plan experiment", "what experiments should I run", "baseline comparison", or…

原文の言語: 英語

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職業分類
データサイエンティスト
説明

Judge whether a research idea contains genuine insight (vs. combinatorial stitching), passes domain-intuition sanity checks, and would survive peer review. Three-layer critique - insight tests, domain pitfall checks, multi-persona reviewer simulation -…

原文の言語: 中国語

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職業分類
テクニカルライター
説明

End-to-end conference talk pipeline: paper → slide outline → Beamer + PPTX → per-page polish → assurance checks (claim / citation / anonymity) → final export and report. Default-good for academic conference talks (NeurIPS / ICML / ICLR / VALSE / 投稿 talks).…

原文の言語: 英語

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職業分類
データサイエンティスト
説明

Extract a research paper PDF into a structured set of poster-agnostic assets reusable by any downstream renderer (paper2poster, paper2blog, paper2audio, paper2video). Produces a `<outdir>/` containing the paper's full text (assets/meta/text.txt), per-figure…

原文の言語: 英語

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収集済み skill 60 件中 40 件を表示しています。