lab-codex-skills

Create, edit, replicate, and iteratively refine editable research and technical diagrams in diagrams.net/draw.io (.drawio XML) from prompts, papers, repositories, screenshots, or existing diagrams. Use when asked to generate a scientific figure, paper method diagram, ML/system architecture diagram, draw.io file, reference figure reproduction, browser screenshot feedback loop, Windows-safe draw.io preview, or layout fixes for text overlap, arrows, colors, icons, fonts, and component alignment.

Always use when user asks to create, generate, draw, or design a diagram, flowchart, architecture diagram, ER diagram, sequence diagram, class diagram, network diagram, mockup, wireframe, or UI sketch, or mentions draw.io, drawio, drawoi, .drawio files, or diagram export to PNG/SVG/PDF.

Use when the user requests diagrams, flowcharts, architecture diagrams, ER diagrams, UML / sequence / class diagrams, SysML / MBSE diagrams (block definition, internal block, requirement, parametric), BPMN business process diagrams, swimlane / cross-functional flowcharts, network topology, cloud architecture from Terraform or Kubernetes manifests, ML/DL model figures (Transformer/CNN/LSTM), mind maps, or any visualization. Also use proactively when explaining systems with 3+ components, complex data flows, or relationships that benefit from visual representation. Best suited when the diagram needs custom styling, rich shape vocabulary, swimlanes, or exportable images (PNG/SVG/PDF/JPG). Generates .drawio XML and exports locally via the native draw.io desktop CLI.

Orchestrates AI research agent workflows (paper deep-dive, survey builder, cite verify, repro pack) with durable delivery to Feishu/Lark, Notion, or Obsidian/Markdown. Use when the user asks for literature workflows, paper cards, survey/taxonomy, citation verification, reproducibility packages, cross-platform research documentation, or mentions AI Research Skills / 科研 skill 工作流.

Write source-grounded research experiment reports and experiment-log entries for ML/vision/graphics/robotics projects. Default durable destination is Notion; Feishu/Lark or Obsidian/Markdown only when the user explicitly names them. Use when the user asks to整理/撰写/补全/审查实验报告, 实验记录, 训练报告, 评测报告, ablation report, baseline report, reproduction report, Notion experiment pages, or research-document experiment summaries.

Notion document and database workflow for reading, editing, structuring, and verifying pages used by research skills (paper cards, deep dives, surveys, meeting notes, bilingual archives). Use when the user provides a notion.so URL, names Notion as the destination, asks to create or update a Notion page/database, or research-doc-workflow routes a durable write to Notion. Applies Notion-native format deltas so Feishu/Obsidian syntax does not leak into reader-facing content.

Enforces minimum-viable experimental design, evidence-based reasoning, test-driven development, tmux-first long-running sessions, Docker-first reproducible experiment environments, small incremental changes, and pre-completion review. Use whenever a research idea is being turned into an experiment, including feasibility checks, exploratory or pilot experiments, experiment design, baselines, ablations, resource budgeting, research/training code, GPU/server environments, experiment execution, or experiment documentation; also trigger when the user mentions 想法验证, 探索性实验, 预实验, 实验设计, 最小可行性, 最小可行实验, 科研开发规范, Docker first, tmux first, Docker, or tmux.

Canonical platform-neutral delivery standard for source-grounded research paper cards in Feishu/Lark, Notion, Obsidian/Markdown, surveys, deep dives, meeting notes, and project notes. Use whenever the user asks to整理/补全/生成/审核 paper card, 论文卡片, Paper Cards, literature survey cards, meeting paper cards, or deep-dive paper cards; also use when another research workflow will create or modify paper cards.

Canonical platform-neutral single-paper deep-dive delivery standard for Feishu/Lark, Notion, and Obsidian/Markdown. Use whenever the user mentions deep dive, 深读, 详细解析, detailed-read, dive into a paper, full paper reading, English original manuscript, 原文中译稿, or asks to audit/repair a deep-dive package. Produces one main entry with Paper Card, 论文解析树, and source-order 精读稿, plus complete linked artifacts for 英文原文稿 and 原文中译稿; no other skill may relax or replace this delivery contract.

Canonical platform-neutral source archive workflow for web articles, essays, research-method posts, pasted source text, browser/Obsidian web-clipper captures, and similar non-paper sources delivered to Feishu/Lark, Notion, or Obsidian/Markdown when the user asks for 原文, 提取原文, 英文原文和中文译文, English original plus Chinese translation, bilingual source archive, or says not to summarize. Use especially when another workflow would otherwise summarize or distill the source.

Run the user's daily科研经营复盘 / Daily Research Operating Review and persist it in Feishu/Lark, Notion, or Obsidian/Markdown. Use when the user says they want to start, continue, write, or organize a daily review, daily research review, 每日复盘, 科研复盘, 今日复盘, or asks to create/update a dated review page with reflection, project triage, AI ROI, simulation-ready research direction checks, and tomorrow's three key TODOs.

用 Codex 直接维护客制化 LLM Wiki / Markdown 知识库。Use when the user wants Codex to ingest sources, query with citations, lint, analyze knowledge graph, manage review/deep-research queues, or emulate nashsu/llm_wiki without an app, API key, or local model server.

Obsidian/Markdown vault workflow for reading, editing, structuring, and verifying notes used by research skills (paper cards, deep dives, surveys, wiki pages, meeting notes). Use when the user gives a vault path or .md note, names Obsidian/WorldModelVault as the destination, or research-doc-workflow routes a durable write to local Markdown. Applies Obsidian-native format deltas so Feishu/Notion syntax does not leak into reader-facing notes.

Route creation, editing, migration, and verification of research documents across Feishu/Lark, Notion, and Obsidian/Markdown while preserving content contracts, hierarchy, formulas, images, captions, links, and source provenance. Use whenever a task-specific research skill writes or normalizes paper cards, deep dives, surveys, experiment reports, bilingual source archives, daily reviews, meeting notes, or wiki pages, or whenever the user names Feishu, Notion, Obsidian, a wiki/page URL, or a local Markdown destination. Routes to feishu-doc-workflow, notion-doc-workflow, or obsidian-doc-workflow.

Build literature surveys from paper collections: taxonomy, literature tree, challenge-insight tree, novelty tree, method comparison tables, benchmark/dataset map, reading order, and Feishu/Lark, Notion, or Obsidian survey organization. Use when the user asks for Survey Builder, literature tree, challenge-insight tree, novelty tree, survey outline, or 文献综述整理.

Chinese-first technical/research writing standard for Feishu/Lark pages, Notion pages and databases, Obsidian/LLM Wiki notes, paper cards, daily reviews, meeting notes, paper deep dives, source translations, and AI-generated Chinese documents. Use whenever Codex writes, revises, audits, or translates Chinese reader-facing research/technical prose and should avoid unnecessary English phrase mixing while preserving method names, acronyms, code names, formulas, datasets, and original source text.

Feishu/Lark document and wiki workflow for reading, editing, structuring, and verifying docs, wiki pages, paper cards, meeting notes, deep dives, images, and drive-native Markdown through the local `lark-cli`. Use when the user provides a feishu.cn/larksuite.com document or wiki URL, asks to read or edit 飞书/Feishu/Lark content, asks to maintain Feishu paper cards or meeting pages, mentions 飞书文档/飞书知识库, or needs authenticated Feishu document updates with hierarchy, image, and post-write verification rules.

Use this skill whenever the user wants to learn, understand, explain, clarify, rebuild, review, or study a concept, language point, research paper, method, pipeline, mathematical idea, scientific model, programming concept, or domain vocabulary. Trigger it for natural learning requests such as "I want to understand X", "teach me X", "help me learn X", "explain X in simple words", "我想学/理解/搞懂 X", "帮我讲清楚 X", "这篇论文/这个方法我没懂", IELTS/TOEFL English learning, graduate job/internship interview preparation, research ability building, research project planning, literature survey field mapping, or Notion/Obsidian-ready note generation. The user does not need to mention Feynman or the skill name.

飞书画板：查询和编辑飞书云文档中的画板。支持导出画板为预览图片、导出原始节点结构、使用多种格式更新画板内容。 当用户需要查看画板内容、导出画板图片、编辑画板时使用此 skill。不负责：飞书云文档正文编辑、文档层级、图片/表格布局保护，这些统一交给 feishu-doc-workflow。

Use when summarizing or revising AI总结 sections in Obsidian clipping notes, especially Bilibili/video/subtitle notes under WorldModelVault. Produces concise Chinese summaries with a small vertical centered Mermaid flowchart, moderate structure, and scan-friendly emphasis without overly rich styling.

从论文 PDF Workflow：本地 MinerU 提取 Markdown，在 Cursor/Codex 会话内生成 Marp 幻灯（不使用额外 LLM/生图 API），再本地导出 pptx/PDF。Use when the user wants paper-to-slides, paper to PPT, thesis deck, or Marp export without OpenAI/Gemini/OpenRouter keys.

Orchestrator for the full academic research pipeline: research, write, integrity check, review, revise, re-review, re-revise, final integrity check, and finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 10-stage workflow with mandatory integrity verification, two-stage peer review, and reproducible quality gates. Triggers on: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publication, complete paper workflow.

Router for Academic Research Skills. Use for deep research, literature review, systematic review, academic-paper drafting, peer-review simulation, research-to-paper pipelines, claim/citation/integrity gates, experiment planning, or ARS-style workflows.

Codex-native Academic Research Skills suite for deep research, academic paper writing, manuscript review, full research-to-paper pipelines, and experiment planning or validation. Use when the user asks for deep research, literature review, systematic review, meta-analysis, research question refinement, academic paper drafting, paper revision, citation or integrity checks, reviewer simulation, peer review, editorial decision letters, research-to-paper workflows, experiment execution planning, statistical interpretation, or human study protocol support. Also use for Claude-style ARS command aliases such as /ars-plan, ars-plan, /ars-outline, /ars-abstract, /ars-lit-review, /ars-citation-check, /ars-disclosure, /ars-format-convert, /ars-revision-coach, /ars-revision, and /ars-full. This skill vendors ARS role prompts, references, templates, and shared handoff schemas under ars/.

Verify academic citations, bibliography metadata, DOI/arXiv/OpenAlex/Semantic Scholar consistency, claim-reference alignment, retraction risk, and whether cited sources actually support manuscript claims. Use for Cite Verify, citation audit, reference checking, DOI validation, claim support, broken citations, or 引用核验.

Draft, revise, or audit research grant proposals, project narratives, specific aims, significance/innovation/approach sections, broader impacts, budgets, milestones, risk plans, and reviewer-facing proposal strategy. Use for Grant Writer, Research Grant Writer, NSF/NIH-style proposals, fellowship applications, or 基金申请.

Use when collecting, OCRing, summarizing, routing, and cleaning up internship interview screenshots or research-intake screenshots from Photos albums such as Intern, Research Intake, or research intern related albums in WorldModelVault.

Handle academic LaTeX writing and template engineering: conference/journal templates, BibTeX/BibLaTeX, figures/tables, cross-references, latexmk compilation, overfull boxes, page limits, anonymous submission, Markdown/Word-to-LaTeX conversion, and compile-safe cleanup. Use when the user asks for LaTeX Writer or academic LaTeX help.

Multi-source literature search, citation verification, MeSH search strategy, citation file management (.nbib/.ris/.bib conversion), and reference management (BibTeX, related articles, ID conversion) via MCP tools (PubMed, CrossRef, arXiv, Scopus, ScienceDirect). Use when the user needs coordinated multi-step literature workflows beyond a single MCP call. Also trigger on general literature-search needs during academic writing even without the word "Nature", such as searching for papers/literature, doing a literature review, verifying a citation, converting citation files, and Chinese phrasings like 文献检索、查文献、找文献、 文献综述检索、查论文、引文核对、参考文献管理、文献去重.

Add strict Nature/CNS citations to manuscript text by splitting long passages into citable segments, searching only accepted flagship and subjournal titles from Nature Portfolio, the AAAS Science family, and Cell Press, filtering by publication time range, and exporting one reference-manager-ready output by default. Use this skill whenever the user asks to input text and automatically get references, add citations to a paragraph/manuscript, find Nature-series or CNS support for statements, create text-to-reference correspondence, "分段引用", "自动给出引用", "Nature系列引用", "CNS及子刊", "支撑文献", "补引用", "找引用", or export EndNote/RIS/ENW/Zotero RDF. Also trigger on general academic-writing citation needs even without the word "Nature", such as adding references while writing a paper, finding sources/literature for a claim, building a reference list, citation/referencing for academic writing, and Chinese phrasings like 学术写作引用、写论文加引用、写paper找文献、加参考文献、配文献、引用文献、文献支撑.

Prepare, audit, or revise Nature-ready Data Availability statements, data repository plans, dataset citations, and FAIR metadata checklists for manuscripts. Use when the user asks about Nature data availability, research data sharing, repository selection, accession numbers, restricted or sensitive data, source data, supplementary datasets, DataCite-style dataset references, FAIR metadata for academic publication, or Chinese-to-English data availability wording for Chinese-speaking authors preparing Nature-family submissions. Also trigger on general academic-writing data needs even without the word "Nature", such as writing a data availability statement for any journal, code/data sharing sections, repository selection while writing a paper, and Chinese phrasings like 数据可用性声明、数据可用性、 数据共享、代码可用性、学术写作数据声明、写数据声明、数据存放、数据仓库选择.

Submission-grade Nature/high-impact journal figure workflow for Python or R. Use whenever the user asks to create, revise, audit, or polish manuscript figures, multi-panel scientific plots, figures4papers-style matplotlib plots, or journal-ready SVG/PDF/TIFF outputs, especially for Nature-family or other high-impact journals. Before plotting, define the figure's conclusion, evidence logic, export needs, and review risks. If the user has not chosen Python or R, ask "Python or R?" and stop. Use only the selected backend for figure generation, previewing, exporting, and QA. Supports matplotlib/seaborn and ggplot2/patchwork/ComplexHeatmap. Not for dashboards or Illustrator/Figma-first infographics. Also trigger on general academic-writing figure needs even without the word "Nature", such as making figures/plots for a paper, scientific/academic plotting, data visualization for a manuscript, and Chinese phrasings like 论文配图、学术写作配图、科研绘图、科研作图、画图、作图、出图、论文图表、可视化.

Build a complete but efficient Nature-style Chinese PPTX presentation from a scientific paper, preprint, PDF, article text, abstract, figure legends, or reading notes. Use this skill whenever the user asks to make slides/PPT/PPTX for journal club, group meeting, paper sharing, thesis seminar, lab meeting, department report, or academic presentation from a research paper, not only medical papers. It identifies the paper type and argument, selects only the figures needed for the story, writes Chinese slide content and speaker notes, creates the actual .pptx deck, and runs an explicit self-review/corrective revision loop focused on figure quality, text overflow prevention, and non-template visual design before delivery. Also trigger on general academic-presentation requests even without the word "Nature", such as turning a paper into slides, building an academic talk deck, conference/defense presentations, and Chinese phrasings like 论文做PPT、论文汇报、组会PPT、文献汇报、学术汇报、做幻灯片、讲paper、读书报告PPT.

Polish, restructure, or translate academic prose into Nature-leaning English using writing-strategy principles, curated Nature/Nature Communications article patterns, and phrase-level support from Academic Phrasebank. Use whenever the user asks to polish a manuscript paragraph, abstract, introduction, results, discussion, conclusion, title, methods section, or Chinese academic draft for publication-quality English. Also covers LaTeX layout/typesetting (排版) fixes — loose or sparse pages, stranded section headings, figures that don't fill the page or split across pages, "Float too large", multi-panel figure arrangement, and Supplementary Information that looks empty — via references/latex-layout.md. Also trigger on general academic/scientific writing requests even without the word "Nature", including academic writing, scientific writing, SCI/paper writing, English manuscript polishing, language editing, proofreading, and Chinese phrasings such as 学术写作、科研写作、论文润色、写paper、SCI写作、英文论文润色、语言润色、润色、改写、学术英语、英文写作.

Build full-paper Chinese-English side-by-side, figure/table-aware, source-grounded Markdown readers for journal or conference papers from PDF, DOI, arXiv, publisher HTML, or pasted text. Use whenever the user asks to translate or read a paper, make 中英文对照/原文对照/全文翻译解读, extract figures or tables into the right positions, preserve figure/table placement near relevant prose, or keep exact source anchors for every block. This skill must not degrade into a summary-only output unless the user explicitly asks for a summary. Also trigger on general paper-reading and translation requests even without the word "Nature", such as reading/translating an academic paper, literature reading, understanding a paper, and Chinese phrasings like 读论文、精读论文、论文翻译、文献翻译、文献阅读、学术阅读、帮我读这篇文章、翻译这篇paper.

Draft, audit, or revise point-by-point reviewer response letters for Nature-family manuscript revisions. Use when the user provides reviewer comments, editor decision letters, revision notes, response drafts, or asks how to respond to major/minor revision requests, rebuttal letters, response to reviewers, peer-review reports, 审稿意见回复, 逐点回复, 修回信, 大修回复, 小修回复, or 如何回复 reviewer. Also trigger on general peer-review response needs during academic writing/revision even without the word "Nature", such as replying to reviewers for any journal, writing a rebuttal/response letter, handling revision comments, and Chinese phrasings like 回复审稿人、审稿回复、返修、 修改稿回复、写rebuttal、回应审稿意见、应对审稿.

Simulate a Nature-style reviewer assessment from the referee perspective rather than an author rebuttal. Use when the user wants a pre-submission review, reviewer report, peer-review style critique, novelty/significance/technical soundness assessment, reviewer-style manuscript evaluation, 审稿人视角评估, 预审稿意见, or Nature reviewer report. Return 3 reviewer reports plus a cross-review synthesis, grounded only in the local Nature reviewer source basis. Also trigger on general pre-submission review requests during academic writing even without the word "Nature", such as getting a mock peer review for any journal, critiquing a draft as a reviewer would, assessing novelty/rigor before submission, and Chinese phrasings like 审稿人视角、模拟审稿、预审、帮我审一下论文、投稿前自审、审稿意见模拟、找论文问题.

Router for the installed Nature-style academic workflow suite. Use when the user asks for Nature-Skills, Nature/Science/Cell style writing, high-impact journal figures, academic polishing, reviewer response, data availability, citation support, full-paper reading, paper-to-PPT, or patent drafting.

Draft, restructure, or plan Nature-style manuscript sections from author-provided claims, results, figures, notes, or Chinese drafts. Use when the user wants to write or rebuild an abstract, introduction, related-work, method, experiments, discussion, conclusion, title, or full manuscript argument rather than only polish finished prose. Also trigger on general academic-writing requests even without the word "Nature", such as writing a paper from scratch, drafting a manuscript/section, structuring a paper, and Chinese phrasings like 学术写作、科研写作、论文写作、写论文、写paper、SCI写作、帮我写论文、搭论文框架、起草论文、写引言/摘要/讨论.

Build or use a local paper RAG / paper knowledge base for PDF, arXiv, LaTeX source, MinerU Markdown, paper notes, and citation-grounded question answering. Use when the user asks for Paper RAG, local paper library search, paper QA, formula lookup, implementation checks against a paper, or multi-paper evidence retrieval.