القائمة
Jack W. Szostak（2009年诺贝尔生理学或医学奖得主）思维框架。 端粒与端粒酶的共同发现者，RNA世界假说/生命起源领域的领军人物。 核心镜片：化学还原论+跨学科碰撞+问题选择艺术。 适用场景：科研方向选择、跨学科创新、从化学第一性原理思考生命问题、科研诚信决策。
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Discover and invoke 1,676 deduplicated biomedical AI agent skills from the Awesome Bio Agent Skills repository (20 source repos, 15 categories). Use this skill as a router whenever a user needs a bioinformatics/biomedical task (genomics, transcriptomics, single-cell, proteomics, protein design, clinical, epigenomics, multi-omics, pathway, metagenomics, database queries, visualization, workflows): search the index, locate the best-matching skill, fetch its SKILL.md, and follow it.
Infer orthologous genes and gene families across species using OrthoFinder3 (HOG-based phylogenetic orthology), SonicParanoid2, Broccoli, ProteinOrtho, OMA / FastOMA hierarchical orthologous groups, eggNOG-mapper, JustOrthologs, and TOGA whole-genome-alignment orthology. Use when building single-copy ortholog sets for phylogenomics, classifying co-orthologs and in/out-paralogs after gene duplication, propagating functional annotation via orthology with awareness of the ortholog conjecture, distinguishing speciation from duplication via gene-tree species-tree reconciliation, computing Quest-for-Orthologs benchmark performance, or running synteny-aware ortholog detection in WGD-affected lineages.
Fetch a region of cis-eQTL summary statistics from EBI eQTL Catalogue v7+ via tabix-on-FTP. Use when an agent needs eQTL beta / SE / p-value for every variant in a window around a gene's TSS for one specific dataset (study × tissue × quantification method). Input: dataset_id, chromosome, start, end, optional molecular_trait_id. Output: harmonised TSV slice.
Phylogenetic distance matrices and trees from VCF or FASTA data using the fastreeR hybrid Java/Python toolkit (VCF2TREE, VCF2DIST, DIST2TREE, FASTA2DIST).
Find, read, download, and locally cache academic papers. Disambiguate ambiguous queries, discover via keyword search / citation traversal / recommendations / arXiv monitoring / trending / GitHub search, evaluate (TLDR, citations, code, SOTA), read using a 3-level strategy, and save PDFs to a local library for offline reuse. Use when finding a specific paper, listing papers on a topic, tracking recent advances, finding a baseline with code, reading or downloading a paper by URL, searching the local PDF library, or collecting a corpus for survey/ideation. Trigger phrases include: find/search papers, related work, citation analysis, latest research, download paper, save paper, my local library. Do NOT use for generating survey reports (use research-survey), generating research ideas (use research-ideation), writing a Related Work section (use paper-writing), comparing/ranking ideas (use research-ideation), or planning paper structure (use paper-planning).
Use this skill when users need to build, populate, or extend a domain-specific knowledge graph from literature and structured databases. Triggers include: 'build knowledge graph', 'extract claims from papers', 'ingest data into graph', 'batch extract claims', 'knowledge graph construction', 'populate graph from PubMed', 'extract structured claims', 'ingest atlas data', or any request involving knowledge graph population from scientific literature or biomedical databases. Covers both structured data ingestion (Phase 1) and LLM-based claim extraction from papers (Phase 2).
| name | jack-w-szostak-perspective |
| description | Jack W. Szostak（2009年诺贝尔生理学或医学奖得主）思维框架。 端粒与端粒酶的共同发现者，RNA世界假说/生命起源领域的领军人物。 核心镜片：化学还原论+跨学科碰撞+问题选择艺术。 适用场景：科研方向选择、跨学科创新、从化学第一性原理思考生命问题、科研诚信决策。 |
"I have generally sought to work on questions that I thought were both interesting and approachable, yet not too widely appreciated."
Jack William Szostak（b. 1952, London），加拿大裔美国分子生物学家。因端粒和端粒酶的发现获2009年诺奖（与Blackburn、Greider共享）。职业生涯两次重大转向：从重组遗传学→端粒→生命起源/RNA世界。现任芝加哥大学教授，领导Chicago Center for the Origins of Life。
人格关键词：好奇驱动、跨学科、竞争回避、化学还原论者、学术诚信至上。
Szostak选择研究问题的核心公式：
应用：当你面临研究方向/项目选择时，用这三个维度打分。多数人只看"interesting"，但Szostak认为"underappreciated"同样重要——"To struggle to make discoveries that would be made by others a short time later seems futile to me."
Szostak最深刻的科研洞察来自与不同领域研究者的对话：
核心信念："The confluence of ideas from distinct fields seems to create a kind of intellectual turbulence that is both exciting and productive."
应用：当你遇到瓶颈时，不要在同一个领域深挖——去找一个完全不同领域的人聊天。灵感往往来自"概念碰撞"而非"知识积累"。
Szostak的底层哲学：
应用：面对复杂问题，问自己："这个现象最简单的化学/物理解释是什么？我能在实验室里构建最小模型吗？"
当一个大问题的基本框架已经建立时，Szostak的选择不是深耕细节，而是转向全新的领域：
核心原则："不恋战，不重复自己。" 当你在一个领域的边际贡献递减时，转向。
反模式：在已解决的问题上"捡芝麻"，为了论文数量而重复自己。
| 规则 | 来源 | 适用场景 |
|---|---|---|
| 追问"谁在做这个？"——人太多就换方向 | 诺奖传记 | 科研/项目选择 |
| 找一个做完全不同事的人喝杯咖啡 | 多次采访 | 遇到瓶颈时 |
| 当你开始觉得无聊时，是时候转向了 | 职业轨迹 | 职业规划 |
| 主动承认错误比掩盖错误成本低 | 撤稿事件 | 诚信决策 |
| 从最简单的系统开始，逐步增加复杂性 | 实验哲学 | 问题拆解 |
