Zhougeng Xu

Create, update, validate, and evaluate Wisp skills. Use when authoring a project-local or installable skill, refining its trigger description, adding deterministic scripts or Python sidecars, or testing whether another Agent can follow the workflow.

Workflow & Productivity · xuzhougeng/wisp-science

Probabilistic single-cell RNA-seq with scvi-tools — scVI for a batch-corrected latent space, scANVI for semi-supervised label transfer, and Bayesian differential expression. Reach for this skill to integrate scRNA-seq batches, embed cells for clustering, transfer annotations from a reference onto a query, or score differentially expressed genes per cluster. For spatial deconvolution / mapping use the cell2location, DestVI, or Tangram methods instead.

AI & Agents · xuzhougeng/wisp-science

Use this skill when the user has attached a PDF, paper, report, or other document and the answer needs its content: summarize a section, compare sections, read specific pages, check the table of contents, or read a value off a figure. The `read` tool cannot parse PDF binary — python is the extraction path. Provides `pdf_pages` (pages as text or rendered PNGs, cached) and `pdf_outline` (embedded-bookmark TOC) in the persistent python kernel; load them once via the Kernel Sidecar exec line that `use_skill` appends. For PDF creation/manipulation, use reportlab/pypdf directly.

Content & Marketing · xuzhougeng/wisp-science

Judge and reshape the story told by a manuscript and its figure deck. Use when revising paper structure, testing whether Figure 1 is a hook, ordering figures, moving panels, identifying missing analyses, or defining the claim passed to figure-composer.

Design & Presentation · xuzhougeng/wisp-science

Compose or improve a publication-grade multi-panel scientific figure from a claim, concrete data paths, or an existing image. Use for figure outlining, parallel panel rendering, exact-grid composition, visual inspection, and adversarial figure review. Use figure-style for one standalone plot and paper-narrative for whole-paper figure ordering.

Data & Analytics · xuzhougeng/wisp-science

Find, verify, and synthesize scientific literature — from "what's the seminal paper for X" through full multi-source reviews. Covers grounding claims in real retrieved sources, avoiding fabricated citations, handling retractions, and calibrating confidence to evidence strength.

Code Review & Quality · xuzhougeng/wisp-science

Publication-grade figure correctness and legibility rules. Load before drawing any plot and call `apply_figure_style()` — sets a role-mapped font-size ladder, outward ticks, frameless legends, and 300-dpi output. The skill is a checklist, not a house look: data fidelity (claim-titles tested against every row, excluded data never enters summaries), label economy (floor and ceiling), colour threading, chart-choice-by-data-shape, layout, and a render-then-verify QA loop (bbox collision + per-panel perceptual check). Ships helpers: focal_palette, bar_with_points, strip_with_median, end_of_line_lab

Testing & QA · xuzhougeng/wisp-science

Generate a therapeutic indication dossier. Covers the patient population, epidemiology, disease biology, standard of care, regulatory precedent, and landmark clinical trials.

Other · xuzhougeng/wisp-science

Biohub ESMFold2 / ESMFold2-Fast all-atom co-folding (Candido et al. 2026, github.com/Biohub/esm). Single-sequence and MSA modes; protein, DNA, RNA, ligand (CCD/SMILES), modified residues. FoldBench Ab-Ag 50-55%, PPI 70-77% DockQ-pass. Also covers the ESMC-{300M,600M,6B} protein language models from the same release: masked-LM logits, hidden states, mutation scoring, contact prediction, and the SAE interpretability head. MIT-licensed weights on HuggingFace org `biohub`. Use this skill when: (1) Predicting complex structures with single-sequence input, (2) Validating designed binders with ESMF

AI & Agents · xuzhougeng/wisp-science

给一个研究 idea，依次执行撞车检测、安静区支撑检索、潜在挑战检索，在一份综合报告里呈现这个 idea 的立项前证据格局——撞车风险在哪、安静区里有没有文献支撑、最需要提前想清楚的挑战是什么。底层走真实检索（scimaster-cli），绝不编造引用。 **以下情况请主动触发本技能**：用户想"开题前评估一下"、"这个 idea 值不值得做"、"立项前做个全面的文献调研"、"帮我评估这个研究方向"——即使没有说"bear-propose"，只要意图是**在正式投入一个研究方向之前做综合评估**，就使用本技能。 不适用于：只查撞车（用 bear-scoop）、只找支持（用 bear-support）、只找反对（用 bear-counter）、概念地图（用 bear-map）、溯源演化史（用 bear-trace）。

Other · xuzhougeng/wisp-science

给一个主题或一篇种子论文，向前挖掘它建立在哪些前驱工作上（逐层回溯），再向后补充最新进展，讲清楚这个问题从源头到现在是怎么演化的。底层走真实检索（scimaster-cli），每个节点都锚定真实检索到的论文。 **以下情况请主动触发本技能**：用户问"这个问题是怎么来的"、"帮我溯源这个方向"、"这个领域怎么发展的"、"这篇论文是建立在谁的基础上的"、"从头讲一下这个方向的历史"、"入门一个新领域想先了解演化脉络"——即使用户没有说"bear-trace"，只要意图是**理解一个研究问题或领域的来龙去脉**，就使用本技能。加 `-d N` 控制向前溯源的层数（默认 3 层）。 不适用于：为观点找支持文献（用 bear-support）、找反对文献（用 bear-counter）、选题查重（用 bear-scoop）、概念地图（用 bear-map）。

Other · xuzhougeng/wisp-science

给一个概念，从真实检索到的论文摘要里挖出它的邻近概念，画出以该概念为中心的知识地图——每个节点都锚定真实文献，不从记忆里补节点。同时输出 Mermaid 概念图（可在 Claude Code / GitHub / Obsidian 渲染）和可截图的独立 HTML 地图，再给 3–6 篇入门推荐。 **以下情况请主动触发本技能**：用户说"帮我画一张这个概念的知识地图"、"这个词周围有哪些相关概念"、"梳理一下这个方向的概念网络"、"给我一张概念图"、"这个领域的核心概念有哪些"、"知识地图"、"概念地图"、"map out this concept"、"draw a knowledge map of X"、"what concepts surround X"、"show me the concept network around this term"、"concept map for X"——即使用户没有说"bear-map"，只要意图是**以一个概念为中心，了解它周围的知识版图**，就使用本技能。 不适用于：为观点找支持文献（用 bear-support）、找反对文献（用 bear-counter）、选题查重（用 bear-scoop）、溯源演化史（用 bear-trace）。

Workflow & Productivity · xuzhougeng/wisp-science