hxk622
@hxk622
Public Skills
deep_research
by hxk622
深度研究能力，支持多源搜索、信息聚合、引用回溯、文档上传分析。适用于市场调研、竞品分析、学术研究、技术选型、金融投研等场景。支持上传 PDF/Excel/Word 等文档，自动转换并提取关键信息。
financial_research
by hxk622
面向股票/行业/宏观的金融研究技能，结合结构化金融数据（OpenBB/AkShare）与多源信息验证，生成带引用与免责声明的研究报告。
requesting-code-review
by hxk622
"完成任务、实现主要功能或合并前使用，验证工作是否满足要求。Use when completing tasks, implementing major features, or before merging to verify work meets requirements. Review early, review often."
ppt_generation
by hxk622
智能 PPT 生成能力，支持从研究报告一键生成演示文稿。基于 Marp Markdown 引擎，支持专业模板、数据图表、PDF 导出。适用于商业提案、项目汇报、产品介绍、培训课件、融资路演等场景。
subagent-driven-development
by hxk622
"在当前会话中执行包含独立任务的实施计划时使用。每个任务派送新的子Agent，并进行两阶段审查。Use when executing implementation plans with independent tasks - dispatch fresh subagent per task + two-stage review (spec then quality)."
brainstorming
by hxk622
"创意工作前的必备技能 - 用于探索用户意图、需求和设计。适用于创建功能、构建组件、添加新特性或修改行为。You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior."
systematic-debugging
by hxk622
"遇到任何 bug、测试失败或意外行为时使用，在提出修复方案之前进行系统化调试。Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes. Follow the four phases: Root Cause Investigation, Pattern Analysis, Hypothesis Testing, Implementation."
dispatching-parallel-agents
by hxk622
"当面临 2+ 个独立任务时使用，这些任务可以并行处理，无共享状态或顺序依赖。Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies. Dispatch one agent per independent problem domain."
executing-plans
by hxk622
"当有书面实施计划需要执行时使用，在单独会话中执行并设置审查检查点。Use when you have a written implementation plan to execute in a separate session with review checkpoints. Batch execution with checkpoints for architect review."
test-driven-development
by hxk622
"实现任何功能或修复 bug 时使用，在编写实现代码之前先写测试。Use when implementing any feature or bugfix - write the test first, watch it fail, write minimal code to pass. TDD 红绿重构循环。"
finishing-a-development-branch
by hxk622
"当实现完成、所有测试通过，需要决定如何集成工作时使用。通过展示 merge、PR 或 cleanup 的结构化选项来引导完成开发工作。Use when implementation is complete, all tests pass, and you need to decide how to integrate the work."
using-git-worktrees
by hxk622
"开始需要与当前工作区隔离的功能开发或执行实施计划前使用。创建隔离的 git worktrees，智能选择目录并进行安全验证。Use for feature work isolation or before implementation plans - creates isolated git worktrees with smart directory selection."
receiving-code-review
by hxk622
"接收代码审查反馈时使用，在实施建议之前，特别是当反馈不清晰或技术上有疑问时。需要技术严谨和验证，而不是盲目实施。Use when receiving code review feedback - requires technical rigor and verification, not blind implementation."
using-superpowers
by hxk622
"开始任何对话时使用 - 确立如何查找和使用技能。在任何响应之前（包括澄清问题）都需要调用 Skill 工具。Use when starting any conversation - establishes how to find and use skills. If a skill might apply (even 1% chance), you MUST invoke it."
verification-before-completion
by hxk622
"在声称工作完成、修复或通过之前使用，在提交或创建 PR 之前。需要运行验证命令并确认输出后才能声称成功。证据先于断言。Use when about to claim work is complete - evidence before assertions always."
writing-plans
by hxk622
"当有多步骤任务的规格或需求时使用，在动代码之前。编写全面的实施计划，假设工程师对代码库零上下文。Use when you have a spec or requirements for a multi-step task, before touching code. Write comprehensive implementation plans."
writing-skills
by hxk622
"创建新技能、编辑现有技能或部署前验证技能时使用。将 TDD 应用于流程文档编写。Use when creating new skills, editing existing skills, or verifying skills work before deployment. Writing skills IS Test-Driven Development applied to process documentation."
frontend-design
by hxk622
创建独特、生产级前端界面，避免 AI 味。用于构建 Web 组件、页面或应用，生成精致、有创意的代码。
planning-with-files
by hxk622
Implements Manus-style file-based planning for complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when starting complex multi-step tasks, research projects, or any task requiring >5 tool calls.
UI/UX Pro Max - Design Intelligence
by hxk622
arboreto
by hxk622
Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.
biopython
by hxk622
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.
biorxiv-database
by hxk622
Efficient database search tool for bioRxiv preprint server. Use this skill when searching for life sciences preprints by keywords, authors, date ranges, or categories, retrieving paper metadata, downloading PDFs, or conducting literature reviews.
brenda-database
by hxk622
Access BRENDA enzyme database via SOAP API. Retrieve kinetic parameters (Km, kcat), reaction equations, organism data, and substrate-specific enzyme information for biochemical research and metabolic pathway analysis.
geniml
by hxk622
This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.
cellxgene-census
by hxk622
Query the CELLxGENE Census (61M+ cells) programmatically. Use when you need expression data across tissues, diseases, or cell types from the largest curated single-cell atlas. Best for population-scale queries, reference atlas comparisons. For analyzing your own data use scanpy or scvi-tools.
chembl-database
by hxk622
Query ChEMBL bioactive molecules and drug discovery data. Search compounds by structure/properties, retrieve bioactivity data (IC50, Ki), find inhibitors, perform SAR studies, for medicinal chemistry.
datamol
by hxk622
Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery including SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters, use rdkit directly.
deepchem
by hxk622
Molecular ML with diverse featurizers and pre-built datasets. Use for property prediction (ADMET, toxicity) with traditional ML or GNNs when you want extensive featurization options and MoleculeNet benchmarks. Best for quick experiments with pre-trained models, diverse molecular representations. For graph-first PyTorch workflows use torchdrug; for benchmark datasets use pytdc.
anndata
by hxk622
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
denario
by hxk622
Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, executing computational experiments, performing literature searches, or generating publication-ready papers in LaTeX format. Supports end-to-end research pipelines with customizable agent orchestration.
geo-database
by hxk622
Access NCBI GEO for gene expression/genomics data. Search/download microarray and RNA-seq datasets (GSE, GSM, GPL), retrieve SOFT/Matrix files, for transcriptomics and expression analysis.
deeptools
by hxk622
NGS analysis toolkit. BAM to bigWig conversion, QC (correlation, PCA, fingerprints), heatmaps/profiles (TSS, peaks), for ChIP-seq, RNA-seq, ATAC-seq visualization.
diffdock
by hxk622
Diffusion-based molecular docking. Predict protein-ligand binding poses from PDB/SMILES, confidence scores, virtual screening, for structure-based drug design. Not for affinity prediction.
gget
by hxk622
"Fast CLI/Python queries to 20+ bioinformatics databases. Use for quick lookups: gene info, BLAST searches, AlphaFold structures, enrichment analysis. Best for interactive exploration, simple queries. For batch processing or advanced BLAST use biopython; for multi-database Python workflows use bioservices."
drugbank-database
by hxk622
Access and analyze comprehensive drug information from the DrugBank database including drug properties, interactions, targets, pathways, chemical structures, and pharmacology data. This skill should be used when working with pharmaceutical data, drug discovery research, pharmacology studies, drug-drug interaction analysis, target identification, chemical similarity searches, ADMET predictions, or any task requiring detailed drug and drug target information from DrugBank.
ena-database
by hxk622
Access European Nucleotide Archive via API/FTP. Retrieve DNA/RNA sequences, raw reads (FASTQ), genome assemblies by accession, for genomics and bioinformatics pipelines. Supports multiple formats.
pydeseq2
by hxk622
Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.
ensembl-database
by hxk622
Query Ensembl genome database REST API for 250+ species. Gene lookups, sequence retrieval, variant analysis, comparative genomics, orthologs, VEP predictions, for genomic research.
hmdb-database
by hxk622
Access Human Metabolome Database (220K+ metabolites). Search by name/ID/structure, retrieve chemical properties, biomarker data, NMR/MS spectra, pathways, for metabolomics and identification.
pysam
by hxk622
Genomic file toolkit. Read/write SAM/BAM/CRAM alignments, VCF/BCF variants, FASTA/FASTQ sequences, extract regions, calculate coverage, for NGS data processing pipelines.
esm
by hxk622
Comprehensive toolkit for protein language models including ESM3 (generative multimodal protein design across sequence, structure, and function) and ESM C (efficient protein embeddings and representations). Use this skill when working with protein sequences, structures, or function prediction; designing novel proteins; generating protein embeddings; performing inverse folding; or conducting protein engineering tasks. Supports both local model usage and cloud-based Forge API for scalable inference.
scanpy
by hxk622
Standard single-cell RNA-seq analysis pipeline. Use for QC, normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, and visualization. Best for exploratory scRNA-seq analysis with established workflows. For deep learning models use scvi-tools; for data format questions use anndata.
etetoolkit
by hxk622
Phylogenetic tree toolkit (ETE). Tree manipulation (Newick/NHX), evolutionary event detection, orthology/paralogy, NCBI taxonomy, visualization (PDF/SVG), for phylogenomics.
scikit-bio
by hxk622
Biological data toolkit. Sequence analysis, alignments, phylogenetic trees, diversity metrics (alpha/beta, UniFrac), ordination (PCoA), PERMANOVA, FASTA/Newick I/O, for microbiome analysis.
gene-database
by hxk622
Query NCBI Gene via E-utilities/Datasets API. Search by symbol/ID, retrieve gene info (RefSeqs, GO, locations, phenotypes), batch lookups, for gene annotation and functional analysis.
scvi-tools
by hxk622
Deep generative models for single-cell omics. Use when you need probabilistic batch correction (scVI), transfer learning, differential expression with uncertainty, or multi-modal integration (TOTALVI, MultiVI). Best for advanced modeling, batch effects, multimodal data. For standard analysis pipelines use scanpy.
string-database
by hxk622
Query STRING API for protein-protein interactions (59M proteins, 20B interactions). Network analysis, GO/KEGG enrichment, interaction discovery, 5000+ species, for systems biology.
uniprot-database
by hxk622
Direct REST API access to UniProt. Protein searches, FASTA retrieval, ID mapping, Swiss-Prot/TrEMBL. For Python workflows with multiple databases, prefer bioservices (unified interface to 40+ services). Use this for direct HTTP/REST work or UniProt-specific control.
image_generation
by hxk622
AI图像生成与编辑能力，基于 Nano Banana (Gemini Image) 实现文生图、图生图、图像编辑。适用于创意设计、营销素材、社交媒体内容、演示文稿配图等场景。支持多种风格、高分辨率输出（最高4K）、文字渲染、角色一致性保持。