Data & Analytics

Use this skill for reinforcement learning tasks including training RL agents (PPO, SAC, DQN, TD3, DDPG, A2C, etc.), creating custom Gym environments, implementing callbacks for monitoring and control, using vectorized environments for parallel training, and integrating with deep RL workflows. This skill should be used when users request RL algorithm implementation, agent training, environment design, or RL experimentation.

Query Reactome REST API for pathway analysis, enrichment, gene-pathway mapping, disease pathways, molecular interactions, expression analysis, for systems biology studies.

Therapeutics Data Commons. AI-ready drug discovery datasets (ADME, toxicity, DTI), benchmarks, scaffold splits, molecular oracles, for therapeutic ML and pharmacological prediction.

Python interface to OpenMS for mass spectrometry data analysis. Use for LC-MS/MS proteomics and metabolomics workflows including file handling (mzML, mzXML, mzTab, FASTA, pepXML, protXML, mzIdentML), signal processing, feature detection, peptide identification, and quantitative analysis. Apply when working with mass spectrometry data, analyzing proteomics experiments, or processing metabolomics datasets.

Comprehensive healthcare AI toolkit for developing, testing, and deploying machine learning models with clinical data. This skill should be used when working with electronic health records (EHR), clinical prediction tasks (mortality, readmission, drug recommendation), medical coding systems (ICD, NDC, ATC), physiological signals (EEG, ECG), healthcare datasets (MIMIC-III/IV, eICU, OMOP), or implementing deep learning models for healthcare applications (RETAIN, SafeDrug, Transformer, GNN).

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.

Computational pathology toolkit for analyzing whole-slide images (WSI) and multiparametric imaging data. Use this skill when working with histopathology slides, H&E stained images, multiplex immunofluorescence (CODEX, Vectra), spatial proteomics, nucleus detection/segmentation, tissue graph construction, or training ML models on pathology data. Supports 160+ slide formats including Aperio SVS, NDPI, DICOM, OME-TIFF for digital pathology workflows.

Digital pathology image processing toolkit for whole slide images (WSI). Use this skill when working with histopathology slides, processing H&E or IHC stained tissue images, extracting tiles from gigapixel pathology images, detecting tissue regions, segmenting tissue masks, or preparing datasets for computational pathology deep learning pipelines. Applies to WSI formats (SVS, TIFF, NDPI), tile-based analysis, and histological image preprocessing workflows.

High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.

This skill should be used at the start of any computationally intensive scientific task to detect and report available system resources (CPU cores, GPUs, memory, disk space). It creates a JSON file with resource information and strategic recommendations that inform computational approach decisions such as whether to use parallel processing (joblib, multiprocessing), out-of-core computing (Dask, Zarr), GPU acceleration (PyTorch, JAX), or memory-efficient strategies. Use this skill before runni...

Spreadsheet toolkit (.xlsx/.csv). Create/edit with formulas/formatting, analyze data, visualization, recalculate formulas, for spreadsheet processing and analysis.

客户风险暴露诊断助手，适用于券商财富管理、投顾服务、客户风控、适当性管理等场景。 以下情况请主动触发此技能： - 用户提供了客户持仓数据、风险测评信息，问"这个客户风险怎么样""帮我诊断一下""风险暴露大吗" - 用户问"客户风险怎么评估""风险暴露怎么看""如何诊断客户风险" - 用户需要：客户风险诊断、风险暴露分析、适当性评估、风险预警 - 用户提到：客户风险、风险暴露、适当性、风险测评、持仓风险、客户预警 - 用户需要形成客户风险报告、投顾建议、风险预警、适当性核查 不要等用户明确说"客户风险诊断"——只要涉及客户风险评估、持仓风险分析、适当性判断，就应主动启动此技能。

用于信托领域合同与法务中的条款风险审查助手-风险提示版场景。支持结构化输入处理、规则分析与Markdown结果输出。

用于信托领域合同与法务中的条款风险审查助手-缺失项版场景。支持结构化输入处理、规则分析与Markdown结果输出。

用于信托领域合同与法务中的条款风险审查助手-冲突版场景。支持结构化输入处理、规则分析与Markdown结果输出。

用于信托领域合同与法务中的条款定位助手场景。支持结构化输入处理、规则分析与Markdown结果输出。

黑名单筛查助手，适用于券商合规管理、客户准入、反洗钱、风险监控等场景。 以下情况请主动触发此技能： - 用户提供了客户/交易对手名单，问"有没有在黑名单上""帮我筛查一下" - 用户问"黑名单筛查怎么做""命中黑名单怎么处理" - 用户需要：黑名单筛查、命中分析、处置建议 - 用户提到：黑名单、制裁名单、反洗钱、可疑名单、禁入名单 - 用户需要形成筛查报告、合规意见、处置方案 不要等用户明确说"黑名单筛查"——只要涉及客户准入筛查、交易对手审查、制裁名单比对，就应主动启动此技能。

策略回测Skill - 基于Backtrader提供量化策略回测、绩效分析、策略优化 via Backtrader/AkShare

用于风险波动的波动率计算原子 skill，适用于通用行业金融计算场景。

用于案件/项目时间线的时间线抽取原子 skill，适用于通用行业信息抽取场景。

用于时序标准化的时间序列数据整理原子 skill，适用于通用行业数据接入场景。

用于Excel/表单接入的半结构化数据接入原子 skill，适用于通用行业数据接入场景。

用于区间/年化收益的收益率计算原子 skill，适用于通用行业金融计算场景。

用于主体关系抽取的关系抽取原子 skill，适用于通用行业信息抽取场景。