Total 54,043 skills, Data Processing has 2767 skills
Showing 12 of 2767 skills
Groundwater time series analysis and modelling using transfer function noise models. Use when Claude needs to: (1) Analyze groundwater level time series, (2) Model well responses to precipitation/pumping, (3) Calibrate aquifer parameters from head data, (4) Forecast or hindcast groundwater levels, (5) Decompose hydrological signals into components, (6) Compare response functions, (7) Perform model diagnostics and uncertainty analysis.
Multi-method geophysical modelling and inversion framework. Use when Claude needs to: (1) Perform electrical resistivity tomography (ERT) inversion, (2) Run seismic refraction tomography (SRT), (3) Model induced polarization (IP) data, (4) Simulate ground penetrating radar (GPR), (5) Create finite element meshes for geophysical problems, (6) Perform joint inversions of multiple datasets, (7) Forward model geophysical responses, (8) Analyze time-lapse monitoring data.
Elliott Wave technical timing analysis for individual stocks. Identifies current wave cycle position (impulse 5-wave / corrective ABC), validates with Fibonacci ratios, confirms with momentum indicators (MACD, RSI, volume divergence), and evaluates market environment per market (HK / US / A-share / SGX). Outputs structured natural language report with Fibonacci price zones and actionable reference. Triggers on "波浪分析", "艾略特波浪", "Elliott Wave", "波浪周期", "wave analysis", "技术择时", "technical timing", stock ticker + wave/timing keywords, "现在是第几浪", "处于哪个波浪", "波浪判断", "波浪理论", "浪形分析", "波浪择时".
Analyze microbiome and metagenomics data using MGnify, GTDB, ENA, and literature tools. Search studies by biome/keyword, retrieve taxonomic profiles and functional annotations, classify genomes with GTDB taxonomy, and find related publications. Use for human gut microbiome, soil/ocean metagenomics, and environmental microbiology research.
Explain MotherDuck pricing and ROI tradeoffs. Use when an economic_buyer, technical_owner, or analytics_lead is asking about spend, budget guardrails, workload cost drivers, plan fit, or whether MotherDuck is worth adopting.
Design and operate data quality programs for financial data — golden source architecture, validation rules, data lineage, exception management, profiling, and governance. Use when building validation rules for pricing or client data pipelines, designing a data quality monitoring framework, establishing golden source designations across systems, implementing data lineage for BCBS 239 or MiFID II, investigating reconciliation breaks or billing errors traced to bad data, preparing for regulatory exams on data accuracy, building data quality scorecards, or defining data stewardship roles. Trigger on: data quality, golden source, data lineage, data validation, data profiling, exception management, data governance, BCBS 239, data completeness, data accuracy, validation rules, data anomaly, data stewardship, data quality scorecard.
Query the JASPAR database for Transcription Factor (TF) binding profiles. Use when retrieving Position Frequency Matrices (PFMs) or Position Weight Matrices (PWMs) for specific TFs, resolving gene symbols to JASPAR Matrix IDs, or getting TF metadata. Supports multiple output formats (MEME, TRANSFAC, PFM, JASPAR, YAML).
Query the STRING database for protein-protein interactions (PPIs), functional enrichment, and homology. Use when the user asks about interactions between specific proteins, interaction evidence, confidence scores, protein interaction partners, or pathway enrichments.
Use when you want to retrieve semi-quantitative protein expression and spatial localisation data from the Human Protein Atlas (HPA).
Perform relative value analysis on bonds by combining pricing, yield curve context, credit spreads, and scenario stress testing. Use when analyzing bond richness/cheapness, computing spread decomposition, comparing bonds, assessing bond value vs curves, or running rate shock scenarios.
Expert knowledge for Azure Data Explorer development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring ADX clusters, private endpoints, follower DBs, streaming ingestion, or Power BI integration, and other Azure Data Explorer related development tasks. Not for Azure Synapse Analytics (use azure-synapse-analytics), Azure Stream Analytics (use azure-stream-analytics), Azure HDInsight (use azure-hdinsight), Azure Databricks (use azure-databricks).
Query video analytics data and metrics from Elastic search via the VA-MCP server (port 9901). This includes incidents, alerts, sensor data, and metrics. Use for any question about violations, alerts, incidents, object counts, speeds, occupancy, or anything that requires looking up recorded events. This is the primary way to answer a question that requires incidents, alerts and other metrics such as people counts and violations.