data Skills

SpaceIndices.jl for fetching and querying space weather indices (F10.7, Ap, Kp, Dst). Use when initializing space indice...

This document describes the translation-based spaced repetition system, its data model, and study flow.

SpacetimeDB development best practices for TypeScript server modules and client SDK. This skill should be used when writ...

Generates consistent spacing tokens using base values and ratios. Use when creating margin/padding systems, gap tokens,...

Creates spacing and sizing systems including margins, padding, gaps, and consistent spacing scales. Defines spacing toke...

Industrial-strength NLP with spaCy 3.x for text processing and custom classifier training. Use when: installing spaCy, s...

Comprehensive Spanish language expert covering grammar, conversation, regional dialects, and language learning strategie...

Assists in provisioning instances and databases, designing performant schemas, and querying data in Cloud Spanner on Goo...

Use these skills when you need to explore the database structure, discover schema objects like tables and graphs, and ex...

Spansion (now Infineon) MPN encoding patterns for Flash memory and MCUs. Use when working with Spansion components or Sp...

SPARC Architecture phase specialist for system design, component architecture, interface design, scalability planning, a...

SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) is a systematic development methodology integrat...

Creates comprehensive implementation plans using the SPARC framework (Specification, Pseudocode, Architecture, Refinemen...

SPARC Pseudocode phase specialist for algorithm design, data structure selection, complexity analysis, and design patter...

SPARC Refinement phase specialist for iterative improvement through TDD, code optimization, refactoring, performance tun...

Build Spark DataFrame and SQL jobs, tune partitions and shuffle behavior, and diagnose local or cluster execution failur...

Distributed processing framework for large-scale data sets using in-memory computing.

Apache Spark skill for ETL and data transformation across all versions (3.5 LTS through 4.2). Deep expertise in DataFram...

Apache Spark distributed computing. Use for big data processing.

Use when building distributed data pipelines with Apache Spark. Covers partitioning, shuffles, skew, joins, caching, and...

PySpark fundamentals for distributed data processing.

Apache Spark 4.0.2 best practices for PySpark and Scala distributed data processing

Write PySpark and Spark SQL jobs — RDDs, DataFrames, streaming, MLlib, and cluster configuration.

Creates, configures, and updates Databricks Lakeflow Spark Declarative Pipelines (SDP/LDP) using serverless compute. Han...

Use when building Apache Spark applications, distributed data processing pipelines, or optimizing big data workloads. In...

Use when writing Spark jobs, debugging performance issues, or configuring cluster settings for Apache Spark applications...

Spark Job Creator - Auto-activating skill for Data Pipelines. Triggers on: spark job creator, spark job creator Part of...

Create spark job creator operations. Auto-activating skill for Data Pipelines. Triggers on: spark job creator, spark job...

Parse and analyze Nginx access logs using PySpark, extracting IP, timestamp, URL, and status code, then compute basic st...

Optimize Apache Spark jobs with partitioning, caching, shuffle optimization, and memory tuning. Use when improving Spark...

Spark Sql Optimizer - Auto-activating skill for Data Pipelines. Triggers on: spark sql optimizer, spark sql optimizer Pa...

Set up Spark Bitcoin L2 wallet capabilities for AI agents. Initialize wallets from mnemonic, transfer sats and tokens, c...

Guidance for writing and verifying SPARQL queries against RDF datasets, particularly university/academic ontologies. Thi...

Critical thinking partner for technical concepts and strategy. Use when the user wants to explore technical ideas, valid...

Use when the user has a proposal, position, or design and wants it adversarially pressure-tested before committing.

Evaluate sparse retrieval models on standard IR benchmarks (BEIR, MIRACL, mMARCO). Covers all IR metrics (nDCG@k, Recall...

Minimal SPARV workflow (Specify→Plan→Act→Review→Vault) with 10-point spec gate, unified journal, 2-action saves, 3-failu...

Analyze cell-cell communication in spatial transcriptomics data using ligand-receptor analysis with Squidpy. Infer inter...

Load spatial transcriptomics data from Visium, Xenium, MERFISH, Slide-seq, and other platforms using Squidpy and Spatial...

Estimate cell type composition in spatial transcriptomics spots using reference-based deconvolution. Use cell2location,...

Build spatial neighbor graphs for spatial transcriptomics data using Squidpy. Compute k-nearest neighbors, Delaunay tria...

Quality control, filtering, normalization, and feature selection for spatial transcriptomics data. Calculate QC metrics,...

Spatial registration and multi-slice alignment for spatial transcriptomics data using PASTE or STalign, with method-spec...

Compute spatial statistics for spatial transcriptomics data using Squidpy. Calculate Moran's I, Geary's C, spatial autoc...

Design and implement visionOS SwiftUI scenes that integrate RealityKit content. Use when building spatial UI with Realit...

Use when animation involves depth, perspective, volume, or three-dimensional awareness—camera moves, character positioni...

Visualize spatial transcriptomics data using Squidpy and Scanpy. Create tissue plots with gene expression, clusters, and...

SpatialData framework for handling spatial multi-modal and multi-scale data. Use this skill for questions about spatial...