Results for “data”

Adds the MariaDB JDBC driver to a build, configures connection URLs and datasources, and sets up TLS with the correct sslMode and certificate options.

Audits and improves search visibility through technical SEO, on-page optimization, structured data, Core Web Vitals, and content strategy.

Manage Kuma service mesh by discovering meshes, dataplanes, and policies via the Kuma API, then analyzing configuration and producing structured reports.

Provides a pre-built Salesforce Sales Cloud data model in Mermaid flowchart format with color coding, relationship indicators, and optional live org metadata enrichment.

Provides German data protection compliance guidance covering DSGVO, BDSG, and TDDDG, including legal bases, retention periods, cookie rules, and standard wording templates.

Provides French data protection compliance guidance covering RGPD, Loi Informatique et Libertés, and LCEN, including retention periods, cookie rules, and standard wording templates.

Implements production LLM operations: RAG pipelines, embeddings, vector databases, fine-tuning, advanced prompt engineering, cost estimation, quality evals, semantic caching, streaming, and agents.

Analyze Google Analytics data, review website performance metrics, identify traffic patterns, and suggest data-driven improvements. Use when the user asks about analytics, website metrics, traffic analysis, conversion rates, user behavior, or performance optimization.

Half-Quadratic Quantization for LLMs without calibration data. Use when quantizing models to 4/3/2-bit precision without needing calibration datasets, for fast quantization workflows, or when deploying with vLLM or HuggingFace Transformers.

Half-Quadratic Quantization for LLMs without calibration data. Use when quantizing models to 4/3/2-bit precision without needing calibration datasets, for fast quantization workflows, or when deploying with vLLM or HuggingFace Transformers.

Expert financial analyst specializing in financial modeling, forecasting, scenario analysis, and data-driven decision support. Transforms raw financial data into actionable business intelligence that drives strategic planning, investment decisions, and operational optimization.

Data Version Control for ML projects. Track large datasets and models alongside Git, build reproducible ML pipelines, and run experiments with metric comparison. Works with any storage backend including S3, GCS, Azure, and local filesystems.

Hardens code against vulnerabilities. Use when handling user input, authentication, data storage, or external integrations. Use when building any feature that accepts untrusted data, manages user sessions, or interacts with third-party services.

Create refined user personas from research data — 3 personas with JTBD, pains, gains, and unexpected insights. Use when building personas from survey data, creating user profiles from research, or segmenting users for product decisions.

Explains MariaDB-specific syntax and behavior for LOAD DATA [LOCAL] INFILE and LOAD XML, including LOCAL vs server-side file handling, security and privilege requirements, default tab/newline parsing, duplicate and strict-mode caveats, IGNORE n LINES, user-variable SET transforms, CHARACTER SET clause, and priority.

Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.

Designs and implements backend systems including REST APIs, microservices, database architectures, authentication flows, and security hardening. Use when the user asks to "design REST APIs", "optimize database queries", "implement authentication", "build microservices", "review backend code", "set up GraphQL", "handle database migrations", or "load test APIs". Covers Node.js/Express/Fastify development, PostgreSQL optimization, API security, and backend architecture patterns.

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.

Access and analyze drug information from the DrugBank database — drug properties, interactions, targets, pathways, chemical structures, and pharmacology data. Use when working with pharmaceutical data, drug discovery research, drug-drug interaction analysis, target identification, chemical similarity searches, ADMET predictions, or any task needing detailed drug and drug-target records from DrugBank. Part of the AlterLab Academic Skills suite.

Loads Therapeutics Data Commons (TDC, PyTDC) AI-ready drug-discovery datasets and benchmarks — ADME, toxicity, drug-target interaction (DTI), scaffold splits, and molecular oracles for therapeutic ML and pharmacological prediction. Use when fetching a standardized benchmark dataset, applying scaffold or cold-split evaluation, or sourcing labeled molecules for ADMET, toxicity, or DTI modeling. Sources data, splits, and oracles only — defer molecular featurization (ECFP/fingerprints), model training, and transformers to a molecular-ML skill (e.g. deepchem). Part of the AlterLab Academic Skills suite.

Use when running analytical SQL over Parquet/CSV/JSON without a warehouse, replacing pandas for data wrangling, joining S3 data in-place, building local data marts, or embedding OLAP into an app. Triggers: read_parquet/read_csv setup, partitioned dataset queries, hive partitioning, glob patterns for S3, COPY TO export, attach Postgres/MySQL, UDFs in Python/R, MotherDuck cloud sync, columnar performance vs row stores. NOT for OLTP workloads (concurrent writes), distributed analytics at petabyte scale (use Spark/Trino), or vector search (use pgvector/Lance).

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.

Econometrics skill for panel data models. Activates when the user asks about: "panel data", "fixed effects", "random effects", "Hausman test", "within estimator", "between estimator", "two-way fixed effects", "clustered standard errors panel", "FE model", "RE model", "pooled OLS", "unobserved heterogeneity", "panel regression", "first difference estimator", "entity fixed effects", "time fixed effects", "面板数据", "固定效应", "随机效应", "豪斯曼检验", "双向固定效应", "面板回归", "个体效应", "时间效应", "一阶差分"

Translate natural language into SQL queries, optimize database performance, generate migrations, explore schemas, and work with ORMs across PostgreSQL, MySQL, SQLite, and SQL Server.

Plans, configures, and manages GKE networking including private clusters, VPC-native configurations, Gateway API, DNS, ingress/egress, Dataplane V2, and IP planning.

Send custom logs to Azure Monitor Log Analytics workspace using the Logs Ingestion API and Python SDK.

Audit, plan, and implement SEO improvements across technical SEO, on-page optimization, structured data, Core Web Vitals, and content strategy.

Provides idiomatic React 18/19 patterns for hooks, server/client components, Suspense, error boundaries, forms, data fetching, state management, and accessibility-first composition.

Provides guidance and code for production AI workflows including RAG pipelines, vector databases, embedding indexing, prompt engineering, cost estimation, semantic caching, and quality evaluation.

Design secure, scalable Firebase backends with Firestore, Auth, Functions, and Storage, following best practices for security rules, data modeling, and real-time listeners.

Implement and debug network requests, API calls, and data fetching in Expo apps using fetch, React Query, SWR, and Expo Router loaders.

Generates a compact KPI digest showing how key metrics changed over a period and what's driving the movement, using Customer Journey Analytics data.

Extracts structured product data from Amazon search results, including prices, ratings, sales estimates, and shipping info, using the BrowserAct API.

Extracts structured channel data from YouTube search results via the BrowserAct API, including subscriber counts, verification status, and channel descriptions.

Process large-scale ML datasets with distributed streaming execution across CPU/GPU, supporting Parquet, CSV, JSON, images, and integration with PyTorch, TensorFlow, and Ray Train.

Audit server-side paid-media measurement, including tag management, conversion APIs, event taxonomy, deduplication, consent, hashing, data quality, and observability.