Total 54,172 skills, Data Processing has 2771 skills
Showing 12 of 2771 skills
Perform cohort analysis on user engagement data — retention curves, feature adoption trends, and segment-level insights. Use when analyzing user retention by cohort, studying feature adoption over time, investigating churn patterns, or identifying engagement trends.
Expert knowledge for Azure Synapse Analytics development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building, debugging, or optimizing Azure Synapse Analytics applications. Not for Azure Data Factory (use azure-data-factory), Azure Data Explorer (use azure-data-explorer), Azure Databricks (use azure-databricks), Azure Stream Analytics (use azure-stream-analytics).
Comprehensive Stata reference for writing correct .do files, data management, econometrics, causal inference, graphics, Mata programming, and 20 community packages (reghdfe, estout, did, rdrobust, etc.). Covers syntax, options, gotchas, and idiomatic patterns. Use this skill whenever the user asks you to write, debug, or explain Stata code.
Expert knowledge for Azure Data Manager for Agriculture development including limits & quotas, security, configuration, and integrations & coding patterns. Use when setting up BYOL creds/Private Link, ag data ingestion/IoT, AI/nutrient APIs, throttling, or Event Grid logs, and other Azure Data Manager for Agriculture related development tasks. Not for Azure Data Explorer (use azure-data-explorer), Azure Data Factory (use azure-data-factory), Azure Synapse Analytics (use azure-synapse-analytics), Azure Databricks (use azure-databricks).
Query GMGN on-chain tracking data — follow-wallet trade records, KOL trades, and Smart Money trades. Supports sol / bsc / base.
Enrich contacts and companies with verified emails, phones, and firmographic data. Also covers CRM data hygiene, deduplication, and bulk enrichment. Use when enriching leads, finding email addresses, cleaning CRM data, doing bulk enrichment, optimizing enrichment credits, setting up auto-enrichment, or fixing stale contact data. Do NOT use for building new prospect lists from scratch (use /sales-prospect-list), interpreting buying signals (use /sales-intent), or general Apollo platform help (use /sales-apollo).
Lobstr.io platform help — no-code web scraping platform with 50+ ready-made scrapers for Google Maps, LinkedIn Sales Navigator, Twitter, YouTube, and more. Features cookie-based login sync, scheduled automation, multi-threading, and a full API with Python SDK and MCP Server. Use when configuring a Lobstr scraper, exporting data to Google Sheets or S3, setting up scheduled scraping, working with the Lobstr API or Python SDK, or managing credits. Do NOT use for general prospect list strategy (use /sales-prospect-list), cross-platform enrichment strategy (use /sales-enrich), or integration strategy (use /sales-integration).
Use when the user needs Excel file manipulation — reading, writing, formulas, charts, conditional formatting, data validation, pivot tables, or large file handling. Trigger conditions: create Excel reports programmatically, read spreadsheet data, add formulas or charts, apply conditional formatting, perform data validation, generate pivot tables, handle CSV import/export, process large datasets in Excel format.
Use daily frequency data of natural gas and fertilizer prices to verify whether the narrative of "natural gas price surge → fertilizer supply constraints/breach of contract → fertilizer price surge" holds, and output key turning points and lead-lag analysis that can be marked on charts.
Access UniProt for protein sequence and annotation retrieval. Use this skill when: (1) Looking up protein sequences by accession, (2) Finding functional annotations, (3) Getting domain boundaries, (4) Finding homologs and variants, (5) Cross-referencing to PDB structures. For structure retrieval, use pdb. For sequence design, use proteinmpnn.
Complete guide for Apache Airflow orchestration including DAGs, operators, sensors, XComs, task dependencies, dynamic workflows, and production deployment
Executive-grade data analysis with pandas/polars and McKinsey-quality visualizations. Use when analyzing data, building dashboards, creating investor presentations, or calculating SaaS metrics.