Total 50,527 skills, Data Processing has 2561 skills
Showing 12 of 2561 skills
How to read and query onchain data — events, The Graph, indexing patterns. Why you cannot just loop through blocks, and what to use instead.
Data analysis, SQL queries, BigQuery operations, and data insights. Use for data analysis tasks and queries.
Retention Calculator - Auto-activating skill for Data Analytics. Triggers on: retention calculator, retention calculator Part of the Data Analytics skill category.
Build interactive data applications and dashboards with pure Python - no frontend experience required
Comprehensive multi-omics disease characterization integrating genomics, transcriptomics, proteomics, pathway, and therapeutic layers for systems-level understanding. Produces a detailed multi-omics report with quantitative confidence scoring (0-100), cross-layer gene concordance analysis, biomarker candidates, therapeutic opportunities, and mechanistic hypotheses. Uses 80+ ToolUniverse tools across 8 analysis layers. Use when users ask about disease mechanisms, multi-omics analysis, systems biology of disease, biomarker discovery, or therapeutic target identification from a disease perspective.
Transform GWAS signals into actionable drug targets and repurposing opportunities. Performs locus-to-gene mapping, target druggability assessment, existing drug identification, safety profile evaluation, and clinical trial matching. Use when discovering drug targets from GWAS data, finding drug repurposing opportunities from genetic associations, or translating GWAS findings into therapeutic leads.
Use when creating or reviewing TradingView Pine Script v6 indicators/strategies/libraries, applying non-repainting best practices, generating Pine Script from other languages, or running Pine Script linting.
Expert Clay platform consultant for B2B data enrichment and workflow automation. Use when the user asks about Clay tables, waterfall enrichment, Clay credits, Clay pricing, Claygent, Clayscript formulas, Clay CRM sync, Clay enrichment workflows, Clay integrations, Clay Chrome extension, Clay templates, or building data pipelines in Clay. Also triggers on "Clay workflow", "enrichment waterfall", "Clay credits", "Claygent", "Clayscript", "Clay + HubSpot", "Clay + Salesforce", "Clay table", "Clay providers", "enrich in Clay", "Clay API", "Clay column", "Clay formulas", "find emails", "email waterfall", "phone waterfall", "lead scoring", "Clay debugging". Do NOT use for general CRM questions without Clay context, standalone email tools (Findymail, Hunter), or non-Clay enrichment platforms.
Parse, search, analyze, and ingest LinkedIn GDPR data exports. This skill should be used when working with LinkedIn data — searching messages, analyzing connections, exporting to Markdown, or ingesting into RLAMA for semantic search. Requires a LinkedIn GDPR data export ZIP file.
Use when designing software architecture for bioinformatics pipelines, defining data structures, planning scalability, or making technical design decisions for complex systems.
Parse raw text from an Instagram or TikTok Story insights screenshot and format it into a clean, spreadsheet-ready row with labeled fields. This skill should be used when parsing Story metrics from a screenshot, formatting Story insights for a spreadsheet, extracting metrics from a pasted Story screenshot, cleaning up Story analytics data, converting Story insights text into structured data, turning a Story performance screenshot into a row for the tracker, logging Story metrics into a spreadsheet, normalizing Story screenshot data, pulling numbers from a Story insights paste, organizing Story metrics from creator screenshots, processing a batch of Story screenshots into rows, building a Story metrics tracker from screenshots, or entering Story data from a screenshot into a sheet. For normalizing metrics from multiple sources into a unified table, see metrics-normalization-formatter. For calculating engagement rates and comparing to benchmarks, see engagement-rate-calculator-benchmarker.
This skill should be used when the user needs to perform year-end closing adjustments, review financial statements, compute depreciation, or review their trial balance. Trigger phrases include: "year-end settlement", "year-end closing adjustments", "prepare financial statements", "depreciation", "trial balance", "trial balance sheet", "income statement", "balance sheet", "BS", "PL", "period-end processing", "inventory taking", "accrual of unpaid expenses", "prepayment processing"