Total 30,737 skills, Data Processing has 1471 skills
Showing 12 of 1471 skills
Guidance for implementing Adaptive Rejection Sampling (ARS) algorithms. This skill should be used when implementing rejection sampling methods, log-concave distribution samplers, or statistical sampling algorithms that require envelope construction and adaptive updates. It provides procedural approaches, performance considerations, and verification strategies specific to ARS implementations.
Use when designing databases for data-heavy applications, making schema decisions for performance, choosing between normalization and denormalization, selecting storage/indexing strategies, planning for scale, or evaluating OLTP vs OLAP trade-offs. Also use when encountering N+1 queries, ORM issues, or concurrency problems.
Guidance for building and fixing Cython extensions, particularly for numpy compatibility issues. This skill should be used when tasks involve compiling Cython code, fixing deprecated numpy type errors, or resolving compatibility issues between Cython extensions and modern numpy versions (2.0+).
Automate College Football Data tasks via Rube MCP (Composio). Always search tools first for current schemas.
Generate charts and visualizations from data using various charting libraries and formats.
Read, watch, and listen to video/audio files. Extract key frames to "see" videos, extract audio to "hear" them via Whisper transcription. Use when a user sends a video/audio and asks about its content, what's in it, what someone said, etc.
Google Optimization Tools. An open-source software suite for optimization, specialized in vehicle routing, flows, integer and linear programming, and constraint programming. Features the world-class CP-SAT solver. Use for vehicle routing problems (VRP), scheduling, bin packing, knapsack problems, linear programming (LP), integer programming (MIP), network flows, constraint programming, combinatorial optimization, resource allocation, shift scheduling, job-shop scheduling, and discrete optimization problems.
Coordinate the plot point and dramatic function analysis process, manage text preprocessing, parallel analysis, and result integration. Suitable for scenarios of plot point and dramatic function analysis of long texts, and scenarios requiring structured analysis reports
Integrate multiple plot point analysis results into a comprehensive report, and generate high-quality analysis through deduplication, classification, sorting, and summarization. Suitable for integrating multiple analysis sources and generating unified reports
Analyze multi-round evaluation score data, count various indicators, and calculate rating levels. Suitable for analyzing score trends and calculating S/A/B ratings
Audit and improve CRM data quality by identifying missing fields, inconsistent values, duplicate records, and stale data
Model best-case, worst-case, and likely revenue scenarios with sensitivity analysis for strategic planning