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Claude Skills by majiayu000
github.com/majiayu00015,502 skills856 installs32,980 views
- Data Cleaning StandardsClean and standardize vehicle insurance CSV/Excel data. Use when handling missing values, fixing data formats, removing duplicates, or standardizing fields. Mentions "clean data", "handle nulls", "standardize", "duplicates", or "normalize".Votes: 0GitHub stars: 666
- Data CleaningData cleaning, preprocessing, and quality assurance techniquesVotes: 0GitHub stars: 666
- Data Cloud 2025Salesforce Data Cloud integration patterns and architecture (2025)Votes: 0GitHub stars: 666
- Data ContractCreate, validate, test, and manage data contracts using the Open Data Contract Specification (ODCS) and the datacontract CLI. Use when working with data contracts, ODCS specifications, data quality rules, or when the user mentions datacontract CLI or data contract workflows.Votes: 0GitHub stars: 666
- Data ContractsData contracts สำหรับกำหนด schema, quality expectations และ SLAs ระหว่าง data producers และ consumersVotes: 0GitHub stars: 666
- Data ConverterConvert data between formats (JSON, XML, CSV, YAML, TOML). Use when transforming data structures or migrating between data formats.Votes: 0GitHub stars: 666
- Data DesignData modeling, schema design, and data architectureVotes: 0GitHub stars: 666
- Data DesignerGenerate high-quality synthetic datasets using statistical samplers and Claude's native LLM capabilities. Use when users ask to create synthetic data, generate datasets, create fake/mock data, generate test data, training data, or any data generation task. Supports CSV, JSON, JSONL, Parquet output. Adapted from NVIDIA NeMo DataDesigner (Apache 2.0).Votes: 0GitHub stars: 666
- Data Engineering Data Driven FeatureBuild features guided by data insights, A/B testing, and continuous measurement using specialized agents for analysis, implementation, and experimentation.Votes: 0GitHub stars: 666
- Data EngineeringUse this skill when designing or reviewing data pipelines, ETL processes, data warehouses, streaming systems, or any system where data movement, transformation, and quality are primary concerns. Applies data engineering thinking to specifications, designs, and implementations.Votes: 0GitHub stars: 666
- Data ExpertData processing expert including parsing, transformation, and validationVotes: 0GitHub stars: 666
- Data ExplorationExplore and analyze pilot data sets to uncover patterns, anomalies, and initial insights. Use when performing ad-hoc data investigations, validating data quality, or preparing exploratory visualizations for hypothesis generation.Votes: 0GitHub stars: 666
- Data Export ExcelExport analysis results, data tables, and formatted spreadsheets to Excel files using openpyxl. Works with ANY LLM provider (GPT, Gemini, Claude, etc.).Votes: 0GitHub stars: 666
- Data Export FormatsUse when exporting data for ad platforms (Google Ads, Meta) or working with project datasets. Documents exact CSV formats for Enhanced Conversions, Customer Match, and project data schemas.Votes: 0GitHub stars: 666
- Data Extraction PatternsCommon patterns for extracting and combining analytics data from GA4, GSC, and SE Ranking. Includes API patterns, rate limiting, caching, and error handling.Votes: 0GitHub stars: 666
- Data ExtractionUse when extracting structured data from medical research PDFs, parsing study characteristics, patient demographics, outcomes, and results. Invoke for systematic review data collection from papers.Votes: 0GitHub stars: 666
- Data Fetching PatternsSWR-based data fetching and caching patterns used throughout the monorepo. Use this skill when implementing API interactions, creating custom data hooks, handling loading/error states, or working with mock data. Covers SWR configuration, custom hook patterns (useUserInfo, useTimesSquarePage), error handling, and mock data setup.Votes: 0GitHub stars: 666
- Data FetchingBest practices and conventions for server-side data fetching, caching, and rendering in Next.js 16+ applications.Votes: 0GitHub stars: 666
- Data FlowRooms as pipeline nodes, exits as edges, objects as messagesVotes: 0GitHub stars: 666
- Data FormatsData format specialist covering TOON encoding, JSON/YAML optimization, serialization patterns, and data validation for modern applications. Use when optimizing data for LLM transmission, implementing high-performance serialization, validating data schemas, or converting between data formats.Votes: 0GitHub stars: 666
- Data Governance And QualityData governance strategy, quality validation rules, and data dictionary management for vehicle insurance platform. Use when defining data quality standards, implementing validation rules, managing field mappings, resolving data conflicts, or establishing data governance processes. Covers data cleaning standards, quality metrics, and mapping management.Votes: 0GitHub stars: 666
- Data Governance CheckReview data handling for privacy and retention. Use when a senior developer needs governance validation.Votes: 0GitHub stars: 666
- Data Import WorkflowManaging the lifecycle of weapon and mod data from external sources to the local databaseVotes: 0GitHub stars: 666
- Data ImportLoad and parse mass spectrometry data formats including mzML, mzXML, and quantification tool outputs like MaxQuant proteinGroups.txt. Use when starting a proteomics analysis with raw or processed MS data. Handles contaminant filtering and missing value assessment.Votes: 0GitHub stars: 666
- Data ImporterImport Synnovator platform data from .synnovator/*.md files into SQLite database via SQLAlchemy models. Use when need to populate test data, initialize database from file-based data, or migrate .synnovator content to relational database. Triggers include "import synnovator data", "populate database from .synnovator", "fill database with test data", or when user needs to test FastAPI endpoints with real data.Votes: 0GitHub stars: 666
- Data Incident ResponseProcedures and playbooks for responding to data quality incidents, data loss, corruption, and pipeline failures.Votes: 0GitHub stars: 666
- Data Ingestion BuilderBuild new data ingestion providers following the FF Analytics registry pattern. This skill should be used when adding new data sources (APIs, files, databases) to the data pipeline. Guides through creating provider packages, registry mappings, loader functions, storage integration, primary key tests, and sampling tools following established patterns.Votes: 0GitHub stars: 666
- Data InsightsGenerate actionable insights from transaction data. Use when implementing insight generators, anomaly detection, or data analysis features for financial/tax tracking applications.Votes: 0GitHub stars: 666
- Data Integrity Auditor Monkey1sai Openai CliDetects data integrity issues including orphaned records, broken foreign key relationships, constraint violations, and provides automated fix migrations. Use for "data integrity", "orphaned records", "broken relationships", or "data quality".Votes: 0GitHub stars: 666
- Data Integrity AuditorDetects data integrity issues including orphaned records, broken foreign key relationships, constraint violations, and provides automated fix migrations. Use for "data integrity", "orphaned records", "broken relationships", or "data quality".Votes: 0GitHub stars: 666
- Data Integrity GuardianMaintain database quality, ensure data alignment, verify mission compliance, prepare for JusticeHub syndication.Votes: 0GitHub stars: 666
- Data Lake ArchitectureOrganize object storage with lifecycle policies.Votes: 0GitHub stars: 666
- Data Lake ManagementData Lake architecture and management including medallion architecture (bronze/silver/gold zones), data catalog with AWS Glue, partitioning strategies, schema evolution, data quality, governance, cost optimization, S3 lifecycle policies, data retention, compliance, query optimization with Athena, data formats (Parquet, ORC, Avro), incremental processing, CDC patterns, and production best practices for scalable data lakes.Votes: 0GitHub stars: 666
- Data Lake PlatformData lake and lakehouse platform patterns: ingestion/CDC, transformations, open table formats (Iceberg/Delta/Hudi), query and serving engines (Trino/ClickHouse/DuckDB), orchestration, governance/lineage, cost and operations. Self-hosted and cloud options.Votes: 0GitHub stars: 666
- Data Layer ArchitectureBronze Layer（LLM抽出ログ層）とGold Layer（確定データ層）の2層アーキテクチャ設計。LLM抽出結果の履歴管理と人間修正の保護を実現。抽出処理の実装、ExtractionLogの使用、is_manually_verifiedフラグの扱いに関するガイダンスを提供。Votes: 0GitHub stars: 666
- Data LayerThis skill provides patterns for working with the data-layer module. Use when creating/editing files in src/data-layer/, src/lib/data/, or adding new data sources.Votes: 0GitHub stars: 666
- Data LineageMapping the flow of data from source to destination for transparency, impact analysis, and troubleshooting.Votes: 0GitHub stars: 666
- Data LoadLoad data from files (CSV, JSON, JSONL, Parquet) or stdin for analysis and visualization with ggterm. Use when reading datasets, importing data, opening files, or when the user mentions loading, reading, or opening data.Votes: 0GitHub stars: 666
- Data ManagementDesign and manage data storage effectively. Use when working with databases, schemas, or data migrations. Covers schema design, migrations, and data integrity.Votes: 0GitHub stars: 666
- Data Manager SystemService-scoped data orchestration for TMNL. Invoke when implementing search, data streams, kernel systems, or Effect-based DAQ. Covers hybrid dispatch (fibers + workers), Atom-as-State pattern, and progressive streaming.Votes: 0GitHub stars: 666
- Data ManagerPB-000の成果物をファイルベースで保存・管理。フォルダ作成、ファイル存在確認、実行履歴管理を担当。データ管理、ファイル操作で必ず使用。Votes: 0GitHub stars: 666
- Data MappingData mapping patterns for transforming API responses to internal typesVotes: 0GitHub stars: 666
- Data Mesh ExpertExpert-level data mesh architecture, domain-oriented ownership, data products, federated governance, and self-serve platformsVotes: 0GitHub stars: 666
- Data MetabaseMetabase REST API automation and troubleshooting: authenticate (API key preferred, session fallback), export/upsert questions (cards) and dashboards, standardize visualization_settings, and run/export results.Votes: 0GitHub stars: 666
- Data Migration AgentPlans and executes data migrations between systems, databases, and formatsVotes: 0GitHub stars: 666
- Data Migration ExpertUse this agent when reviewing database migrations, schema changes, or data transformations. Specializes in validating ID mappings, checking for swapped values, and verifying rollback safety. Triggers on requests like "migration review", "schema change validation".Votes: 0GitHub stars: 666
- Data Model ReporterStandards for generating Model Cards from data analysis notebooks. Aligned with Hugging Face and ISO transparency standards.Votes: 0GitHub stars: 666
- Data Model ReviewerAnalyze and Refactor TypeScript data models. Detect duplication, improve type safety, and validate relationships in interfaces/types.Votes: 0GitHub stars: 666
- Data ModelAdding new data models - schema, shared zod, entity pattern, and oRPC routes. Use when user asks to create a new entity, model, or feature that needs database tables.Votes: 0GitHub stars: 666
- Data ModelerDesign data models with Pydantic schemas, comprehensive validation rules,Votes: 0GitHub stars: 666