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Found 1,571 Skills
Convert natural language queries to SQL. Use for database queries, data analysis, and reporting.
Look up Next.js documentation for a topic. Use before implementing any Next.js feature to get accurate, up-to-date framework knowledge.
Vitest fast unit testing framework powered by Vite with Jest-compatible API. Use when writing tests, mocking, configuring coverage, or working with test filtering and fixtures.
Generates comprehensive, workable unit tests for any programming language using a multi-agent pipeline. Use when asked to generate tests, write unit tests, improve test coverage, add test coverage, create test files, or test a codebase. Supports C#, TypeScript, JavaScript, Python, Go, Rust, Java, and more. Orchestrates research, planning, and implementation phases to produce tests that compile, pass, and follow project conventions.
Configure PostgreSQL with pgvector for GrepAI. Use this skill for team environments and large codebases.
Audit code architecture for over-engineering and unnecessary abstractions. Use when user asks to "review architecture", "simplify code structure", "reduce over-engineering", "evaluate abstractions", or mentions premature abstraction, interface proliferation, factory patterns, YAGNI, or enterprise-grade complexity.
Migrate a file to use stricter Pyrefly type checking with annotations required for all functions, classes, and attributes.
Isar Database, Caching & Offline-First Patterns
Create institutional-quality equity research initiation reports through a 5-task workflow. Tasks must be executed individually with verified prerequisites - (1) company research, (2) financial modeling, (3) valuation analysis, (4) chart generation, (5) final report assembly. Each task produces specific deliverables (markdown docs, Excel models, charts, or DOCX reports). Tasks 3-5 have dependencies on earlier tasks.
Manage Taskwarrior tasks scoped to the current git repository using its remote URL as a project identifier.
Native Arrow filesystem integration with PyArrow. Optimized for Parquet workflows, zero-copy data transfer, predicate pushdown, and column pruning. Covers S3, GCS, HDFS with PyArrow datasets.
A practical, jargon-free guide to fp-ts functional programming - the 80/20 approach that gets results without the academic overhead. Use when writing TypeScript with fp-ts library.