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Found 959 Skills
Profile and explore a dataset to understand its shape, quality, and patterns. Use when encountering a new table or file, checking null rates and column distributions, spotting data quality issues like duplicates or suspicious values, or deciding which dimensions and metrics to analyze.
Overview of LookML field types (Dimension, Measure, Filter, Parameter) and the role of the `sql` parameter in each. Use this skill to choose the right field type for your data modeling needs.
Comprehensive guide for building with Prisma 8 (Prisma Next), the contract-first data layer. Use whenever working on Prisma code in a project that uses it — authoring or editing the data contract (contract.prisma, PSL, TypeScript builders), migrations, queries (db.orm / db.sql), runtime wiring (db.ts, middleware, DATABASE_URL), build-tool integration, Supabase / RLS, reading PN-* structured errors, or filing feedback — and for orientation questions like "what is Prisma Next" or comparisons to other ORMs. Signals that this skill applies: @internal/* imports, prisma.config.ts, contract.prisma / contract.json / contract.d.ts, the prisma-next CLI, PN-* error codes. Also covers upgrading Prisma in a project — "upgrade Prisma 8", "bump Prisma Next", "move to Prisma Next X.Y", or dealing with an @internal/* version bump, in a consumer app or in an extension package. Does not apply to Prisma ORM 7 or earlier (schema.prisma + @prisma/client projects).
Relational Database Schema Design. Design tables, fields, relationships, and indexes based on requirements, covering naming conventions, data types, constraints, and query pattern analysis, and output table creation scripts and design specifications. Use to design or review relational database schemas from requirements.
SQL and NoSQL schema design with normalization, indexing, and migration patterns. Use when designing database schemas, creating tables, optimizing slow queries, or planning database migrations.
Visualization Best Practices - Auto-activating skill for Data Analytics. Triggers on: visualization best practices, visualization best practices Part of the Data Analytics skill category.
Simple Pomodoro timer for focused work sessions with session tracking and productivity analytics. Use when users request focus timers, ask about productivity patterns, or want to track work sessions over time. Demonstrates the System Skill Pattern (CLI + SKILL.md + Database).
Diagnose and resolve ClickHouse grant and authentication errors, especially after upgrades. Use when queries fail with ACCESS_DENIED/NOT_ENOUGH_PRIVILEGES, AUTHENTICATION_FAILED/WRONG_PASSWORD/REQUIRED_PASSWORD, or ON CLUSTER privilege errors; when system.* or INFORMATION_SCHEMA access is denied; or when grant behavior changes after version upgrades.
factory_boy test data generation specialist. Covers Factory, DjangoModelFactory, SQLAlchemyModelFactory, all field declarations (Faker, LazyAttribute, Sequence, SubFactory, RelatedFactory, post_generation, Trait, Maybe, Dict, List), batch creation, pytest integration, and Celery task testing patterns. USE WHEN: user mentions "factory_boy", "test factory", "DjangoModelFactory", "SQLAlchemyModelFactory", asks about "test data generation", "factory traits", "SubFactory", "factory fixtures". DO NOT USE FOR: pytest internals - use `pytest`; Django setup - use `pytest-django`; Hypothesis property testing - use `pytest` with Hypothesis
Decompile and analyze IDA functions. Use when asked for pseudocode, ctree AST analysis, local variables, labels, or decompiler-driven cleanup.
IDA debugger operations. Use when asked to set breakpoints, patch bytes, add conditions, or manage a patch inventory.
Query the german_shopping_receipts BigQuery table with bq. Use when the user asks about groceries, supermarket spend, item prices, or that table.