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Found 1,411 Skills
Rust full-stack patterns. Leptos + Axum + PostgreSQL web apps, auth, multi-tenant, API design.
Implement reliable PostgreSQL-based job queues with PG Boss. Use when implementing background jobs, scheduled tasks, cron-like functionality, task rollover, or email notifications in Node.js/TypeScript projects.
Эксперт SQL window functions. Используй для аналитических запросов, OVER clauses и ranking functions.
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
Vector embeddings with HNSW indexing, sql.js persistence, and hyperbolic support. 75x faster with agentic-flow integration. Use when: semantic search, pattern matching, similarity queries, knowledge retrieval. Skip when: exact text matching, simple lookups, no semantic understanding needed.
Use these skills when you need to explore the database schema, identify objects like views and triggers, and execute custom SQL queries to interact with your data.
Use these skills when you need to handle large-scale data exploration and dataset management. Use when users need to find data assets or run SQL at scale. Provides metadata discovery and query execution across the data warehouse.
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.
Pull every meal you ever logged out of MyFitnessPal — per-food CSV, agent-shaped trends, and a local SQLite store. Trigger phrases: `what did I eat this week`, `export my food diary`, `find every time I logged X`, `top foods driving my protein`, `am I hitting my calorie streak`, `use myfitnesspal`, `run myfitnesspal`.
Salesforce Data Cloud Segment phase. Use this skill when the user creates or publishes segments, manages calculated insights, or troubleshoots audience SQL in Data Cloud. TRIGGER when: user creates or publishes segments, manages calculated insights, inspects segment counts or membership, or troubleshoots audience SQL in Data Cloud. DO NOT TRIGGER when: the task is DMO/mapping/identity-resolution work (use harmonizing-datacloud), activation work (use activating-datacloud), query/search-index work (use retrieving-datacloud), or Standard Data Model (STDM)/session tracing (use observing-agentforce).
Required reading before writing any HogQL/SQL or calling execute-sql against PostHog. Use whenever the user wants to search, find, or do complex aggregations PostHog entities (insights, dashboards, cohorts, feature flags, experiments, surveys, hog flows, data warehouse, persons, etc.) and query analytics data (trends, funnels, retention, lifecycle, paths, stickiness, web analytics, error tracking, logs, sessions, LLM traces). Covers HogQL syntax differences from ClickHouse SQL, system table schemas (system.*), available functions, query examples, and the schema-discovery workflow.
Build ETL pipelines and analytics dashboards for Harvard Art Museums API data using Python, SQL, and Streamlit