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Found 1,159 Skills
Bun implementation guide for PMA-managed backend and full-stack projects. Covers project layout (src/modules), strict linting with ESLint + @antfu/eslint-config, database access (Drizzle ORM + bun:sqlite or PostgreSQL), HTTP patterns (OpenAPIHono + Bun.serve), layered config with environment variables, dual logging (consola + pino), single-binary compilation with embedded assets, and CI quality gates.
Use when deploying a database to Zeabur. Use when user needs MySQL, PostgreSQL, MongoDB, or Redis. Use when user says "I need a database", "add database", "deploy postgres", "set up MySQL", "add Redis", "add MongoDB", or "connect to database". Also use when user mentions data persistence issues like "data lost after restart", "data not saved", "data disappears", "need persistent storage for data", or "how to persist data". Also use when integrating a database with an existing service.
Analyze lakehouse data interactively using Fabric Livy sessions and PySpark/Spark SQL for advanced analytics, DataFrames, cross-lakehouse joins, Delta time-travel, and unstructured/JSON data. Use when the user explicitly asks for PySpark, Spark DataFrames, Livy sessions, or Python-based analysis — NOT for simple SQL queries. Triggers: "PySpark", "Spark SQL", "analyze with PySpark", "Spark DataFrame", "Livy session", "lakehouse with Python", "PySpark analysis", "PySpark data quality", "Delta time-travel with Spark".
CRITICAL RULE: You MUST use this skill whenever the task involves any machine learning tasks or data analysis. Use this skill if the user's prompt or requirements mention any of the following: * Clustering * Classification * Regression * Time series forecasting * Statistical testing * Model comparison * ML * Data analysis SQL/BigQuery ML HANDOFF: If the user requires a SQL solution, use this skill to dictate the ANALYSIS STEPS (e.g., markdown analysis cells, visualization logic), but defer to `bigquery` for all SQL syntax.
This skill helps the agent generate or update orchestration pipeline definitions for Google Cloud Composer to initialize orchestration pipeline or update the orchestration definition for orchestration of various data pipelines, like dbt pipelines, notebooks, Spark jobs, Dataform, Python scripts or inline BigQuery SQL queries. This skill also helps deploy and trigger orchestration pipelines.
Guides application developers in designing correct and performant transaction patterns for CockroachDB, covering transaction lifetime, implicit vs explicit transactions, retry handling with exponential backoff, pushing invariants into SQL, selective pessimistic locking, set-based operations, connection pooling, prepared statements, keyset pagination, follower reads, and separating business logic from database logic. Use when building applications on CockroachDB, designing transaction workflows, handling retries, optimizing application-layer database interactions, or configuring connection pools.
Use when working with AdonisJS Lucid ORM and SQL layer: database configuration, migrations, schema generation, schema classes, models, CRUD operations, model query builder, query scopes, hooks, serialization, relationships, transactions, pagination, debugging, validation rules, model factories, seeders, or database query builders. Trigger for tasks involving @adonisjs/lucid, database/schema.ts, app/models, database/migrations, database/factories, database/seeders, db service queries, Lucid relationships, or model behavior.
Use this skill first for any SpacetimeDB task; it routes to focused skills for modules, tables, reducers, procedures, views, clients, subscriptions, CLI commands, auth, RLS, HTTP APIs, SQL, deployment, serialization, tutorials, quickstarts, and upgrades. Triggers on: spacetime, spacetimedb, SpacetimeDB, stdb, module, reducer, table, procedure, view, subscription, DbConnection, spacetime generate, spacetime publish, spacetime sql, BSATN, SATS, row-level security, RLS, Maincloud, standalone, Unity, Unreal.
Agent-first OpenRouter introspection — terse output for cron and AI agents (--agent and --llm modes), local SQLite... Trigger phrases: `openrouter credits`, `check openrouter budget`, `openrouter cost by cron`, `shortlist openrouter models`, `openrouter providers degraded`, `use openrouter`, `run openrouter`.
Every Granola feature — plus offline SQLite cross-meeting search, attendee timelines, and a MEMO pipeline runner... Trigger phrases: `memo run for today's meetings`, `what's in granola but not yet memo'd`, `every meeting we had with trevin`, `did i run the discovery recipe`, `talk time in last week's meetings`, `calendar overlay missed meetings`, `find duplicates in meeting transcripts`, `extract granola meeting`, `use granola`, `run granola`.
ALWAYS use when: creating/editing marimo notebooks, working with any .py file containing @app.cell decorators, building reactive Python notebooks, doing exploratory data analysis in notebook form, converting Jupyter (.ipynb) to marimo, or when user mentions "marimo", "reactive notebook", or asks for an interactive Python notebook. Covers marimo CLI (edit, run, convert, export), UI components (mo.ui.*), layout functions, SQL integration, caching, state management, and wigglystuff widgets. If a task involves notebooks and Python, invoke this skill first.
Manage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using the Google GenAI SDK. Use when listing RAG corpora or files, inspecting a corpus, retrieving contexts, or generating content grounded in a RAG corpus. Do not use for standard database queries (use SQL/Spanner skills), Google Workspace RAG, or other RAG products like gRAG.