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Found 87 Skills
Fetch up-to-date documentation and code examples for any library or framework. Use when needing API references, code examples, library documentation, or framework guides. Supports React, Next.js, MongoDB, Supabase, and thousands of other libraries.
Creates and scaffolds a new Spring Boot project (3.x or 4.x) by downloading from Spring Initializr, generating package structure (DDD or Layered architecture), configuring JPA, SpringDoc OpenAPI, and Docker Compose services (PostgreSQL, Redis, MongoDB). Use when creating a new Java Spring Boot project from scratch, bootstrapping a microservice, or initializing a backend application.
Deploys infrastructure components via Helm charts on TrueFoundry. Supports any public or private OCI Helm chart including databases (Postgres, MongoDB, Redis), message brokers (Kafka, RabbitMQ), and vector databases (Qdrant, Milvus). Uses YAML manifests with `tfy apply`. Use when installing Helm charts or deploying infrastructure on TrueFoundry.
Build backend APIs for Chrome extensions. NestJS + MongoDB (Mongoose) recommended stack. Auth, webhooks, license verification, CORS. Use when: backend, API, server, database, license, webhook.
Drop-in pandas replacement with ClickHouse performance. Use `import chdb.datastore as pd` (or `from datastore import DataStore`) and write standard pandas code — same API, 10-100x faster on large datasets. Supports 16+ data sources (MySQL, PostgreSQL, S3, MongoDB, ClickHouse, Iceberg, Delta Lake, etc.) and 10+ file formats (Parquet, CSV, JSON, Arrow, ORC, etc.) with cross-source joins. Use this skill when the user wants to analyze data with pandas-style syntax, speed up slow pandas code, query remote databases or cloud storage as DataFrames, or join data across different sources — even if they don't explicitly mention chdb or DataStore. Do NOT use for raw SQL queries, ClickHouse server administration, or non-Python languages.
Guide the user through connecting a new data warehouse source — Postgres, MySQL, Stripe, Hubspot, MongoDB, Salesforce, BigQuery, Snowflake, and so on. Use when the user wants to "connect Stripe", "import data from Postgres", "add a new data source", "sync my warehouse tables", or wants to pick sync methods for each table. Walks through source-type discovery, credential validation, table discovery, per-table sync_type selection, and the final create call. Also covers picking a good prefix and what to do right after creation.
Database operations including querying, schema exploration, and data analysis. Activates for tasks involving PostgreSQL, MySQL, MariaDB, SQLite, MongoDB, Redis, Elasticsearch, or ClickHouse databases.
Automatically generate complete Python project deliverables from natural language requirements through collaboration among four virtual roles: autonomous learning, PM, architect, and senior programmer. Supports feature expansion, project refactoring, and skill invocation. Also supports web search, knowledge integration, version control, Python 3.11+ features, UV package management, loguru logging, and project size adaptation (folder/single file). It provides support for database design and implementation (SQLite, PostgreSQL, MongoDB, vector databases, graph databases), data layer abstraction (Repository pattern), and database switching. Suitable for scenarios such as software requirement clarification, rapid prototyping, project initialization, feature expansion, and code refactoring.
Database performance optimization, schema design, query analysis, and connection management across PostgreSQL, MySQL, MongoDB, and SQLite with ORM integration. Use this skill for queries, indexes, connection pooling, transactions, and database architecture decisions.
Analyzes and optimizes SQL/NoSQL queries for performance. Use when reviewing query performance, optimizing slow queries, analyzing EXPLAIN output, suggesting indexes, identifying N+1 problems, recommending query rewrites, or improving database access patterns. Supports PostgreSQL, MySQL, SQLite, MongoDB, Redis, DynamoDB, and Elasticsearch.
PostgreSQL relational database. Covers SQL queries, indexes, constraints, and performance. Use when working with PostgreSQL. USE WHEN: user mentions "postgres", "postgresql", "pg_", asks about "JSONB queries", "window functions", "recursive CTE", "row level security", "full text search", "partitioning", "pgBouncer", "replication" DO NOT USE FOR: MySQL syntax - use `mysql` instead, MongoDB - use `mongodb` instead, Oracle PL/SQL - use `plsql` instead, SQL Server T-SQL - use `tsql` instead
Vulcan C# Agent — sviluppo C# moderno, cloud-native (AWS/Azure) e provider-agnostic con Serilog, LiteDB, MongoDB e pattern architetturali puliti