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Found 260 Skills
Production-grade Next.js chatbot builder. Covers tool calling with human-in-the-loop (HITL) approval, PostgreSQL session persistence, GDPR consent gating, SQL-first search, per-tool UI rendering, message feedback, and follow-up suggestions. Use when building chat apps, conversational AI interfaces, customer support bots, or any chatbot needing database-backed sessions, tool approval workflows, consent gating, or custom tool output components. Reference implementation: fair-helpdesk project.
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.
Identifies and exploits SQL injection vulnerabilities in web applications during authorized penetration tests using manual techniques and automated tools like sqlmap. The tester detects injection points through error-based, union-based, blind boolean, and time-based blind techniques across all major database engines (MySQL, PostgreSQL, MSSQL, Oracle) to demonstrate data extraction, authentication bypass, and potential remote code execution. Activates for requests involving SQL injection testing, SQLi exploitation, database security assessment, or injection vulnerability verification.
Import data into the AWS data lake from S3 files, local uploads, JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS, Aurora), Amazon Redshift, Snowflake, BigQuery, DynamoDB, or existing Glue catalog tables (migration). Default target is S3 Tables; standard Iceberg on a general purpose bucket is supported where S3 Tables is not adopted. Handles one-time loads, recurring pipelines, migrations. Triggers on: import data, load data, ingest, sync database, migrate table, move data to AWS, set up pipeline, ETL, pull from Snowflake, query BigQuery into S3, export DynamoDB, CTAS, convert to Iceberg. Do NOT use for setting up or troubleshooting Glue connections (use connecting-to-data-source), creating empty tables (use creating-data-lake-table), running queries (use querying-data-lake), finding tables by fuzzy name (use finding-data-lake-assets), catalog audit (use exploring-data-catalog), or SaaS platforms like Salesforce, ServiceNow, SAP, MongoDB, Kafka.
Trigger when the user wants to create a new dashboard, set up monitoring for a service or infrastructure component, or import a pre-built dashboard template. Includes requests like "create a dashboard for PostgreSQL", "monitor my Redis cluster", "set up observability for my k8s cluster", "I need a dashboard for tracking LLM costs".
Plan a migration onto MotherDuck. Use when moving from Snowflake, Redshift, PostgreSQL, dbt-heavy stacks, or lakehouse tooling and the key decisions are target pattern, cutover slices, validation, rollback, and native-versus-DuckLake posture.
Comprehensive fullstack development skill for building complete web applications with React, Next.js, Node.js, GraphQL, and PostgreSQL. Includes project scaffolding, code quality analysis, architecture patterns, and complete tech stack guidance. Use when building new projects, analyzing code quality, implementing design patterns, or setting up development workflows.
Senior Database Administrator with expertise in PostgreSQL, MySQL, MongoDB, and enterprise database systems. Specializes in high availability architectures, performance tuning, backup strategies, and database security for production environments.
Automatically discover database skills when working with SQL, PostgreSQL, MongoDB, Redis, database schema design, query optimization, migrations, connection pooling, ORMs, or database selection. Activates for database design, optimization, and implementation tasks.
Best practices, coding conventions, and patterns for backend projects using TypeScript. Use when writing code, tests, or new features in TypeScript backends with src/, Express, PostgreSQL/MongoDB, and Mocha+tsx.
Cal.com self-hosted deployment to GCP Cloud Run with Supabase PostgreSQL. Docker Compose for local dev. TRIGGERS - deploy calcom, cloud run, self-hosted, docker compose, supabase, gcp deploy, infrastructure, cal.com hosting.
Use this skill when a user wants to store, manage, or work with Goldsky secrets — the named credential objects used by pipeline sinks. This includes: creating a new secret from a connection string or credentials, listing or inspecting existing secrets, updating or rotating credentials after a password change, and deleting secrets that are no longer needed. Trigger for any query where the user mentions 'goldsky secret', wants to securely store database credentials for a pipeline, or is working with sink authentication for PostgreSQL, Neon, Supabase, ClickHouse, Kafka, S3, Elasticsearch, DynamoDB, SQS, OpenSearch, or webhooks.