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Create a Wren MDL project, a model layer for database queries, from an existing database. Discover tables and relationships, normalize column types, generate YAML files, and validate and build the project before indexing its schema.

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• Create a Wren project from an existing database
• Add selected schemas and tables as a new data source
• Define model relationships from database constraints

Set up Wren Engine through guided steps covering environment checks, installation, database connection, and project creation. Prepare data definitions and validate the setup, then suggest initial questions to help the user begin exploring their data.

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• Installing Wren Engine for the first time
• Connecting a new database to Wren
• Creating a project and preparing data definitions

Find the Wren CLI workflow for answering data questions, connecting databases or SaaS sources, generating model definitions, adding business metrics, or building a shareable analytics app. Guides are retrieved from the installed CLI version.

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• Set up Wren and connect a database
• Load HubSpot or Stripe data through dlt
• Generate model definitions and add business metrics

Answer business data questions with Wren CLI by checking model definitions, reusing past queries, and executing SQL or predefined aggregations. The workflow also covers query verification, error diagnosis, and saving successful queries for future use.

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• Analyze monthly revenue trends
• Rank customers by purchase value
• Compare metrics across plans or regions

Set up and manage a local Kubernetes development environment for OpenShell using k3d, Skaffold, and Helm. Build and deploy changes, inspect traces, configure optional authentication components, and test behavior across multiple gateway replicas.

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• Create or stop a local OpenShell development cluster
• Rebuild and deploy changes during development
• Inspect local execution traces

Diagnose unreachable or unhealthy OpenShell gateways and sandbox startup failures. Identify the underlying execution platform, then examine logs, authentication, certificates, and configuration with the matching tools to narrow down the cause.

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• Investigate gateway connection and health check failures
• Find why a sandbox remains pending or fails to start
• Check Docker or Podman runtime and image problems

Run the current working copy locally with a real language model and Postgres database. Choose web, Slack, or both to test a branch end to end, with separate Slack apps for concurrent instances.

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• Test a branch through Slack
• Check web and admin screens locally
• Run several working copies at once

Use Phoenix to record execution traces, detailed records of an AI application's operations, and investigate problems. Evaluate answers on datasets, compare prompts and models, and set up monitoring through a self-hosted server.

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• Investigate AI application problems using execution traces
• Evaluate answer quality across a test dataset
• Compare prompts and models through experiments

Build AI agents by connecting workflow blocks in AutoGPT's visual editor. This skill covers multi-step automation, scheduled runs, webhooks that start work after external events, execution monitoring, and custom agent development.

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• Build an AI workflow in a visual editor
• Start an agent when an external event occurs
• Run a multi-step workflow on a schedule

Investigate slow SQL, write complex joins and summaries, and design database structures. Uses execution plans, which show how queries run, to guide index choices and query rewrites, with before-and-after performance measurements.

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• Investigate a slow SQL query
• Write complex joins and grouped calculations
• Design tables, keys, and constraints

Design or review a system’s overall structure, compare technology choices, and plan for growth and failures. Produce architecture diagrams and Architecture Decision Records, documents that explain key choices, alternatives, and their consequences.

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• Designing the overall structure of a new system
• Comparing monolith and microservices architectures
• Recording technology decisions and alternatives

Analyze and tune PostgreSQL databases using query execution plans, which show how queries run. This skill guides index design, JSONB searches, replication setup, maintenance, and monitoring, with checks to compare behavior before and after changes.

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• Investigate slow queries with EXPLAIN
• Design indexes for JSONB searches
• Configure replication and monitor lag

Investigate slow PostgreSQL and MySQL queries using execution plans, which show how the database runs a query. Develop index, SQL, and configuration changes, then compare measurements before and after each change to validate the results.

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• Investigating slow SQL queries
• Reviewing database index design
• Tuning memory and database configuration

Use persistent virtual terminal sessions to keep directories and environment variables across commands, interact with Python or database consoles, and answer prompts. The skill explains sending input, reading responses, detecting prompts, and closing sessions when finished.

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• Keep directories and environment variables across commands
• Run a sequence of commands in an interactive Python console
• Interact with mysql or psql consoles

Look up how to configure and organize Omnigent agents. Use examples to choose an executor, the agent's runtime, arrange instructions and skills, add local tools or external services, and define specialized child agents.

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• Check agent directory layout and config.yaml settings
• Choose an executor and harness
• Add skills, custom tools, or MCP services

Build and run Omnigent’s server and Postgres together with Docker Compose on a laptop or existing Docker host. Use the supplied configuration and troubleshooting guidance to rebuild images, investigate startup problems, or adapt deployment to another platform.

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• Running Omnigent locally with Postgres
• Starting the stack on an existing VPS or EC2 host
• Investigating startup and web interface problems

Get help understanding and configuring Octop, a self-hosted AI assistant. The skill explains features, points to relevant documentation, and supports model switching, messaging connections, skill management, scheduled tasks, backups, and upgrades.

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• Learn about Octop and find installation instructions
• Switch AI models or configure providers
• Connect messaging services such as Discord

Write and review Apache SeaTunnel unit tests and E2E tests that check complete jobs using Testcontainers. It provides concrete rules for container setup, waiting, resource cleanup, and assertions to address intermittent failures and resource leaks.

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• Writing a new connector E2E test
• Reviewing a test diff before a pull request
• Fixing intermittent failures or resource leaks in tests

Create, update, or review Bifrost feature documentation for Mintlify using MDX, a format combining Markdown and components. Research the interface and backend, validate configuration examples, and organize pages with screenshot placeholders and navigation entries.

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• Write documentation for a new Bifrost feature
• Update guides after interface or API changes
• Validate config.json examples against the schema

Audit database migration changes before a Bifrost release for lock contention, deadlocks, and delayed application startup. Receive pass, warning, or failure results, a release recommendation, and concrete remediation steps without modifying files.

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• Review migration safety before a release
• Check index creation risks on large log tables
• Find migration work that delays application startup

Work with Apache Beam I/O connectors, components that read and write external data. Get guidance on connector usage, unit and integration tests, troubleshooting data connections, and the basic structure of new connectors.

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• Add BigQuery or Kafka reads and writes to a pipeline
• Run unit and integration tests for connectors
• Investigate data source or destination issues

Build a graph of functions and calls across multiple programming languages to investigate entry points, paths to sensitive operations, and potential impact. Use the results to prioritize security reviews and connect external findings with source code.

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• Tracing call paths from entry points to sensitive functions
• Prioritizing code for a security audit
• Connecting calls across language and RPC boundaries

Assess web applications and APIs for SQL injection, where input changes database queries. The skill covers finding vulnerable inputs, testing different database systems, automating checks, and documenting findings with remediation suggestions.

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• Assessing web application inputs for SQL injection
• Reviewing GraphQL and WebSocket injection risks
• Combining SQLmap automation with manual verification

Set up and operate NVIDIA AI-Q Blueprint locally or on your own infrastructure. Choose a deployment mode, configure credentials, check service health, troubleshoot failures, and provide a verified server address for aiq-research.

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• Starting a backend for aiq-research
• Running AI-Q through a terminal or browser
• Deploying AI-Q to a Kubernetes cluster