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Found 55 Skills
Unified intelligent query interface for the CDM DuckDB database. Use this skill when the user wants to query the linkml-coral CDM database. Automatically chooses between fast SQL translation and schema-aware intelligent queries based on complexity. Supports natural language questions, schema exploration, and data analysis.
Use this skill for data pipeline work — ingestion with dlt, transformations with sqlmesh, analytics with DuckDB/MotherDuck, DataFrames with polars, notebooks with marimo, and project management with uv.
Connect SaaS data (HubSpot, Stripe, Salesforce, GitHub, Slack, etc.) to Wren Engine for SQL analysis. Guides the user through the full flow: install dlt, pick a SaaS source, set up credentials, run the data pipeline into DuckDB, then auto-generate a Wren semantic project from the loaded data. Use this skill whenever the user mentions: connecting SaaS data, importing data from an API, dlt pipelines, loading HubSpot/Stripe/Salesforce/GitHub/Slack data, querying SaaS data with SQL, or setting up a new data source from a REST API. Also trigger when the user already has a dlt-produced DuckDB file and wants to create a Wren project from it.
Design an end-to-end MotherDuck pipeline. Use when choosing raw, staging, and analytics boundaries, bulk ingestion paths, transformation sequencing, publication targets, or whether DuckLake is actually required.
Roll out self-serve analytics on MotherDuck for internal teams. Use when deciding the first governed dataset, the first Dive or share, ownership boundaries, and the rollout path from one audience to broader adoption.
Design a MotherDuck-backed customer-facing analytics app. Use when building embedded or product analytics for external users and the decision depends on per-customer isolation, backend routing, service-account boundaries, read scaling, or Hypertenancy-style patterns.
Design and build database schemas and data models in MotherDuck. Produces a file-based project scaffold. Use when creating tables, choosing data types, defining relationships, or restructuring data for analytics workloads.
Create, edit, manage, share, or embed MotherDuck Dives. Use when the work involves Dive authoring, live React + SQL components, MCP get_dive_guide, useSQLQuery, local preview, version history, Dives-as-code, required resources, team sharing, or embedded Dive sessions.
Explain MotherDuck security, governance, and access-control patterns. Use when a security_compliance_owner, technical_owner, or application_builder is asking about residency, access boundaries, service accounts, isolation, sharing, or governance posture.
Build a live MotherDuck dashboard as a Dive. Use when composing one shareable KPI, trend, and breakdown story over existing MotherDuck data, especially when the result should stay a saved workspace artifact rather than a full application.
Decide when DuckLake is the right MotherDuck storage pattern. Use when evaluating fully managed DuckLake, BYOB, own-compute DuckLake access, data inlining, object-storage layout, or file-aware maintenance instead of native MotherDuck storage.
Explain MotherDuck pricing and ROI tradeoffs. Use when an economic_buyer, technical_owner, or analytics_lead is asking about spend, budget guardrails, workload cost drivers, plan fit, or whether MotherDuck is worth adopting.