Generates a delivery-focused status report for a named Rittman Analytics client engagement. Anchored on SOW milestones and sprint cadence — not a relationship or commercial report. Reports milestone status (on track / at risk / slipping), tickets and MRs delivered, bugs raised and resolved, decisions owed by the client, cross-cutting risks, and client and team sentiment. Pulls from Fathom meeting transcripts, client Slack channels (external and internal), and Atlassian where available. Use when Mark asks for delivery status, project status, milestone status, sprint status, "where are we on [client]", "is [client] on track", or "what's slipping on [client]". Triggers on any client name (Client A, Client B, Client C, Client D, Client E, Barton Peveril, Client F, Client H, Client I, Client J) plus a delivery framing.
Proactive skill for building Dagster orchestration layers. Auto-activates when creating or modifying Dagster assets, schedules, sensors, or components, or when working on the orchestration artifact in a Wire project. Covers the assets-first pattern, dagster-dbt integration, automation (schedules, sensors, declarative automation), the component framework, and CLI usage (dg dev, dg launch, dg check, dg scaffold).
Proactive skill for answering business analytics questions using dbt's Semantic Layer, Discovery API, or direct SQL. Auto-activates when a user asks a data or metrics question against a dbt project (e.g. "What were total sales last quarter?", "Show me top customers by revenue"). Uses a 4-level escalation — Semantic Layer first, modified compiled SQL, model discovery, manifest analysis. Always exhausts all options before saying "cannot answer."
Proactive skill for generating Mermaid flowchart diagrams of dbt model lineage. Auto-activates when a user asks to visualise dbt model dependencies, create a lineage diagram, or show the dbt DAG. Uses MCP get_lineage tools first, then manifest.json parsing, then direct code parsing as fallbacks. Produces colour-coded diagrams matching Wire's naming conventions.
Proactive skill for validating dbt models against coding conventions. Auto-activates when creating, reviewing, or refactoring dbt models in staging, integration, or warehouse layers. Validates naming, SQL structure, field conventions, testing coverage, and documentation. Supports project-specific convention overrides and sqlfluff integration.
Proactive skill for creating dbt unit tests. Auto-activates when working with dbt model testing, mock inputs/outputs, or transformation validation. Covers the Model-Inputs-Outputs pattern, format selection (dict/CSV/SQL), BigQuery-specific caveats, and production deployment guidance.
Generate an Oracle Analytics Cloud (OAC) semantic model in SMML (Semantic Modeler Markup Language) from a dbt project. Use when the user wants to build, convert, or scaffold an OAC semantic model from dbt models — generate SMML, the physical/logical/presentation layers, measures, hierarchies and role-playing dimensions — driven by dbt metadata plus `meta.oac` annotations in schema.yml. Triggers: "generate SMML", "dbt to OAC semantic model", "build the OAC semantic layer from dbt", "create logical/physical/presentation layer from dbt". For hand-authoring, editing, or reviewing SMML directly (no dbt project), use the sibling `smml-semantic-modeling` skill instead — this skill's `meta.oac` vocabulary and generator are built on that skill's modeling knowledge.
Skill for generating a standardised Wire Framework & Claude Code usage review for a client engagement. Activates when the user asks to review Wire usage, audit Claude Code activity, or generate a project review for a client. Gathers usage telemetry from BigQuery, Wire artifacts from the delivery GitHub repo, Jira tickets, and Fathom call transcripts, then produces a structured review document in wire/docs/reviews/.