Dbt Transformation Patterns Agent Skill

Ab Test Setup

by lingxling

×1

Structured guide for setting up A/B tests with mandatory gates for hypothesis, metrics, and execution readiness.

Keeper Stress Analysis

by ClickHouse

vendor

Analyze ClickHouse Keeper stress-test results from play.clickhouse.com / keeper_stress_tests data warehouse. Use whenever the user asks about Keeper performance, validates Keeper PRs against stress dashboards, investigates regressions or improvements in Keeper nightlies, asks about specific date windows / SHAs / PR-sets in Keeper stress tests, wants per-PR or window-vs-window comparisons, asks "did this PR break Keeper", asks "what changed in Keeper between dates", or wants a summary report of Keeper stress runs. Triggers on terms like "keeper stress", "keeper PR", "keeper p99", "keeper memory", "keeper rps", "keeper nightly", "keeper-stress-tests", "keeper validation", "keeper regression", or any question referencing the keeper-stress Grafana dashboard. ALWAYS prefer this skill over re-deriving the workflow from scratch — it captures hard-learned lessons about cgroup-vs-Keeper memory, bench-harness confounds, noise floors, and per-PR attribution limits.

Dbt Transformation Patterns

by wshobson

Master dbt (data build tool) for analytics engineering with model organization, testing, documentation, and incremental strategies. Use when building data transformations, creating data models, or implementing analytics engineering best practices.

Dashboard Testing

by microsoft

vendor

Guide for writing tests for the Aspire Dashboard. Use this when asked to create, modify, or debug dashboard unit tests or Blazor component tests.

Canvas2d Data Visualization

by openai

vendor

Render data visualizations with Canvas2D. Use when the visualization needs high mark counts, fast redraws, immediate-mode rendering, custom hit testing, or a hybrid Canvas plus SVG or HTML architecture.

Analyze Test Report

by pytorch

vendor

Analyze torch-tensorrt local test results and drive failures to a fix. Use when the user pastes a test report / summary, asks why tests failed, asks to triage or fix failing tests, or mentions the JUnit/test-summary output from `just tests-report` / `just test-summary`. Covers where the JUnit XMLs live, how to read the consolidated report, how to reproduce a single failure, and how to categorize (real bug vs torch-API change vs OOM/skip vs flake).

Parallel Investigation

by rohitg00

Coordinates parallel investigation threads to simultaneously explore multiple hypotheses or root causes across different system areas. Use when debugging production incidents, slow API performance, multi-system integration failures, or complex bugs where the root cause is unclear and multiple plausible theories exist; when serial troubleshooting is too slow; or when multiple investigators can divide root-cause analysis work. Provides structured phases for problem decomposition, thread assignment, sync points with Continue/Pivot/Converge decisions, and final report synthesis.

Bench Regression

by pytorch

vendor

Investigate a Helion benchmark dashboard regression (helionlang.com/dashboard) — find the cause and classify it. Auto-activate when the user reports a perf drop/spike on a dashboard platform (e.g. b200 cute) around a given date.