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…
Augment a Wren project with business context that DB schema cannot carry — enum value meanings, units (USD vs cents, ms vs sec), NULL semantics, magic sentinels (-1 = unknown), soft-delete default filters, business synonyms, time-grain / TZ conventions, cross-system identifiers, currency rules, canonical-table…
Wren Engine CLI workflow guide for AI agents. Answer data questions end-to-end using the wren CLI: gather schema context, recall past queries, write SQL through the MDL semantic layer, execute, and learn from confirmed results. Use when: user asks a data question, requests a report or analysis, asks about metrics…
Guidance on writing fast, robust, modern Svelte code. Load this skill whenever in a Svelte project and asked to write/edit or analyze a Svelte component or module. Covers reactivity, event handling, styling, integration with libraries and more.
A command-line guide for querying fund information, including profiles, managers, holdings, prices, returns, financial data, news, and exchange-traded fund snapshots. A command-line tool is a program controlled by typed terminal commands.
A command-line tool entry for retrieving ordinary Chinese A-share market data, including snapshots, historical price bars, trading calendars, adjustment factors, and company actions.
Use when implementing, debugging, packaging, or host-enabling onetcli WASM connection importers such as DBeaver, Navicat, Navicat Lite, Termius, connection-import.wit components, wasm32-wasip2 importers, composite extension manifests, local importer visibility, or connection import UI freezes.
Use when working in the Navop repository on CHANGELOG.md, version-tag preparation, GitHub Releases, or R2 updater release notes, especially when bilingual Chinese and English notes must be generated, reviewed, synchronized, published, or verified.
The enforcement arm of the handbook rules (handbook/meta/handbook/): the checks that keep the documentation system whole. Run it when a change touches documentation — handbook pages, free-floating .md files, script headers, generated indexes — and periodically as a scheduled sweep.
Build, validate, and manage semantic models using Sidemantic. Use when asked to create a semantic layer, define metrics/dimensions, model a database schema, generate models from SQL queries, import from Cube/dbt/LookML, or set up analytics definitions. Prioritizes CLI-first workflows, with YAML and optional Python API…
Answer analytical, KPI, metric, trend, cohort, and business-performance questions through a Sidemantic semantic layer. Use when asked to analyze data, explain why a metric changed, compare segments or periods, calculate a business measure, or explore warehouse data when Sidemantic MCP tools or semantic model files are…
Build interactive analytics webapps, demos, dashboards, or embedded app surfaces from Sidemantic semantic models using copyable component primitives and deterministic query inspection. Use when asked to create a web UI around Sidemantic models, generate a metric explorer, copy reusable analytics components into a…
Use textual agent instructions for GIS and geospatial work: source discovery and provenance, vector/raster/point-cloud pipelines, CRS and metric analysis, spatial SQL, routing and isochrones, QGIS projects, tile generation, and web maps. Use advanced tools and formats such as OSM, Overture, STAC, Sentinel/Landsat…
Backtesting, cross-validation, evaluation metrics, and conformal prediction intervals for the anofoxforecast DuckDB extension. Use when evaluating forecast accuracy, comparing models with time-series-aware CV, computing metrics (MAE / RMSE / MAPE / MASE / coverage), or attaching distribution-free prediction intervals…
Seasonality, changepoint, peak, and decomposition detection for the anofoxforecast DuckDB extension. Use when identifying seasonal periods before configuring seasonal forecasting models, detecting structural breaks, analysing peak timing regularity, or decomposing a series into trend / seasonal / residual components.
Forecasting models and the tsforecastby / tsforecastvarby API surface of the anofoxforecast DuckDB extension. Covers 36 models (baseline, exponential smoothing, state-space ARIMA + Kalman, classical GARCH, Theta, multi-seasonal, intermittent-demand, distributional Laplace with three variants, panel/global…
Produce a knowledge dashboard with recent entries, corrections, expiring soon, stale knowledge, and unresolved items. In team mode, also shows team activity, related entries from teammates, and the review queue.