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Found 711 Skills
TypeScript 6+ guidance for project development, tsconfig configuration, diagnostics, module resolution, deprecations, and modern standard-library typings. Use when building or maintaining TypeScript 6+ projects, debugging compiler behavior, or working through TS 6-specific defaults and tooling such as `#/` subpath imports, `ignoreDeprecations`, `RegExp.escape`, `Temporal`, and `--stableTypeOrdering`. Triggers on typescript 6, ts 6, stableTypeOrdering, ignoreDeprecations, types array, noUncheckedSideEffectImports, baseUrl deprecated, moduleResolution node deprecated, and subpath imports.
A repository of BigQuery-specific logic, knowledge, and specialized standards. Use this skill whenever you are doing anything with BigQuery, including: 1. BigQuery query optimization 2. BigFrames Python code 3. BigQuery ML/AI functions.
This skill should be used when the user asks to 'optimize performance', 'check for memory leaks', 'improve performance', 'performance tuning', 'adjust performance', or mentions performance issues in Adobe Animate or CreateJS projects.
Search and retrieve documentation for libraries via Context7 API. Use for getting up-to-date documentation context for programming libraries like React, Next.js, etc.
Configure Frigate NVR with optimized YAML, object detection, recording, zones, and hardware acceleration. Use when setting up Frigate cameras, troubleshooting detection issues, configuring Coral TPU/OpenVINO, or integrating with Home Assistant.
Create and debug Home Assistant automations, scripts, blueprints, and Jinja2 templates. Use when working with triggers, conditions, actions, automation YAML, scripts, blueprints, or template expressions. Activates on keywords: automation, trigger, condition, action, blueprint, script, template, jinja2.
Review code for best practices, security issues, and potential bugs. Use when reviewing code changes, checking PRs, analyzing code quality, or performing security audits.
Query Prometheus and Loki billing metrics from Grafana. Use when discussing observability costs, active series, ingestion rates, storage usage, or cardinality analysis.
Analyze images using AI with the understand_image tool
Expert guidance for creating, modifying, and optimizing dbt pipelines for BigQuery. Use this skill whenever user asks for generating or modifying a dbt model or project. Activate this skill when the user - Creates, modifies, or troubleshoots **dbt models or pipelines** - Needs to **optimize SQL** within a dbt project - Is **setting up a new dbt project** or configuring existing one
This skill guides the use of Jupyter notebooks for data analysis, exploration, and visualization, particularly with BigQuery. It outlines best practices for notebook execution and validation (supporting both cell-by-cell execution and full notebook generation depending on tool availability), library installation, and structuring notebooks for clarity. It also covers specific rules for data cleaning, plotting, and integrating with BigQuery SQL and machine learning workflows. Relevant when any of the following conditions are true: 1. The user request involves a data analysis, data exploration, data visualization, or data insights task that requires multiple steps, queries, or visualizations to answer. 2. The user explicitly requests a notebook (.ipynb). 3. You are creating, editing, or executing cells in a Jupyter notebook. 4. You need to query BigQuery from within a notebook. DO NOT use the Python BigQuery client library; instead, you MUST use the `%%bqsql` magics explained in this skill.
Use these skills when you need to provision new Cloud SQL instances, create databases and users, clone existing environments, and monitor the progress of long-running operations.