glassflow

UI/UX design intelligence. 67 styles, 96 palettes, 57 font pairings, 25 charts, 13 stacks (React, Next.js, Vue, Svelte, SwiftUI, React Native, Flutter, Tailwind, shadcn/ui). Actions: plan, build, create, design, implement, review, fix, improve, optimize,…

Loads and applies product/UX design principles and design system when designing or implementing features. Use when designing a new feature, implementing a new feature, or when the user asks for design or UX input.

Next.js 16 Cache Components - PPR, use cache directive, cacheLife, cacheTag, updateTag

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js…

Keeps project documentation aligned with implementation. Use when adding a new feature, changing architecture, adding a module or store slice, adding an implementation (e.g. SSE/Kerberos-like), or when the user asks to update docs, align documentation with…

Use when the user reports a GlassFlow pipeline failure, missing events, or unexpected behavior. Starts with component logs (via kubectl or whichever log backend the OTel Collector routes to) and only reaches for metrics when the logs are clean or ambiguous.…

Use when the user asks to create a GlassFlow ETL pipeline. Walks through source configuration (Kafka or OTLP), optional dedup/filter/transform stages, and ClickHouse sink mapping, then submits the v3 config to the GlassFlow API. Triggers on phrases like…

Use when a GlassFlow pipeline is experiencing backpressure, sustained sink lag, or throughput pain. Reads GlassFlow's emitted Prometheus metrics to confirm the bottleneck (backpressure gauges, stream depth ratio, source vs sink rate, sink batch size…

Use when you need cross-source context about this project's systems (recent deploys, logs, metrics, entities, correlated timelines), OR when organizing Tares itself — creating sources, labels, and views. Tares is the data plane; read it via the tares MCP…

Installs Tares, the open-source platform for always-on AI agents, starts the daemon, adds a first source over the HTTP API, connects the agent it runs inside over MCP, and proves the connection with one read. Use when the user asks an agent to install or set…

Use after pushing a new git tag (vMAJOR.MINOR.PATCH) on the operator main branch — bumps the Helm chart version, updates appVersion + operator image tag, and syncs the CRD into the chart if it changed.