Databuddy

Work inside the Databuddy monorepo for internal implementation, debugging, review, and refactoring. Use only for repository code changes across dashboard, api, basket, links, docs, uptime, SDK, tracker, auth, RPC, database schema, ClickHouse, or shared packages. Do not use for external SDK, API, CDN, feature flag, or LLM observability integration guidance; use databuddy instead.

Help external users integrate Databuddy into their own apps. Use for SDK setup, React/Vue/vanilla browser tracking, Node/server event tracking, custom event planning, attribution, feature flag evaluation, experiments, Databuddy DevTools, REST analytics queries, and event ingestion. Do not use for Databuddy monorepo implementation work; use databuddy-internal.

Integrate Databuddy analytics using the SDK, REST API, or MCP. Use when implementing analytics tracking, feature flags, custom events, Web Vitals, error tracking, LLM observability, MCP agents, or querying analytics data programmatically.

Use whenever the Databuddy MCP server is available and the user wants their analytics, errors, vitals, insights, comparisons, anomalies, top movers, flags, links, or annotations queried. Covers get_data, ask, capabilities, summarize_insights, compare_metric, top_movers, detect_anomalies, get_schema, list/save/forget memory, and workspace mutations. Not for SDK integration help (use databuddy) or monorepo implementation (use databuddy-internal).

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.

Reduce codebase slop by deleting code, flattening abstractions, and replacing custom helpers/types/assertions with native SDK/npm helpers or straightforward schemas (for example Zod). Use when asked to simplify, delete code, or "desloppify" TypeScript/Bun/Nuxt code.

Build or review Bun fullstack TypeScript code with Drizzle-backed SQL. Use for backend or cross-layer changes touching API/domain logic, schema or query design, migrations, runtime/type debugging, and boundary validation between contracts, business rules, and persistence.

Design, implement, and review software using vertical slices (feature-first architecture) instead of horizontal layers. Use when creating a new feature, refactoring layered code (controllers/services/repositories), defining clear API-domain-data boundaries, improving slice-level testability, or reducing cross-module coupling in backend or fullstack TypeScript projects.