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Found 199 Skills
SQL and NoSQL schema design with normalization, indexing, and migration patterns. Use when designing database schemas, creating tables, optimizing slow queries, or planning database migrations.
RICE, ICE, WSJF, MoSCoW and other prioritization frameworks for product backlogs. Use when scoring features, ranking initiatives, or deciding what to build next.
Tracks competitor page changes over time. Captures snapshots, detects diffs, alerts on significant changes. Supports Tavily site discovery for URL enumeration. Use when monitoring competitive intelligence, pricing changes, or feature tracking.
Core Web Vitals optimization for LCP, INP, CLS with 2026 thresholds, performance budgets, and RUM. Use when improving page performance, diagnosing CWV regressions, or setting performance budgets.
Multi-directory context patterns for monorepos. Use when working with --add-dir, per-service CLAUDE.md, or separating root vs service context
Retrieval-Augmented Generation patterns for grounded LLM responses. Use when building RAG pipelines, constructing context from retrieved documents, adding citations, or implementing hybrid search.
DDD aggregate design patterns for consistency boundaries and invariants. Use when designing aggregate roots, enforcing business invariants, handling cross-aggregate references, or optimizing aggregate size.
FastAPI advanced patterns including lifespan, dependencies, middleware, and Pydantic settings. Use when configuring FastAPI lifespan events, creating dependency injection, building Starlette middleware, or managing async Python services with uvicorn.
RFC 9457 Problem Details for standardized HTTP API error responses. Use when implementing problem details format, structured API errors, error registries, or migrating from RFC 7807.
Test data management with fixtures and factories. Use when creating test data strategies, implementing data factories, managing fixtures, or seeding test databases.
Value Proposition Canvas, Jobs-to-be-Done (JTBD), Build/Buy/Partner decisions, and strategic product frameworks. Use when validating value propositions, understanding customer needs, or making strategic technology decisions.
Local LLM inference with Ollama. Use when setting up local models for development, CI pipelines, or cost reduction. Covers model selection, LangChain integration, and performance tuning.