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Found 1,194 Skills
MUST USE when reviewing ClickHouse schemas, queries, or configurations. Contains 28 rules that MUST be checked before providing recommendations. Always read relevant rule files and cite specific rules in responses.
Diagnose ClickHouse merge performance, part backlog, and 'too many parts' errors. Use for merge issues and part management problems.
Track and diagnose ClickHouse ALTER UPDATE, ALTER DELETE, and other mutation operations. Use for stuck mutations and mutation performance issues.
Diagnose ClickHouse issues by analyzing system.part_log (part creation, merges, mutations, downloads, removals, moves). Use for too many parts / micro-batch inserts, merge backlog or slow merges, mutation storms (ALTER DELETE/UPDATE), unusual replication DownloadPart churn, unexpected RemovePart spikes, or ZooKeeper/Keeper znode growth correlated with part activity.
Diagnose ClickHouse SELECT query performance, analyze query patterns, identify slow queries, and find optimization opportunities. Use for query latency and timeout issues.
Neo4j Cypher Shell skill. Connect to instances, run Cypher queries, and retrieve full graph schemas via cypher-shell CLI.
Search and analyze academic literature. Find papers, understand research methodologies, and synthesize academic findings for research projects.
Discovers all projects in a .NET solution, classifies each for Oracle-to-PostgreSQL migration eligibility, and produces a persistent master migration plan. Use when starting a multi-project Oracle-to-PostgreSQL migration, creating a migration inventory, or assessing which .NET projects contain Oracle dependencies.
Creates structured bug reports for defects found during Oracle-to-PostgreSQL migration. Use when documenting behavioral differences between Oracle and PostgreSQL as actionable bug reports with severity, root cause, and remediation steps.
Schema migration strategies for evolving applications including adding new fields, backfilling data, removing deprecated fields, index migrations, and zero-downtime migration patterns
Build semantic search with Cloudflare Vectorize V2. Covers async mutations, 5M vectors/index, 31ms latency, returnMetadata enum changes, and V1 deprecation. Prevents 14 errors including dimension mismatches, TypeScript types, testing setup. Use when: building RAG or semantic search, troubleshooting returnMetadata, V2 timing, metadata index, dimension errors, vitest setup, or wrangler --json output.
High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance.