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Found 1,702 Skills
Database development and operations workflow covering SQL, NoSQL, database design, migrations, optimization, and data engineering.
Database migration best practices — schema changes, zero-downtime migrations, rollback strategies, and data migration patterns. Reference when modifying database schemas.
Grafana Cloud Database Observability — query-level performance insights for MySQL and PostgreSQL. Covers setup with Grafana Alloy, query samples, visual explain plans, RED metrics, pg_stat_statements and Performance Schema integration, and correlation with application traces. Use when monitoring database performance, diagnosing slow queries, setting up database observability for MySQL or PostgreSQL (self-managed, RDS, Aurora, Azure, Cloud SQL), or correlating DB metrics with APM data.
Open-source lightweight cross-platform database management tool built with Tauri, Vue 3, and Rust supporting MySQL, PostgreSQL, SQLite, Redis, MongoDB, DuckDB, ClickHouse, and SQL Server.
Query the Ensembl database to resolve gene, transcript, and protein IDs, fetch genomic or protein sequences, retrieve gene structures (exons), and get variant consequence and effect predictions (VEP). Use this skill as a primary ID translator, genomic sequence database and variant effect prediction tool.
Identify domains, families, and sites in proteins; find all proteins in a family or sharing a domain; explore species distribution for a domain; annotate genomes with protein families and GO terms. InterPro combines 14 databases (e.g., Pfam, CDD) into one searchable resource. InterPro-N significantly expands annotation and sequence coverage with deep learning. Includes domain architecture (IDA) search.
Queries the UniBind database for experimentally validated transcription factor (TF) binding sites. Use when retrieving direct TF-DNA interaction datasets, downloading binding site coordinates (BED/FASTA) for local analysis, or listing available datasets by species, cell line, or TF name. Don't use to query specific intervals, locations, genes, motif models or expression data.
Query the STRING database for protein-protein interactions (PPIs), functional enrichment, and homology. Use when the user asks about interactions between specific proteins, interaction evidence, confidence scores, protein interaction partners, or pathway enrichments.
Use when needing clinical significance, pathogenicity classifications (e.g., Pathogenic, Benign, VUS), clinical evidence rationales, or finding "hard positive" benchmark controls for human genomic variants.
Use DBML as the standard format for database schema documentation. Apply this whenever creating, updating, reviewing, or repairing database docs, ERDs, schema diagrams, table inventories, migration summaries, Doctrine migration changes, SQL schema docs, ORM model docs, or CI schema drift failures. Prefer db/schema.dbml over Mermaid, Prisma schema, ad hoc Markdown tables, or prose-only database documentation unless the user explicitly requests another format.
Auto-activate for pytest_databases, Docker DB fixtures, PostgreSQL/pgvector/AlloyDB Omni/MySQL/Oracle/MSSQL/CockroachDB/Yugabyte/MongoDB/GizmoSQL/Redis/Spanner/BigQuery/Azurite/MinIO tests. Not for mocked DBs.
This skill should be used when the user wants to add a database (Postgres, Redis, MySQL, MongoDB), says "add postgres", "add redis", "add database", "connect to database", or "wire up the database". For other templates (Ghost, Strapi, n8n, etc.), use the templates skill.